University Medical
Resume:
Trevor John Hastie
Stanford, CA 94305
Home Phone&FAX: 650-***-****
Department of Statistics Born: June 27, 1953, South Africa
Sequoia Hall Married, two children
Stanford University U. S. citizen
Stanford, CA 94305 E-Mail: abqssd@r.postjobfree.com
650-***-**** Fax: 650/725-8977
Updated: October 29, 2012
Present Position
2006-2009 Chair, Department of Statistics, Stanford University.
2005-2006 Associate Chair, Department of Statistics, Stanford University.
1999- Professor, Statistics and Biostatistics Departments, Stanford University. Founder
and co-director of Statistics department industrial a liates program.
1994-1998 Associate Professor (tenured), Statistics and Biostatistics Departments, Stan-
ford University.
Research interests include nonparametric regression models, computer in-
tensive data analysis techniques, statistical computing and graphics, and
statistical consulting. Currently working on adaptive modeling and predic-
tion procedures, signal and image modeling, and problems in bioinformatics
with many more variables than observations.
Professional Duties and Committees
2010-2011 Served on NAS Massive Data Analysis panel (Michael Jordan chair)
1994 - 2001 Associate Editor, Annals of Statistics
1995 - Associate Editor, J. Data Mining and Knowledge Discovery.
1994 Chair, Statistical Computing Section, ASA
1992 Program Chair, Statistical Computing Section, ASA
1989-1991 Associate Editor, Technometrics
1989 Secretary-Treasurer, Statistical Computing Section, ASA
Education
12/84 Stanford University, Stanford, California Ph.D, Department of Statis-
tics (Werner Stuetzle, advisor)
1/79 University of Cape Town, Cape Town, South Africa First Class Masters
Degree in Statistics (June Juritz, advisor).
12/76 Rhodes University, Grahamstown, South Africa Bachelor of Science
Honors Degree in Statistics.
12/75 Rhodes University, Grahamstown, South Africa Bachelor of Science
Degree (cum laude) in Statistics, Computer Science and Mathematics.
Awards and Honors
2011 Elected fellow of South African Statistical Society
2009-2010 Mellon Mentor, University of Cape Town
October 29, 2012 2
2009 Buehler-Martin lecturer, University of Minnesota.
2003 O cial visitor (with Sir David Cox) at 50th anniversary of South African
Statistical Association.
1998 Elected fellow of the American Statistical Association.
1997 IMS special invited speaker, IMS Paci c regional meeting, Taipei.
1996 1996 Myrto Lefkopolou award, Harvard Biostatistics Department
1996 1996 Craig award, University of Iowa.
1996 Elected fellow of the Institute of Mathematical Statistics.
1994 Elected member of International Statistics Institute.
1982 Harry Crossley Bursary, University of Cape Town. Awarded to assist in
overseas doctoral research.
1980 Sir Robert Kotze Bursary, University of Cape Town. Awarded to assist in
overseas doctoral research.
1979 Elected Fellow of Royal Statistical Society.
1979 Queen Victoria Scholarship, University of Cape Town. Awarded on the basis
of Masters degree thesis for overseas doctoral research.
1978 National Scholarship, Rhodes University. Awarded on the basis of honors
degree results for overseas doctoral research.
1977 University Research Scholarship, Rhodes University, Grahamstown. Awarded
on basis of honors degree results for post-graduate research at Rhodes Uni-
versity.
1975 University Foundation Scholarship, Rhodes University. Awarded to the
Most Outstanding First Degree Candidate during the period 1973 -1975.
1973 University Scholarship, Rhodes University. Awarded to the top rst year
student in the University in 1973.
Personal Research Grants
7/11 6/15 NIH 8 REB001988E Hastie/Johnstone/Tibshirani. Continuation of New
Statistical Methods for Medical Signals and Imaging .
8/10 7/14 NSF DMS-1007719 Hastie Flexible Statistical Modeling .
7/08 6/12 NIH RO1-EB001988-12 Hastie/Johnstone/Tibshirani. Continuation of New
Statistical Methods for Medical Signals and Imaging .
8/05 7/09 NSF DMS-0505676 Hastie Flexible Statistical Modeling .
7/03 6/07 NIH RO1-EB0011988-08 Hastie/Johnstone/Tibshirani. Continuation of New
Statistical Methods for Medical Signals and Imaging
7/02 7/05 NSF DMS 0204612 Hastie Flexible Statistical Modeling .
9/99 6/03 NIH-2RO1-CA72028 Hastie/Johnstone/Tibshirani Continuation of New Sta-
tistical Methods for Medical Signals and Imaging
7/98 6/01 NSF DMS-9803645 Hastie Flexible Statistical Modeling .
9/96 8/99 NIH RO1-CA-72028-01 Hastie/Johnstone New Statistical Methods for Med-
ical Signals and Imaging
7/95 6/98 NSF DMS-9504495 Hastie Flexible Regression and Classi cation
Ph.D. Student Supervision
Neil CrellinGraduated 1996. Thesis Visualization and Regression of Image Sequence
Data . Google, Mountain View.
Y. Dan Rubenstein Graduated 1998. Thesis Discriminative vs Informative Learning .
Founder and CTO of Re ectivity, a Silicon Valley micro-display manufac-
turer. Product Management Director, Google, Mountain View.
October 29, 2012 3
Gareth James Graduated 1998. Thesis Majority Vote Classi ers: Theory and Applica-
tions . Associate Professor in Statistics, Marshall School of Business, Uni-
versity of Southern California.
Dirk Ormoneit Postdoctoral Student 1999-2000. Head of research team, BlueCrest Finan-
cial, London.
Eva Cantoni Postdoctoral Student 1999-2000. Currently at Econometrics Department,
University of Geneva.
Mu Zhu Graduated 2001. Thesis Feature Extraction and Dimension Reduction with
applications to Classi cation and the Analysis of Co-Occurrence Data . As-
sociate Professor, Department of Statistics and Actuarial Science, University
of Waterloo, Canada.
Ji Zhu Graduated 2003. Thesis Flexible Statistical Modelling Associate Profes-
sor, University of Michigan.
Saharon Rosset Graduated 2003 (co-advising with Jerome Friedman). Thesis title: Boost-
ing and other Methods for following Regularization Optimized Coe cient
Paths . Statistics department, University of Tel Aviv, Israel.
Hui Zou Graduated 2005, Thesis title: Elasticnet Regularization and Beyond . Cur-
rently Assistant Professor, University of Minnesota.
Mee Young Park Graduated 2006, Thesis title Generalized Linear Models with Regular-
ization . Quantitative Analyst, Google Inc, Mountain View.
Gillian Ward Graduated 2007. Thesis title Problems in Ecological Modeling: Presence-
only Data and Boosted Mars . Technical team, Quantcast Inc, San Fran-
cisco.
Ping Li Graduated 2007. Thesis title Stable Random Projections and Conditional
Random Sampling, Two Sampling Techniques for Modern Massive Datasets .
Assistant Professor, Cornell University.
Donal McMahon Graduated 2009. Thesis title Research Synthesis for Multiway Tables
of Varying Shapes and Size
Rahul Mazumder Graduated June 2012. Thesis title Topics in Sparse Multivariate Statis-
tics
Michael Lim Current student
Will Fithian Current student
Jason Lee Current student
Hristo Paskov Spassimirov Current student; co-advising with John Mitchell, Stanford CS.
Work and Experience
1999 - Founder and Director, Stanford Statistic Department Industrial A liates
program.
