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Technical Reports

Technical reports are available from a variety of series, spanning many different reporting groups and funding agencies. To date, all known reports that are present in the Archive have been scanned and appear on this site!

If you find an error on these pages, or have information regarding any of our missing reports, please send a message to the Technical Reports Archive at stat-techreports@lists.stanford.edu.

You can search using title keywords, author, and/or year of issue, or browse the reports by series.

Format: 2016
Report # (Alt Rpt #) Date Author Title Note
2016-03
May 2016
M. Gavish
D.L. Donoho
Optimal Shrinkage of Singular Values new revision of 2014-08 (with same title)
2016-02
Mar 2016
H.Y. He
K. Basu
Q. Zhao
A.B. Owen
Permutation p-value Approximation via Generalized Stolarsky Invariance
2016-01
Feb 2016
R.F. Barber
E.J. Candès
A Knockoff Filter for High-Dimensional Selective Inference
2015-22
Nov 2015
A.B. Owen Statistically Efficient Thinning of a Markov Chain Sampler
2015-21
Nov 2015
M.R. Lee
A.B. Owen
Single Nugget Kriging
2015-20
Nov 2015
W. Su
M. Bogdan
E. Candès
False Discoveries Occur Early on the Lasso Path
2015-19
Sep 2015
J. Gorham
L. Mackey
Measuring Sample Quality with Stein's Method
2015-18
Sep 2015
A. Javanmard
A. Montanari
De-biasing the Lasso: Optimal Sample Size for Gaussian Designs
2015-17
Aug 2015
Z. Fan
L. Mackey
An Empirical Bayesian Analysis of Simultaneous Changepoints in Multiple Data Sequences
2015-16
Aug 2015
B. Rajaratnam
J. Romano
M. Tsiang
N.S. Diffenbaugh
Debunking the Climate Hiatus
2015-15
Aug 2015
C.J. DiCiccio
J.P. Romano
Robust Permutation Tests for Correlation and Regression Coefficients
2015-14
Jul 2015
Z. Fan
A. Montanari
The Spectral Norm of Random Inner-Product Kernel Matrices
2015-13
May 2015
A.O. Hero
B. Rajaratnam
Foundational Principles for Large Scale Inference: Illustrations Through Correlation Mining
2015-12
May 2015
Y. Chen
E. Candès
Solving Random Quadratic Systems of Equations is Nearly as Easy as Solving Linear Systems
2015-11
May 2015
L. Janson
R. Foygel Barber
E. Candès
EigenPrism: Inference for High-Dimensional Signal-to-Noise Ratios

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