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Annals of Applied Statistics |
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Volume 1, Number 1 (2007) |
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Volume 1, Number 2 (2007) |
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Volume 2, Number 1 (2008) |
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Volume 2, Number 2 (2008) |
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Volume 2, Number 3 (2008) |
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Volume 2, Number 4 (2008) |
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Volume 3, Number 1 (2009) |
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Volume 3, Number 2 (2009) |
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Volume 3, Number 3 (2009) |
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Volume 3, Number 4 (2009) |
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Volume 4, Number 1 (2010) |
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Volume 4, Number 2 (2010) |
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Volume 4, Number 3 (2010) |
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Volume 4, Number 4 (2010) |
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Volume 5, Number 1 (2011) |
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Volume 5, Number 2a (2011) |
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Volume 5, Number 2b (2011) |
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Future Issues |
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Instructions for Referees |
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Letters to Editor |
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The mortality of the Italian population: Smoothing techniques on the Lee Carter Model
Valeria D'Amato, Gabriella Piscopo, and Maria Russolillo
Volume 5 Issue 2A, pg. 705-724
Supplements
| Title |
Italy, Exposure to risk |
| Description |
Italian population exposed to risk of death. The data
are downloaded from the Human Mortality database and are indexed by
calendar year during the period 1950--2005. They are divided by sex and
by single year of age for ages from 0 to~100.
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| DOI |
10.1214/10-AOAS394SUPPA |
| Link |
http://lib.stat.cmu.edu/aoas/394/supplementA.txt |
| Title |
Italy, Death rates |
| Description |
Italian population death rates. The data are downloaded
from the Human Mortality database and are indexed by calendar year
during the period 1950--2005. They are divided by sex and by single year
of age for ages from 0 to 100. For each gender and for each calendar
year, the death rates are given by the ratio between the "Number of
deaths" and the "Exposure to risk."
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| DOI |
10.1214/10-AOAS394SUPPB |
| Link |
http://lib.stat.cmu.edu/aoas/394/supplementB.txt |
A Sticky HDP-HMM with Application to Speaker Diarization
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, and Alan S. Willsky
Volume 5 Issue 2A, pg. 1020-1056
Supplements
| Title |
Notational conventions, Chinese restaurant franchises and derivations of Gibbs samplers |
| Description |
We present detailed derivations of the
conditional distributions used for both the direct assignment and blocked
Gibbs samplers, as well as the associated pseudo-code. The description of
these derivations relies on the Chinese restaurant analogies associated with
the HDP and sticky HDP-HMM, which are expounded upon in this supplementary
material. We also provide a list of notational conventions used throughout
the paper.
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| DOI |
10.1214/10-AOAS395SUPP |
| Link |
http://lib.stat.cmu.edu/aoas/395/supplement.pdf
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Copula Gaussian Graphical Models and Their
Application to Modeling Functional Disability Data
Adrian Dobra and Alex Lenkoski
Volume 5 Issue 2A, pg. 969-993
Supplements
| Title |
C++ implementation of copula Gaussian graphical models
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| Description |
We provide source code for the
methodology described in this paper. Our program takes advantage of
cluster computing to run several Markov chains in parallel. By using
this code, one can replicate the analyses of the Rochdale data and the
NLTCS functional disability data for which we give sample input files.
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| DOI |
10.1214/10-AOAS397SUPP |
| Link |
http://lib.stat.cmu.edu/aoas/397/supplement.zip |
FDR Control with adaptive procedures and FDR monotonicity
Amit Zeisel, Or Zuk, and Eytan Domany
Volume 5 Issue 2A, pg. 943-968
Supplements
| Title |
Supplementary material for: FDR control with adaptive procedures and FDR monotonicity
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| Description |
In this supplementary file we provide proofs of
the claims and theorem presented in the paper, together with technical details
regarding the proposed estimator and of the simulations performed. The document
includes the following sections:
Supplement A: Proof of Theorem 2.3.
Supplement B: Designing the IBHsum estimator.
Supplement C: Proof of Claim 3.1.
Supplement D: Proof of the monotonicity theorem.
Supplement E: Details of the simulations.
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| DOI |
10.1214/10-AOAS399SUPP |
| Link |
http://lib.stat.cmu.edu/aoas/399/supplement.pdf |
A mixed effects model for longitudinal relational and network data, with applications to international trade and conflict
Anton H. Westveld and Peter D. Hoff
Volume 5 Issue 2A, pg. 843-872
Supplements
Missing Data In Value-Added Modeling of Teacher Effects
Daniel F. McCaffrey and J.R. Lockwood
Volume 5 Issue 2A, pg. 773-797
Supplements
Automated Analysis of Quantitative Image Data using Isomorphic Functional Mixed Models, with Application to Proteomics Data
Jeffrey S Morris, Veerabhadran Baladandayuthapani, Richard C. Herrick, Pietro P Sanna, and Howard Gutstein
Volume 5 Issue 2A, pg. 894-923
Supplements
| Title |
Computational details for wavelet-space implementation of ISO-FMM for image data
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| Description |
Computational details for wavelet implementation of the
ISO-FMM for image data, including empirical Bayes method for estimating
regularization parameters, MCMC details and Metropolis--Hastings
details for covariance parameters.