3/86 8/94 Member of Technical Sta, Statistics and Data Analysis Research Group,
AT&T Bell Laboratories, 600 Mountain Ave, Murray Hill, New Jersey 07974.
7/92 Professor, Statistics Department, University of Cape Town sabbatical
5-month appointment.
4/92 Member of MSRI, Berkeley. Arranged a 3-day workshop on Neural Net-
works and Nonparametric Regression, with 20 invited participants.
1/85 1/86 Research biostatistician, South African Medical Research Council, Institute
for Biostatistics.
6/81 12/84 Graduate student, Stanford University, Stanford California.
Founded the department s Statistical Consulting Service, together with Rob
Tibshirani.
October 29, 2012 4
Member, Computations Research Group of Stanford Linear Accelerator Cen-
ter. Research in statistical (motion) graphics and non-parametric regression
methods. Group headed by Professor Jerome Friedman.
Statistical consulting projects include performance study for Syva corpo-
ration with Professor Bradley Efron, FDA study for Coherent Inc. with
Professor Lincoln Moses.
1/84 4/84 Visiting researcher/student, IBM Research, Zurich. On leave of absence
from Stanford. Worked on computer vision and computer typesetting (TEX)
projects, and Ph.D. dissertation.
1/77-9/80 Research o cer and consultant, Institute for Biostatistics, Medical Research
Council, Cape Town, South Africa. Consulting with other MRC bodies in
SA and University of Cape Town Medical School.
9/79 11/79 Biomathematics Department, Oxford University, Oxford, U.K. Research,
and consulting work with Professor Peter Armitage for Booths Pharmaceu-
tical company on logistic regression.
7/79 9/79 Johnson Space Center, Clear Lake City, Texas. Worked for two months in
the cellular analytical lab of Dr. Steve Kimzey, on an automated cytology
project.
2/79-7/79 London School of Hygiene and Tropical Medicine. Worked with Professor
Michael Healy as consultant and did research on classi cation procedures.
Projects included St. Lucia schistosomiasis study (Rockefeller Foundation)
and psycho-surgery validation study with the Neuro-surgical center of the
Brooks General Hospital.
Special Invited Talks and Workshops
8/2012 Keynote speaker, COMPSTAT 2012, Cyprus.
5/2012 Keynote speaker, 43rd Interface meeting, Rice University, Houston, Texas
10/2011 Keynote speaker, Chilean Statistical Society annual conference, Pucon, Chile.
8/2011 Keynote speaker, New Zealand Annual Statistics conference, Auckland.
4/2011 Delivered invited one day course on Statistical Learning co-organized by
Australian National University and CSIRO
8/2009 Presidents invited speaker, ISI meeting, Durban, South Africa.
7/09 Keynote speaker, useR! 2009 conference, Rennes, France.
1/09 3eme Cycle de Statistique et Probilites Appliquees, Les Diablerets, Switzer-
land invited lecturer.
12/08 Keynote speaker, International Association of Statistical Computing, Yoko-
hama, Japan.
12/08 Inaugural Pao-Lu Hsu lecturer at Peking University
8/08 Keynote speaker, KDD conference, Las Vegas.
8/08 Invited speaker, Joint statistical meetings, Denver, Colorado.
5/08 Three day invited data-mining workshop, BBVA foundation, Madrid.
8/07 Invited Speaker, Statistics in Technology and Science. Satellite meeting of
ISI, Porto, Portugal.
3/07 Keynote Speaker, AI& Statistics, Puerto Rico.
9/06 Keynote Speaker, RSS 2006, Belfast, Northern Ireland.
6/06 Keynote Speaker, User-R conference, Vienna.
6/06 Keynote Speaker, 50th anniversary of the School of Economics, Erasmus
University, Rotterdam.
10/05 Keynote Speaker, 5th Australian Microarray Conference, Barossa Valley.
5/05 Keynote Speaker, 11th ASMDA (Applied Stochastic Models and Data Anal-
ysis) conference, Brest, France.
October 29, 2012 5
2/05 Conference Keynote Speaker, First South African Data Mining Conference,
Stellenbosch, South Africa.
11/04 Keynote Speaker, SAS datamining conference, Las Vegas.
8/04 Special Guest, Ecology conference, Riederalp.
11/03 O cial conference guest (with Sir David Cox), 50th anniversary of the South
African Statistical Association.
9/03 Plenary speaker, Italian classi cation society meeting, U. Bologna.
8/03 Invited speaker, ASA 2003, San Francisco.
1/03 Invited speaker, SPIE conference of Document Retrieval and Recognition,
Santa Clara, California.
8/02 Keynote speaker, Compstat 2002, Berlin, Germany.
8/02 Invited Speaker, ASA 2002, New York.
7/02 Invited speaker at Current Trends and Advances in Nonparametric Statis-
tics, Hersonissos, Crete.
7/02 Invited speaker at 17th International Workshop on Statistical Modeling in
Chania, Crete.
6/02 Plenary speaker at Multiple Classi cation Systems, Sardinia.
5/02 Plenary speaker, Spring Research Conference, Michigan.
12/01 Invited speaker at New trends in optimization and computational algo-
rithms, Kyoto, Japan
10/01 Keynote speaker at Splus user conference, Philadelphia.
7/01 Special invited speaker at GLM/GAM in Ecology conference at Riederalp,
Switzerland.
4/00 Invited speaker at Snobird conference, Utah; invited to speak on DNA ex-
pression arrays.
7/99 Special invited visitor of Norwegian Statistical Society, to spend 3 weeks
in Oslo collaborating with young Norwegian investigators [grant covers ex-
penses for myself and family for entire stay]
3/99 Invited speaker, Spanish Biometrics Society meeting, Mallorca, Spain.
1/99 Tutorial lecturer, American Association for Arti cial Intelligence biennial
meeting, Fort Lauderdale, Fl. Boosting
12/98 Invited speaker, International Biometrics Society meeting, Cape Town, South
Africa
8/98 Plenary Speaker, Sinape. Annual Brazilian Statistical conference, Caxambu.
7/98 Keynote speaker, Australian Statistical Society Meeting, Gold Coast.
8/97 Special invited IMS keynote address Modern Advances in Classi cation,
Taipei, Taiwan.
12/96 Invited tutorial From Statistics to Neural Networks, annual NIPS meeting,
Denver, Colorado.
11/96 Invited speaker at memorial conference for Stefano Franscini, Acona, Switzer-
land.
11/96 Myrto Lefkopolou lecture and award, Harvard University.
7/96 Invited speaker at International Modeling Conference, Orvieto, Italy.
6/96 Short course on Modern Regression and Classi cation at Applied Statistics
week, University Pompeu Fabra, Barcelona.
4/96 Short course on Modern Regression and Classi cation, ENAR, Richmond.
4/96 Craig lecture and award, Iowa State University.
3/96 3eme Cycle de Statistique et Probilites Appliquees, Villars, Switzerland
invited lecturer.
4/95 Invited speaker at Neural Network and Statistics workshop at Edinburgh,
RSS special session at Edinburgh, and to visit Bristol and Bath in UK.
October 29, 2012 6
1/95 Invited short course on Nonparametric regression and Classi cation, AI &
Statistics workshop, Fort Lauderdale.
12/94 Invited to deliver paper at Neural Information Processing Conference, Den-
ver.
6/94 Invited paper at Statistics in Industry conference at University of Tokyo,
Japan.
9/93 Keynote speaker, STATCOMP 93, Wollongong, Australia.
6/93 Invited speaker, NATO ASI meeting on Neural Networks and Statistics, Les
Arcs, France.
3/92 Statistical Models in S, Interface meeting, College Station, Texas.
9/91 Keynote speaker at International Genstat meeting, Papendal, Holland.
6/91 Keynote speaker at US Classi cation Society Meeting, New Brunswick, NJ.
6/91 Modelling Human Signatures, Total Least Squares Conference, Leuven,
Belgium.
3/91 Generalized Additive Models in S, International Smoothing Workshop,
Heidelberg, Germany.
9/90 Statistical Models in S, COMPSTAT, Dubrovnik, Yugoslavia.
8/90 Keynote speaker at Generalized Linear Models workshop at State Univer-
sity of New York, Stonybrook.
8/90 One-day short course at ASA meeting (Anaheim) on Generalized Additive
Models. Talk: Con dence Sets for Nonparametric Regression at the same
meeting.
6-7/90 Visiting Professor, Summer Quarter, Stanford University. Taught 7-week
course on Generalized Additive Models.
2/90 Statistical Models in S, First International S Conference, Wellington, New
Zealand.
8/89 General Methodology lecture, ASA, Washington.
6/89 Two-day speaker, Diagnostics Quarter, University of Minnesota.
4/89 Short course on Generalized Additive Models, Canadian Statistical Meet-
ings, Ottawa.
2-3/89 Three-day course on Generalized Additive Models, Australian National
University, Canberra.
8/87 Correspondence Analysis, 4-hour tutorial (with Michael Greenacre), ASA
meeting, San Francisco.
7/87 A new algorithm for matched case-control studies with applications to ad-
ditive models, 2nd International Data Analysis Meeting, Perugia, Italy.
3/87 Generalized additive models: the additive Cox Model, Biometrics Meet-
ings, Dallas, TX.
2/87 Principal Pro les, Interface meeting, Philadelphia, PA.
8/86 Generalized additive models: a GAIM analyst s toolbox, ASA annual
meetings, Chicago, Illinois.
3/86 Generalized additive models; some applications, Biometric Society meet-
ings, Atlanta, Georgia.
9/85 Generalized additive models: introduction and applications. Second in-
ternational conference on generalized linear models, Lancaster, England.
8/85 Principal Curves and Surfaces, ASA annual meetings, Las Vegas, Arizona.
6/85 Non-Parametric Logistic Regression, South African Statistical Association
meeting, University of the Western Cape, Cape Town.
6/84 Principal Curves and Surfaces New Methods in Multivariate Statistics,
AMS summer conference, Brunswick, Maine (organized by P. Huber, P. Di-
aconis and P. Bickel).
4/84 Non-parametric Logistic Regression, Department of Mathematics, Impe-
rial College, London, England.
October 29, 2012 7
Teaching
9/94 - Graduate and undergraduate teaching at Stanford University.
8/92 One-semester honors course on Computer Intensive Methods at University
of Cape Town.
8/80 One-day short course at ASA meeting, Anaheim, on Generalized Additive
Models.
6-7/90 Visiting Professor, Summer Quarter, Stanford University. Taught 7-week
course on Generalized Additive Models.
4/89 Short course on Generalized Additive Models, Canadian Statistical Meet-
ings, Ottawa.
2-3/89 Invited 3-day course on Generalized Additive Models, Australian National
University, Canberra.
2/80 6/80 One-semester lecture course on Survival Analysis in the Honors program at
the University of Cape Town.
1/76 12/76 Rhodes University, Grahamstown, South Africa. Junior Lecturer in De-
partment of Mathematical Statistics. Lectured the undergraduate one year
course on Business Mathematics and Statistics.
October 29, 2012 8
Books
[1] Trevor Hastie and R. Tibshirani. Generalized Additive Models. Chapman and Hall,
1990.
[2] J. Chambers and Trevor Hastie. Statistical Models in S. Wadsworth/Brooks Cole,
Paci c Grove, California, 1991.
[3] T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning: Pre-
diction, Inference and Data Mining. Springer Verlag, New York, 2001.
[4] T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning: Pre-
diction, Inference and Data Mining. Springer Verlag, New York, second edition, 2009.
October 29, 2012 9
Refereed Journal Articles
[1] Trevor Hastie. A closer look at the deviance. American Statistician, 41, 1985.
[2] Trevor Hastie and R. Tishirani. Generalized additive models (with discussion). Sta-
tistical Science, 1, 1986.
[3] Trevor Hastie and Robert Tibshirani. Non-parametric logistic and proportional odds
regression. Applied Statistics, 36:260 276, 1987.
[4] Trevor Hastie and Tibshirani. Local likelihood estimation. Journal of the American
Statistical Association, 82, 1987.
[5] Trevor Hastie and M. Greenacre. The geometric interpretation of correspondence
analysis. Journal of the American Statistical Association, 82, 1987.
[6] Trevor Hastie and R. Tibshirani. Generalized additive models; some applications.
Journal of the American Statistical Association, 82, 1987.
[7] Trevor Hastie, J. Botha, and C. Schnitzler. Regression with an ordered categorical
response. Statistics in Medicine, 8, 1989.
[8] Trevor Hastie and W. Stuetzle. Principle curves. Journal of the American Statistical
Association, 84(406):502 516, 1989.
[9] A. Buja, Trevor Hastie, and R. Tibshirani. Linear smoothers and additive models
(with discussion). Annals of Statistics, 17:453 555, 1989.
[10] Trevor Hastie and R. Tibshirani. A method for exploring the nature of covariate e ects
in the proportional hazards model. Biometrics, 46, 1990.
[11] E. Kishon and Trevor Hastie. 3-d curve matching using splines. J. Robotic Systems,
8(6), 1991.
[12] T. Hastie, J. Fan, and E. Kishon. A model for signature veri cation. U.S. Patent
5,111,512, 1992.
[13] Trevor Hastie, W. Nelson, and W Turin. Statistical methods for online signature
veri cation. International Journal of Pattern Recognition and Arti cial Intelligence,
1992.
[14] Trevor Hastie, L. Clark, L. Psota-Kelty, D. Sinclair, and J. Rauchut. Sources of particle
contamination in an ic manufacturing environment. Aerosol Science and Technology,
16:43 50, 1992.
[15] Trevor Hastie, L. Sleeper, and R. Tibshirani. Flexible covariate e ects in the Cox
model. Breast Cancer Research and Treatment, 22:241 250, 1992. (special issue).
[16] Trevor Hastie and Robert Tibshirani. Varying coe cients models (with discussion).
J. Royal Statist. Soc. (Series B), 55:757 796, 1993.
[17] Trevor Hastie and C. Loader. Local regression: Automatic kernel carpentry (with
discussion). Statistical Science, 8:120 143, 1993.
[18] Trevor Hastie, R. Tibshirani, and A. Buja. Flexible discriminant analysis by optimal
scoring. Journal of the American Statistical Association, 89:1255 1270, 1994.
[19] T. Hastie and R. Tibshirani. Discriminant analysis by gaussian mixtures. J. Royal
Statist. Soc. (Series B), 58:155 176, 1996.
October 29, 2012 10
[20] Trevor Hastie, A. Buja, and R. Tibshirani. Penalized discriminant analysis. Annals of
Statistics, 23:73 102, 1995.
[21] Charles B. Roosen and Trevor J. Hastie. Automatic smoothing spline projection pur-
suit. Journal of Computational and Graphical Statistics, 3:235 248, 1994.