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| DOI |
10.1214/10-AOAS407SUPPA |
| Link |
http://lib.stat.cmu.edu/aoas/407/supplement_A.pdf |
| Title |
Supplementary figures |
| Description |
Supplementary figures, including a virtual 2d gel
simulated from the model, a demonstration of the spatial covariance
structure induced by the model and 8 plots containing zoomed-in results
from analysis of application data in certain interesting regions of the gel.
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| DOI |
10.1214/10-AOAS407SUPPB |
| Link |
http://lib.stat.cmu.edu/aoas/407/supplement_B.pdf |
| Title |
Spatial covariance structure in image WFMM |
| Description |
Computational details for wavelet implementation of the
ISO-FMM for image data, including empirical Bayes method for estimating
regularization parameters, MCMC details and Metropolis--Hastings
details for covariance parameters. |
| DOI |
10.1214/10-AOAS407SUPPC |
| Link |
http://lib.stat.cmu.edu/aoas/407/supplement_C.pdf |
| Title |
Movie file illustrating spatial covariance structure of ISO-WFMM with 2D wavelet transform
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| Description |
Windows movie file illustrating the nonstationary
spatial covariance structure induced by the ISO-FMM with 2D wavelet
bases, with independence assumed among wavelet coefficients.
Description of data yielding this movie is provided in the file
"Spatial Covariance Structure in Image WFMM.pdf," also available as
supplementary material.
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| DOI |
10.1214/10-AOAS407SUPPD |
| Link |
http://lib.stat.cmu.edu/aoas/407/supplement_D.wmv |
Sparse Partitioning: Nonlinear regression with binary or tertiary predictors, with application to association studies
Doug Speed and Simon Tavaré
Volume 5 Issue 2A, pg. 873-893
Supplements
| Title |
Extra material
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| Description |
Provides additional details of Sparse
Partitioning's methodology, full
explanation of the simulation studies and extended results from
applying the method to real data sets.
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| DOI |
10.1214/10-AOAS411SUPP |
| Link |
http://lib.stat.cmu.edu/aoas/411/supplement.pdf |
Variance Estimation for Nearest Neighbor Imputation for U.S. Census Long Form Data
Jae-kwang Kim, Wayne Fuller, and William Bell
Volume 5 Issue 2A, pg. 824-842
Supplements
| Title |
Illustrated calculations
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| Description |
We illustrate the construction of replicates for
variance estimation with a simple example where a simple random sample
of original size six is selected with two missing values and two donors
per missing value.
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| DOI |
10.1214/10-AOAS419SUPPA |
| Link |
http://lib.stat.cmu.edu/aoas/419/supplement_a.pdf |
Mean-Variance Portfolio Optimization When Means and Covariances are Unknown
Tze Leung Lai, Haipeng Xing, and Zehao Chen
Volume 5 Issue 2A, pg. 798-823
Supplements
Correcting for Survivor Treatment-Selection Bias with a Structural Accelerated Failure Time Model: Survival in Oscar Award Winning Performers
Xu Han, Dylan Small, Dean Foster, and Vishal Patel
Volume 5 Issue 2A, pg. 746-772
Supplements
| Title |
Oscar Award data for actors and actresses |
| Description |
We have compiled a data file that
records the nominees and winners for each award (best lead actor, best
lead actress, best supporting actor, best supporting actress) on each
Oscar Award date. We collected the data from http://imdb.com. The
selection interval spanned from the inception of the Oscar Awards to
July 25, 2007. |
| DOI |
10.1214/10-AOAS424SUPPA |
| Link |
http://lib.stat.cmu.edu/aoas/424/supplement.dat |
| Title |
R code for data analysis and simulation |
| Description |
We provide the R code for our data
analysis and simulation studies. File "R code.txt'' is for
preprocessing the Oscar data and data analysis in Section 4. File
"simulation 1.txt" is for the simulation studies in Sections 24 and
35, especially for Tables 4, 12, and Figure 3. File "simulation
2.txt'' is for the simulation studies in Tables 5 --10 and Figures 1 and 2.
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| DOI |
10.1214/10-AOAS424SUPPB |
| Link |
http://lib.stat.cmu.edu/aoas/424/supplement.zip |
Bayesian hierarchical modeling for signaling pathway inference from single cell interventional data
Ruiyan Luo and Hongyu Zhao
Volume 5 Issue 2A, pg. 725-745
Supplements
| Title |
Additional descriptions and results of hierarchical models
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| Description |
Materials include description and simulation results of
the hierarchical model (mHM) with varying variances of intrinsic noises
(σIik)2, MCMC algorithm for the hierarchical model (HM),
direction inference for the restricted hierarchical model (RHM), and
additional figures of posterior inference and networks.
|
| DOI |
10.1214/10-AOAS425SUPP |
| Link |
http://lib.stat.cmu.edu/aoas/425/supplement.pdf |
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