[22] T. Hastie and R. Tibshirani. Generalized additive models in medical research. Statistics
Methods in Medical Research, 4:187 196, 1995.
[23] T. Hastie and R. Tibshirani. Discriminant adaptive nearest neighbor classi cation.
IEEE Pattern Recognition and Machine Intelligence, 18:607 616, 1996.
[24] T. Hastie. Pseudosplines. Journal of the Royal Statistical Society, Series B, 58:379 396,
1995.
[25] T. Hastie and R. Tibshirani. Generalized additive models. In S. Kotz and C. Reid,
editors, Encyclopaedia of the Statistical Sciences, volume 4, pages 187 196. Elsevier,
1995.
[26] T. Hastie. Encyclopaedia of Biostatistics, chapter Neural Networks. John Wiley, 1998.
[27] T. Hastie, R. Tibshirani, and A. Buja. Flexible discriminant and mixture models. In
J. Kay and M. Titterington, editors, Statistics and Arti cial Neural Networks. Oxford
University Press, 1998.
[28] G. James and T. Hastie. Error coding and pacts. Journal of Computational and
Graphical Statistics, 1998.
[29] T. Hastie and R. Tibshirani. Classi cation by pairwise coupling. Annals of Statistics,
26(2), 1998.
[30] T. Hastie and P. Simard. Models and metrics for handwritten digit recognition. Sta-
tistical Science, 13(1), 1998.
[31] T. Hastie and R. Tibshirani. Bayesian back tting. Statistical Science (with discussion),
15(3):193 223, 2000.
[32] T. Hastie, D. Ikeda, and R. Tibshirani. On the detection of mammographc masses.
Journal of Computational and Graphical Statistics, 8(3):531 543, 1999.
[33] T. Wu, S. Schmidler, T. Hastie, and D. Brutlag. Regression analysis of multiple protein
structures. J. Computational Biology, 5(3):585 95, 1998.
[34] J. Friedman, T. Hastie, and R. Tibshirani. Additive logistic regression: a statistical
view of boosting (with discussion). Annals of Statistics, 28:337 307, 2000.
[35] G. James, T. Hastie, and C. Sugar. A principal component models for sparse functional
data. Biometrika, 87:587 602, 2000.
[36] Gareth James and Trevor Hastie. Functional linear discriminant analysis for irregularly
sampled curves. Journal of the Royal Statistical Society, Series B, 63:533 550, 2001.
[37] T. Hastie, R. Tibshirani, M. Eisen, A. Alizadeh, R. Levy, L. Staudt, D. Botstein, and
P. Brown. Gene shaving as a method for identifying distinct sets of genes with
similar expression patterns. Genome Biology, 1(2):1 21, 2000.
[38] T. Hastie, R. Tibshirani, D. Botstein, and P. Brown. Supervised harvesting of expres-
sion trees. Genome Biology, 2(1):1 12, 2001.
October 29, 2012 11
[39] R. Tibshirani, G. Walther, and T. Hastie. Estimating the number of clusters in a
dataset via the gap statistic. Journal of the Royal Statistical Society, B, 63:411 423,
2001.
[40] Robert Tibshirani, Trevor Hastie, Balasubramaniam Narasimhan, Michael Eisen,
Gavin Sherlock, Pat Brown, and David Botstein. Exploratory screening of genes and
clusters from microarray experiments. Statistica Sinica, 12:47 59, 2002.
[41] Olga Troyanskaya, Michael Cantor, Gavin Sherlock, Pat Brown, Trevor Hastie, Robert
Tibshirani, David Botstein, and Russ B. Altman. Missing value estimation methods
for dna microarrays. Bioinformatics, 17(6):520 525, 2001.
[42] Antoine Guisan, Thomas Edwards, and Trevor Hastie. Generalized linear and gener-
alized additive models in studies of species distributions: setting the scene. Ecological
Modelling, 157:89 100, 2002.
[43] Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, and Gilbert Chu.
Diagnosis of multiple cancer types by shrunken centroid of gene expression. Proceedings
of the National Academy of Sciences, 99, 2002.
[44] Eva. Cantoni and Trevor Hastie. Degrees-of-freedom tests for smoothing splines.
Biometrika, 89(2):251 263, 2002.
[45] T. Yee and T. Hastie. Reduced rank multinomial models. Statistical Modelling, 3:15
41, 2003.
[46] Trevor Hastie, Rob Tibshirani, and Jerome Friedman. Note on Comparison of model
selection for regression by Vladimir Cherkassky and Yunqian Ma. Neural Comput,
15(7):1477 1480, Jul 2003. Comment.
[47] Mu Zhu and Trevor Hastie. Feature extraction for non-parametric discriminant anal-
ysis. Journal of Computational and Graphical Statistics, 12(1), 2003.
[48] Brad Efron, Trevor Hastie, Iain Johnstone, and Robert Tibshirani. Least angle regres-
sion. Annals of Statistics, 32(2):407 499, 2004. (with discussion).
[49] Francesca Dominici, Aidan McDermott, and Trevor Hastie. Semi-parametric regression
with applications in time series studies for air pollution and mortality. Journal of the
American Statistical Associaition, 99(468):938 948, 2005.
[50] Ji Zhu and Trevor Hastie. Classi cation of expression arrays by penalized logistic
regression. Biostatistics, 5(3):427 443, 2004.
[51] Trevor Hastie and Rob Tibshirani. E cient quadratic regularization for expression
arrays. Biostatistics, 5(3):329 340, 2004.
[52] Saharon Rosset, Ji Zhu, and Trevor Hastie. Boosting as a regularized path to a maxi-
mum margin classi er. JMLR, 5:941 973, August 2004.
[53] Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, Scott Soltys, Gongyi
Shi, Albert Koong, and Quynh-Thu Le. Sample classi cation from protein mass spec-
trometry, by peak probability contrasts . Bioinformatics, 20(17):3034 44, 2004.
[54] Trevor Hastie, Saharon Rosset, Robert Tibshirani, and Ji Zhu. The entire regular-
ization path for the support vector machine. Journal of Machine Learning Research,
(5):1391 1415, 2004.
[55] Mu Zhu, Trevor Hastie, and Guenther Walther. On model formulation in constrained
ordination analysis. Ecological Modelling, 187(4):524 536, 2005.
October 29, 2012 12
[56] Hui Zou and Trevor Hastie. Regression shrinkage and selection via the elastic net.
JRSS B, 67(2):301 320, 2005.
[57] Hui Zou, Trevor Hastie, and Rob Tibshirani. Sparse principal component analysis.
Journal of Computational and Graphical Statistics, 15(2):265 286, 2006.
[58] Eric Bair, Trevor Hastie, Debashis Paul, and Robert Tibshirani. Prediction by super-
vised principal components. Journal of the American Statistical Association, 101:119
137, 2006.
[59] Dirk Ormoneit, Michael Black, Trevor Hastie, and Hedvig Kjellstr m. Represent-
o
ing cyclic human motion using functional analysis. Image and Vision Computing,
23(14):1264 1276, 2005.
[60] John Leathwick, D. Rowe, J. Richardson, Jane Elith, and Trevor Hastie. Using multi-
variate adaptive regression splines to predict the distributions of new zealand s fresh-
water diadromous sh. Freshwater Biology, 50:2034 2051, 2005.
[61] Ji Zhu and Trevor Hastie. Kernel logistic regression and the import-vector machine.
Journal of Computational and Graphical Statistics, 14(1):185 205, 2005.
[62] J. Leathwick, J. Elith, M. Francis, T. Hastie, and P. Taylor. Variation in demersal
sh species richness in the oceans surrounding new zealand: an analysis using boosted
regression trees. Marine Ecology Progress Series, 2006.
[63] Mee Young Park, Trevor Hastie, and Robert Tibshirani. Averaged gene expressions
for regression. Biostatistics, 8:212 217, 2007.
[64] Yaqian Guo, Trevor Hastie, and Robert Tibshirani. Regularized linear discriminant
analysis and its application in microarrays. Biostatistics, 8:86 100, 2007.
[65] John Leathwick, Jane Elith, and Trevor Hastie. Comparative performance of gen-
eralized additive models and multivariate adaptive regression splines for statistical
modelling of species distributions. Ecological Modelling, 199:188 196, 2006.
[66] Robert Tibshirani and Trevor Hastie. Outlier sums for di erential gene expression
analysis. Biostatistics, 8(1):2 8, Jan 2007.
[67] Mee-Young Park and Trevor Hastie. An l1 regularization path for generalized linear
models. J. Royal Statistical Society B, 69(4):659 677, 2007.
[68] Mee-Young Park and Trevor Hastie. Penalized logistic regression for detecting gene
interactions. Biostatistics, 9:30 50, 2008. originally published online on April 11, 2007.
[69] Hui Zou, Trevor Hastie, and Robert Tibshirani. On the degrees of freedom of the lasso.
Annals of Statistics, 35(5):2173 2192, 2007.
[70] Jerome Friedman, Trevor Hastie, Holger Hoe ing, and Robert Tibshirani. Pathwise
coordinate optimization. Annals of Applied Statistics, 2(1):302 332, 2007.
[71] Trevor Hastie, Jonathan Taylor, Robert Tibshirani, and Guenther Walther. Forward
stagewise regression and the monotone lasso. Electron. J. Statist., 1:1 29, 2007.
[72] Ping Li, Trevor Hastie, and Ken Church. Nonlinear estimators and tail bounds for di-
mension reduction in l1 using cauchy random projections. Journal of Machine Learning
Research, 8:2497 2532, 2007.
[73] Jerome Friedman, Trevor Hastie, and Robert Tibshirani. Sparse inverse covariance
estimation with the graphical lasso. Biostatistics, 9:432 441, 2008.
October 29, 2012 13
[74] Robert Tibshirani and Trevor Hastie. Margin trees for high-dimensional classi cation.
Journal of Machine Learning Research, 8:637 652, 2007.
[75] Gill Ward, Trevor Hastie, Simon Barry, Jane Elith, and John Leathwick. Presence-only
data and the em algorithm. Biometrics, 65(2):554 563, 2009.
[76] Debashis Paul, Eric Bair, Trevor Hastie, and Robert Tibshirani. Pre-conditioning
for feature selection and regression in high-dimensional problems. Annals of Statistics,
36(4):1595 1618, 2008.
[77] Trevor Hastie, Jonathan Taylor, Robert Tibshirani, and Guenther Walther. Forward
stagewise regression and the monotone lasso. Electronic Journal of Statistics, 1:1 29,
2007.
[78] John Leathwick, Jane Elith, W. Chadderton, D. Rowe, and Trevor Hastie. Dispersal,
disturbance and the contrasting biogeographies of new zealand s diadromous and non-
diadromous sh species. Journal of Biogeography, pages 1 17, 2008.
[79] Jane Elith, John Leathwick, and Trevor Hastie. A working guide to boosted regression
trees. Journal of Animal Ecology, 77:802 813, 2008.
[80] Hui Zou, Ji Zhu, and Trevor Hastie. New multicategory boosting algorithms based
on multicategory sher-consistent losses. Annals of Applied Statistics, 2(4):1290 1306,
2008.
[81] Daniela Witten, Rob Tibshirani, and Trevor Hastie. A penalized matrix decomposition
with applications to sparse canonical correlation analysis and principal components.
Biostatistics, 10:515 534, 2009.
[82] Jerome Friedman, Trevor Hastie, and Robert Tibshirani. Regularization paths for gen-
eralized linear models via coordinate descent. Journal of Statistical Software, 33(1):1
22, 2010.
[83] T. Wu, Y. Chen, T. Hastie, E. Sobel, and K. Lange. Genome-wide association analysis
by penalized logistic regression. Bioinformatics, 25(6):714 721, March 2009.
[84] Jane Elith, Steven Phillips, Trevor Hastie, Miroslav Dudik, Yung En Chee, and Colin
Yates. A statistical explanation of maxent for ecologists. Diversity and Distribution,
November 2010.
[85] Rahul Mazumder, Trevor Hastie, and Rob Tibshirani. Spectral regularization algo-
rithms for learning large incomplete matrices. Journal of Machine Learning Research,
11:2287 2322, 2010.
[86] Michael Greenacre and Trevor Hastie. Dynamic visualization of statistical learning
algorithms in the context of high-dimensional textual data. Journal of Web Semantics,
8(2):163 168, 2010.
[87] Noah Simon, Jerome Friedman, Trevor Hastie, and Rob Tibshirani. Regularization
paths for cox s proportional hazards model via coordinate descent. Journal of Statis-
tical Software, 39(5):1 13, 2011.
[88] Rahul Mazumder, Jerome Friedman, and Trevor Hastie. Sparsenet: Coordinate de-
scent with non-convex penalties. Journal of the American Statistical Association,
106(495):1125 1138, 2011.
[89] Gen Nowak, Trevor Hastie, Jonathan Pollack, and Robert Tibshirani. A fused-lasso
latent feature model for analyzing multi-sample acgh data. Biostatistics, 12(4):776
791, 2011.
October 29, 2012 14
[90] Line Clemmensen, Trevor Hastie, Daniela Witten, and Bjarne Ersboll. Sparse discrim-
inant analysis. Technometrics, 53(4):406 413, 2011.
[91] Rob Tibshirani, Jacob Bien, Jerome Friedman, Trevor Hastie, Noah Simon, Jonathan
Taylor, and Ryan Tibshirani. Strong rules for discarding predictors in lasso-type prob-
lems. J. Royal Statistical Society B, 74, 2012.
[92] Rahul Mazumder and Trevor Hastie. Exact covariance thresholding into connected
components for large-scale graphical models. Journal of Machine Learning Research,
13:723 736, March 2012.
[93] Rahul Mazumder and Trevor Hastie. The graphical lasso: New insights and alterna-
tives. Electronic Journal of Statistics, 2012. (in press).
October 29, 2012 15
Refereed Medical Journal Articles as Statistical Collaborator
[1] B. Arndt, P. Botha, and T. Hastie. Survey of antiobiotic resistance in gram-negative
bacteria using the cross product ratio. Zbl. Bakt. Hyg., I. Abt. Orig A, 243:483 489,
1979.
[2] L M Irwig, R S du Toit, G K Sluis-Cremer, A Solomon, R G Thomas, P P Hamel,
I Webster, and T Hastie. Risk of asbestosis in crocidolite and amosite mines in South
Africa. Ann N Y Acad Sci, 330:35 52, 1979. Comparative Study.
[3] Trevor Hastie, P. Commerford, and W. Beck. Closed mitral valvotomy: Actuarial
analysis of results in 654 patients over 12 years and analysis of preoperative predictors
of long-term survival. Annals of Thoracic Surgery, 33, 1982.
[4] Allan Herman and Trevor Hastie. An analysis of gestational age, neonatal size and
neonatal death using nonparametric logistic regression. Journal of Clinical Epidemi-
ology, 43, 1990.
[5] P.A. Heidenreich, K.M. McDonald, T. Hastie, B. Fadel, V. Hagan, B.K. Lee, and
M.A. Hlatky. Meta-analysis of trials comparing beta-blockers, calcium antagonists,
and nitrates for stable angina. JAMA, 281(20):1927 36, 1999.
[6] M.K. Gould, A.D. Dembitzer, T.J. Doyle, R.L. Hastie, and A.M. Garber. Low molec-
ular weight heparins compared with unfractionated heparin for the treatment of acute
deep vein thrombosis: A meta-analysis of randomized controlled trials. Annals of
Internal Medicine, 130:800 809, 1999.
[7] Laura Bachrach, Trevor Hastie, May-Choo Wang, Balasubramaniam Narasimhan, and
Robert Marcus. Bone mineral acquisition in healthy asian, hispanic, black and cau-
casian youth. a longitudinal study. J. Clin. Endocrinol. Metab., 84:4702 4712, 1999.
[8] P A Heidenreich, A Go, K A Melsop, T Alloggiamento, K M McDonald, V Hagan,
T Hastie, and M A Hlatky. Prediction of risk for patients with unstable angina. Evid
Rep Technol Assess (Summ), (31):1 3, Aug 2000.
[9] S. Eliaz, C. Blazy, L. Freund, T. Hastie, and A. Riess. Brain anaotomy, gender and ig
in children and adolescents with fragile-x syndrome. Brain, 124:1610 1618, 2001.
[10] Therese Sorlie, C. Perou, Robert Tibshirani, Turid Aas, Stephanie Geisler, Hilde
Johnsen, Trevor Hastie, Michael B. Eisen, Matt van de Rijn, Stefanie S. Je rey, Thor
Thorsen, Hanne Quist, John C. Matese, Patrick O. Brown, David Botstein, Per Eystein
Lonninngg, and Anne-Lise Borresen-Dale. Gene expression patterns of breast carcino-
mas distinguish tumor subclasses with clinical implications. Proceedings of the National
Academy of Sciences, 98:108**-*****, 2001.
[11] Fleischmann D., Hastie TJ., Dannegger FC., Paik DS., Tillich M., Zarins CK., and
Rubin GD. Quantitative determination of age-related geometric changes in the normal
abdominal aorta. J. Vascular Surgery, 33(1):97 105, Jan 2001.
[12] S. Chaparro, Gao S., Perlroth M., Montoya J., Hastie T., Miller JL., Oyer PE., and
Schroeder J. Posttransplantation lymphoproliferative disease in heart and heart-lung
transplant recipients: thirty years experience at our hospital. J Heart Lung Transplant,
20(2):258, Feb 2001.
[13] Sandip Biswal, Trevor Hastie, Thomas P Andriacchi, Gabrielle A Bergman, Michael F
Dillingham, and Philipp Lang. Risk factors for progressive cartilage loss in the knee:
a longitudinal magnetic resonance imaging study in forty-three patients. Arthritis
Rheum, 46(11):2884 2892, Nov 2002.
October 29, 2012 16
[14] Hongjuan Zhao, Trevor Hastie, Dr Michael L Whit eld, Prof Anne-Lise Borresen-
Dale, and Dr. Stefanie S Je rey. Optimization and evaluation of t7 based rna linear
ampli cation protocols for cdna microarray analysis. BMC Genomics, 3(31), October
2002.
[15] Therese Sorlie, Robert Tibshirani, Joel Parker, Trevor Hastie, J S Marron, Andrew
Nobel, Shibing Deng, Hilde Johnsen, Robert Pesich, Stephanie Geisler, Janos Demeter,
Charles M Perou, Per E Lonning, Patrick O Brown, Anne-Lise Borresen-Dale, and
David Botstein. Repeated observation of breast tumor subtypes in independent gene
expression data sets. Proc Natl Acad Sci U S A, 100(14):8418 8423, Jul 2003.
[16] Tomasz A Timek, David T Lai, Frederick Tibayan, David Liang, George T Daughters,
Paul Dagum, Mary K Zasio, Sidney Lo, Trevor Hastie, Neil B Jr Ingels, and D Craig
Miller. Ischemia in three left ventricular regions: Insights into the pathogenesis of
acute ischemic mitral regurgitation. J Thorac Cardiovasc Surg, 125(3):559 569, Mar
2003.
[17] Marci E Schaner, Douglas T Ross, Giuseppe Ciaravino, Therese Sorlie, Olga Troy-
anskaya, Maximilian Diehn, Yan C Wang, George E Duran, Thomas L Sikic, Sandra
Caldeira, Hanne Skomedal, I-Ping Tu, Tina Hernandez-Boussard, Steven W Johnson,
Peter J O Dwyer, Michael J Fero, Gunnar B Kristensen, Anne-Lise Borresen-Dale,
Trevor Hastie, Robert Tibshirani, Matt van de Rijn, Nelson N Teng, Teri A Longacre,
David Botstein, Patrick O Brown, and Branimir I Sikic. Gene expression patterns in
ovarian carcinomas. Mol Biol Cell, 14(11):4376 4386, Nov 2003. Comparative Study.
[18] David Hessl, Bronwyn Glaser, Jennifer Dyer-Friedman, Christine Blasey, Trevor
Hastie, Megan Gunnar, and Allan L. Reiss. Cortisol and behavior in fragile x syn-
drome. Psychoneuroendocrinology, 27(7):855 872, 2002.
[19] Shao-Zhou Gao, Sandra V Chaparro, Mark Perlroth, Jose G Montoya, Joan L Miller,
Sue DiMiceli, Trevor Hastie, Phillip E Oyer, and John Schroeder. Post-transplantation
lymphoproliferative disease in heart and heart-lung transplant recipients: 30-year ex-
perience at Stanford University. J Heart Lung Transplant, 22(5):505 514, May 2003.
[20] Tomasz A Timek, Sten L Nielsen, David T Lai, Frederick Tibayan, David Liang,
George T Daughters, Philip Beineke, Trevor Hastie, Neil B Jr Ingels, and D Craig
Miller. Mitral annular size predicts Al eri stitch tension in mitral edge-to-edge repair.
J Heart Valve Dis, 13(2):165 73, 2004.
[21] Pantaleo Romanelli, Gary Heit, Bruce C Hill, Alli Kraus, Trevor Hastie, and Helen M
Bronte-Stewart. Microelectrode recording revealing a somatotopic body map in the
subthalamic nucleus in humans with Parkinson disease. J Neurosurg, 100(4):611 8,
2004.
[22] Olaug Kristin Rodningen, Jens Overgaard, Jan Alsner, Trevor Hastie, and Anne-Lise
Borresen-Dale. Microarray analysis of the transcriptional response to single or multi-
ple doses of ionizing radiation in human subcutaneous broblasts. Radiother Oncol,
77(3):231 40, 2005.
[23] Ana Lisa Taylor Tavares, Gregory S X E Je eris, Mandy Koop, Bruce C Hill, Trevor
Hastie, Gary Heit, and Helen M Bronte-Stewart. Quantitative measurements of alter-
nating nger tapping in Parkinson s disease correlate with UPDRS motor disability
and reveal the improvement in ne motor control from medication and deep brain
stimulation. Mov Disord, 20(10):1286 98, 2005.
[24] Lauren B Gerson, Nighat Ullah, Trevor Hastie, George Triada lopoulos, and Mary
Goldstein. Patient-derived health state utilities for gastroesophageal re ux disease.
Am J Gastroenterol, 100(3):524 33, 2005.
October 29, 2012 17
[25] Chi JT, Wang Z, Nuyten DS, Rodriguez EH, Schaner ME, Salim A, Wang Y, Kris-
tensen GB, Helland A, Borresen-Dale AL, Giaccia A, Longaker MT, Hastie T, Yang
GP, Vijver MJ, and Brown PO. Gene Expression Programs in Response to Hypoxia:
Cell Type Speci city and Prognostic Signi cance in Human Cancers. PLoS Med,
3(3):e47, 2006.
[26] Howard Y Chang, Dimitry S A Nuyten, Julie B Sneddon, Trevor Hastie, Robert Tibshi-
rani, Therese Sorlie, Hongyue Dai, Yudong D He, Laura J van t Veer, Harry Bartelink,
Matt van de Rijn, Patrick O Brown, and Marc J van de Vijver. Robustness, scalabil-
ity, and integration of a wound-response gene expression signature in predicting breast
cancer survival. Proc Natl Acad Sci U S A, 102(10):3738 43, 2005.
[27] Lauren B Gerson, Nighat Ullah, Trevor Hastie, and Mary K Goldstein. Does cancer risk
a ect health-related quality of life in patients with Barrett s esophagus? Gastrointest
Endosc, 65(1):16 25, Jan 2007.
[28] Jen-Tsan Chi, Edwin H Rodriguez, Zhen Wang, Dimitry S A Nuyten, Sayan Mukher-
jee, Matt van de Rijn, Marc J van de Vijver, Trevor Hastie, and Patrick O Brown.
Gene expression programs of human smooth muscle cells: tissue-speci c di erentiation
and prognostic signi cance in breast cancers. PLoS Genet, 3(9):1770 84, 2007.
[29] Martin Buess, Dimitry Sa Nuyten, Trevor Hastie, Torsten Nielsen, Robert Pesich,
and Patrick O Brown. Characterization of heterotypic interaction e ects in vitro to
deconvolute global gene expression pro les in cancer. Genome Biol, 8(9):R191, 2007.
[30] A. Tutt, A. Wang, C. Rowland, C. Gillett, K. Lau, K. Chew, H. Dai, S. Kwok,
K. Ryder, H. Shu, R. Springall, P. Cane, B. McCallie, L. Kam-Morgan, S. Anderson,
H. Buerger, J. Gray, J. Bennington, L. Esserman, T. Hastie, S. Broder, J. Sninsky,
B. Brandt, and F. Waldman. Risk estimation of distant metastasis in node-negative,
estrogen receptor-positive breast cancer patients using an RT-PCR based prognostic
expression signature. BMC Cancer, 8:339, 2008.
[31] D. S. Nuyten, T. Hastie, J. T. Chi, H. Y. Chang, and M. J. van de Vijver. Combin-
ing biological gene expression signatures in predicting outcome in breast cancer: An
alternative to supervised classi cation. Eur. J. Cancer, 44:2319 2329, Oct 2008.
[32] K. C. Jensen, D. A. Turbin, S. Leung, M. A. Miller, K. Johnson, B. Norris, T. Hastie,
S. McKinney, T. O. Nielsen, D. G. Huntsman, C. B. Gilks, and R. B. West. New
cutpoints to identify increased HER2 copy number: analysis of a large, population-
based cohort with long-term follow-up. Breast Cancer Res. Treat., 112:453 459, Dec
2008.
[33] O. K. Rdningen, A. L. Brresen-Dale, J. Alsner, T. Hastie, and J. Overgaard. Radiation-
induced gene expression in human subcutaneous broblasts is predictive of radiation-
induced brosis. Radiother Oncol, 86:314 320, Mar 2008.
[34] A. H. Beck, C. H. Lee, D. M. Witten, B. C. Gleason, B. Edris, I. Espinosa, S. Zhu,
R. Li, K. D. Montgomery, R. J. Marinelli, R. Tibshirani, T. Hastie, D. M. Jablons,
B. P. Rubin, C. D. Fletcher, R. B. West, and M. van de Rijn. Discovery of molecular
subtypes in leiomyosarcoma through integrative molecular pro ling. Oncogene, Nov
2009.
[35] S. Suthram, J. T. Dudley, A. P. Chiang, R. Chen, T. J. Hastie, and A. J. Butte.
Network-based elucidation of human disease similarities reveals common functional
modules enriched for pluripotent drug targets. PLoS Comput. Biol., 6:e1000662, Feb
2010.
October 29, 2012 18
[36] S. S. Shen-Orr, R. Tibshirani, P. Khatri, D. L. Bodian, F. Staedtler, N. M. Perry,
T. Hastie, M. M. Sarwal, M. M. Davis, and A. J. Butte. Cell type-speci c gene
expression di erences in complex tissues. Nat. Methods, 7:287 289, Apr 2010.
[37] M. Mell, J. J. White, B. B. Hill, T. Hastie, and R. L. Dalman. No increased mortality
with early aortic aneurysm disease. J. Vasc. Surg., 56(5):1246 1251, Nov 2012.
[38] D. S. Cross, C. A. McCarty, E. Hytopoulos, M. Beggs, N. Nolan, D. S. Harrington,
T. Hastie, R. Tibshirani, R. P. Tracy, B. M. Psaty, R. McClelland, P. S. Tsao, and
T. Quertermous. Improved coronary risk assessment among intermediate risk patients
using a clinical and biomarker based algorithm developed and validated in two popu-
lation cohorts. Curr Med Res Opin, Oct 2012.
October 29, 2012 19
Published Discussions
[1] Trevor Hastie. Comment on Graphical Methods for Assessing Logistic Regression
Models by J. Landwehr, D. Pregibon and A. Shoemaker. Journal of the American
Statistical Association, 79, 1984. comment.
[2] T Hastie and R. Tibshirani. Comment on Projection Pursuit by P. Huber. Annals
of Statistics, 13:435 475, 1985.
[3] Trevor Hastie and R. Tibshirani. Discussion of What is Projection Pursuit? by M.
Jones and R. Sibson. Journal of the Royal Statistical Society Series A, 150, 1987.
[4] Trevor Hastie and R. Tibshirani. Discussion of Monotone Splines in Action by J.
Ramsay. Statistical Science, 4, 1988.
[5] T. Hastie. Discussion of Flexible Parsimonious Smoothing and Additive Modelling
by Friedman, J.H. and Silverman, B.W. Technometrics, 31:3 39, 1989.
[6] A. Buja, D. Du y, T. Hastie, and R. Tibshirani. Discussion of Multivariate Adaptive
Regression Splines by J. Friedman. Annals of Statistics, 19, 1991.
[7] Trevor Hastie and E. Kishon. Discussion of Procrustes Methods in the Statistical
Analysis of Shape by Colin Goodall. Journal of the Royal Statistical Society, series
B, 53, 1991.
[8] Trevor Hastie and R. Tibshirani. Discussion of The Method for Estimating Multi-
variate Functions from Noisy Data by Leo Breiman. Technometrics, 33, 1991.
[9] T. Hastie and C. Mallows. Comment on A Statistical View of Some Chemometric
Regression Tools by J. Friedman and I. Frank. Technometrics, 35(2):140 143, 1993.
[10] Trevor Hastie and R. Tishirani. Discussion of Regression Using Fractional Polynomi-
als by J. Royston and D. Altman. Journal of the Royal Statistical Society Series B,
57:355, 1995.
[11] Trevor Hastie. Discussion of Polynomial Splines and Their Tensor Products in Func-
tion Estimation by C. Stone. Annals of Statistics, 1994.
[12] Trevor Hastie and R. Tibshirani. Discussion of Neural Networks and Statistics by
B. Ripley. Journal of the Royal Statistical Society Series B, 56:409 456, 1994.
[13] D. Donoho, I. Johnstone, G. Kerkyachairan, and D. Picard. Wavelet shrinkage; asymp-
topia? (with discussion). J. Royal. Statist. Soc., 57:201 337, 1995.
[14] T. Hastie and R. Tibshirani. Discussion of Polynomial splines and their Tensor Prod-
ucts in Extended Linear Modelling by Stone, Hansen, Kooperberg and Truong. Annals
of Statistics, 25(4):1371 1470, 1997.
[15] T. Hastie and R. Tibshirani. Discussion of Prediction Multivariate Responses in
Multiple Linear Regression by Leo Breiman and Jerome Friedman. Journal of the
Royal Statistical Society, series C, 59:46 47, 1997.
[16] N. Crellin, T. Hastie, and I. Johnstone. Discussion of Non-Linear Fourier Time Series
Analysis for Human Brain Mapping by Functional Magnetic Resonance Imaging by
N. Lange and S. Zeger. Applied Statistics, 46(1):22 23, 1997.
[17] Mu Zhu and Trevor Hastie. Discussion of Dimension Reduction and Visualization in
Discriminant Analysis by D. Cook and X. Yin. Australian and New Zealand Journal
of Statistics, 43(2):179 185, 2001.
October 29, 2012 20
[18] Jerome Friedman, Trevor Hastie, Saharon Rosset, Rob Tibshirani, and Ji Zhu. Discus-
sion of 3 Boosting papers by (1) Wenxin Jiang, (2) Gabor Lugosi and Nicolas Vayatis,
and (3) Tong Zhang. Annals of Statistics, 32(1):102 107, 2004.
[19] Trevor Hastie and Ji Zhu. Discussion of Support Vector Machines with applications
by Javier Moguerza and Alberto Munoz. Statistical Science, 21(3):352 357, 2006.
[20] Trevor Hastie. Discussion of Boosting Algorithms: regularization, Prediction and
Model Fitting by Peter B hlmann and Torsten Hothorn. Statistical Science,
u
22(4):513 515, 2007.
[21] Bradley Efron, Trevor Hastie, and Robert Tibshirani. Discussion of The Dantzig
Selector by Emmanuel Candes and Terrence Tao. Annals of Statistics, 35:2313 2351,
2007.
[22] Daniela Witten, Trevor Hastie, and Robert Tibshirani. Discussion of on consistency
and sparsity of principal components in high dimensions by iain johnstone and arthur
lu. Journal of the American Statistical Association, 104(486):698 699, 2009.
[23] Jerome Friedman, Trevor Hastie, and Robert Tibshirani. Discussion of Evidence
Contrary to the Statistical View of Boosting by David Mease and Aaron Wyner.
Journal of Machine Learning Research, 9:175 180, 2008.
October 29, 2012 21
Published Conference Proceedings
[1] Trevor Hastie. Generalized additive models: a gaim analyst s toolbox. In Proceedings
of the Statistical Computing Section, American Statistical Association, 1986.
[2] Trevor Hastie and F. Little. Principal pro les. In Proceedings of 1987 Interface Meet-
ings, Philadelphia, 1987.
[3] Trevor Hastie and D. Pregibon. A new algorithm for matched case control studies
with applications to additive models. In Proceedings COMPSTAT 88, Copenhagen,
1988.
[4] Trevor Hastie, J. Chambers, and D Pregibon. Statistical models in s. In COMPSTAT
90, Dubrovnik, Yugoslavia, Heidelberg, 1990. Physica Verlag.
[5] Trevor Hastie, E. Kishon, M. Clark, and J Fan. A model for signature veri cation. In
IEEE Proceedings: Systems, Man and Cybernetics, 1991. Charlottesville, Virginia.
[6] Trevor Hastie, P. Simard, and E. S ckinger. Learning prototype models for tangent
a
distance. In D. S. Touretzky G. Tesauro and T. K. Leen, editors, Advances in Neural
Information Processing Systems 7, Cambridge, MA, 1995. MIT Press.
[7] G. James and T. Hastie. Generalizations of the bias/variance decomposition for pre-
diction error. Technical report, Stanford University Statistics Department, 1996.
[8] T. Wu, S. Schmidler, T. Hastie, and D. Brutlag. Modelling and superposition of
multiple protein structures using a ne transformations: analysis of the globins. In
Paci c Symposium on Biocomputing 98, pages 509 520. World Scienti c, 1998.
[9] P. Heidenreich, K. McDonald, T. Hastie, F. Bahaa, V. Hagan, B. Lee, and M Hlatky.
An evaluation of beta-blockers, calcium antagonists, nitrates, and alternative therapies
for stable angina. Evidence report prepared for Agency for Healthcare Research and
Quality AHRQ Publication No. 00-E003, November 1999.
[10] D. Ormoneit and T. Hastie. Optimal kernel shapes for local linear regression. In
S. A. Solla, T. K. Leen, and K-R. M ller, editors, Advances in Neural Information
u
Processing Systems, volume 12, 2000.
[11] Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black, and Trevor Hastie. Learning
and tracking cyclic human, 2001.
[12] Ji Zhu and Trevor Hastie. Kernel logisitic regression and the import vector machine. In
Advances in Neural Information Processing Systems 14, Cambridge, MA, 2002. MIT
Press.
[13] Trevor Hastie and Robert Tibshirani. Independent component analysis through prod-
uct density estimation. In Advances in Neural Information Processing System, vol-
ume 14. MIT Press, 2002.
[14] Saharon Rosset, Ji Zhu, and Trevor Hastie. Margin maximizing loss functions. In
Neural Information Processing Systems, volume 16, 2003.
[15] Ji Zhu, Saharon Rosset, Trevor Hastie, and Rob Tibshirani. 1-norm support vector
machines. In Advances in Neural Information Processing Systems, 2004.
[16] Philip Beineke, Trevor Hastie, and Shivakumar Vaithyanathan. The sentimental factor:
Improving review classi cation via human-provided information. In Proceedings, ACL
2004, Barcelona, 2004.
October 29, 2012 22
[17] Saharon Rosset, Hui Zou, Ji Zhu, and Trevor Hastie. A method for inferring label
sampling mechanisms in semi-supervised learning. In Advances in Neural Information
Processing Systems, 2005.
[18] Trevor Hastie, Saharon Rosset, Rob Tibshirani, and Ji Zhu. The entire regularization
path for the support vector machine. In Advances in Neural Information Processing
Systems, 2005.
[19] Ping Li, Trevor Hastie, and Kenneth Church. Improving random projections using
marginal information. In Proceedings of COLT 2006, 2006.
[20] Ping Li, Kenneth Church, and Trevor Hastie. Conditional random sampling: a sketch-
based sampling technique for sparse data. In NIPS, 2006.
[21] Ping Li, Trevor Hastie, and Ken Church. Very sparse random projections. In KDD,
2006. (best student paper award).
[22] Ping Li, Ken Church, and Trevor Hastie. One sketch ts all: theory and application
of conditional random sampling. In Proceedings NIPS08, 2008.
October 29, 2012 23
Unpublished Technic
Contact this candidate