Research

Technical Reports

To see the Technical Reports produced in the Department during a particular year use the index for the relevant year below. Some Technical Reports are available online from the author's homepage. If a technical report is not available online it can be obtained by writing to:

Technical Report Series
Department of Statistics
University of Toronto
Toronto, Ontario M5S 1A1

or by sending email to sjohns@utstat.utoronto.ca

2010

1. K.  Łatuszyński/Rosenthal - Adaptive Gibbs sampler

2009

1. Bai - Simultaneous drift conditions for Adaptive Markov Chain Monte Carlo algorithms
2. Craiu/Di Narzo - A Mixture-Based Approach to Regional Adaptation for MCMC
3. Bai - An Adaptive Directional Metropolis-within-Gibbs algorithms
4. Atchade/Roberts/Rosenthal - Optimal Scaling of Metropolis-Coupled Markov Chain Monte Carlo
5. Proschan/Rosenthal – Beyond the Quintessential Quincunx
6. Rosenthal/Yoon - Detecting Multiple Authorship of United States Supreme Court Legal Decisions Using Function Words 

7. Evans/Jang - Weak Informativity and the Information in One Prior Relative to Another

2008

1. Yang - Recurrent and Ergodic Properties of Adaptive MCMC
2. Yang - On The Weak Law Of Large Numbers For Unbounded Functionals For Adaptive MCMC
3. Evans/Jang - Invariant P-values for Model Checking and checking for Prior-data Conflict
4. Rosenthal - Optimal Proposal Distributions And Adaptive MCMC
5. Rosenthal - Optimising Monte Carlo Search Strategies for Automated Pattern Detection
6. Bai/Roberts/Rosenthal - On the Containment Condition for Adaptive Markov Chain Monte Carlo Algorithms
7. Craiu/Rosenthal/Yang - Learn From Thy Neighbor: Parallel-Chain Adaptive MCMC
8. Roberts/Rosenthal - Quantitative Non-Geometric Convergence Bounds for Independence Samplers
9. Evans/Jang - The Informationin One Prior Relative to Another

2007

1. Rosenthal - Waiting Time Correlations on Disorderly Streetcar Routes
2. Rosenthal - Notes About Markov Chain CLTs
3. Rosenthal - AMCMC: An R interface For adaptive MCMC
4. Hobert¹/Rosenthal - Norm Comparisons for Data Augmentation
5. Li/Zhang/Neal - A Method for Avoiding Bias from Feature Selection with Application to Naive Bayes Classification Models
6. Evans/Shakhatreh - Consistency of Bayesian Estimates for the Sum of Squared Normal Means with a Normal Prior
7. Shahbaba/Neal - Nonlinear Models Using Dirichlet Process Mixtures
8. Yao/Craiu/Reiser - Nonparametric Adjustment for Receiver Operating Characteristic Curves

2006

1. Bedard - Weak Convergence of Metropolis Algorithms for Non-iid Target Distributions
2. Bedard - Optimal Acceptance Rates for Metropolis Algorithms: Moving Beyond 0.234
3. Jasra/Yang - A regeneration proof of the central limit theorem for uniformly ergodic Markov chains
4. Srivastava - Some tests Criteria For the Covariance Matrix With Fewer Observations Than the Dimension
5. Bedard - Efficient Sampling using Metropolis Algorithms: Applications of Optimal Scaling Results
6. Shahbaba/Neal - Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors
7. Neal - Puzzles of Anthropic Reasoning Resolved Using Full Non-indexical Conditioning
8. Evans - Discussion of Nested Sampling for Bayesian Computations by John Skilling
9. Staicu/Reid - On the uniqueness of probability matching priors
10. Roberts/Rosenthal - Examples of adaptive MCMC
11. Roberts/Rosenthal/Segers/Sousa - Extremal Indices, Geometric Ergodicity of Markov Chains, and MCMC
12. Roberts/Rosenthal - Variance Bounding Markov Chains

2005

1. Roberts/Rosenthal - Coupling and Ergodicity of Adaptive MCMC
2. Srivastava/Kubokawa - Comparison of Discrimination Methods for High Dimensional Data
3. Evans/Moshonov - Checking for Prior-Data Conflict with Hierarchically Specified Priors
4. Craiu/Sun - Choosing the Lesser Evil: Trade-off Between False Discovery Rate and Non-Discovery Rate
5. Bull/Lewinger/Lee - Penalized Maximum Likelihood Estimation for Multinomial Logistic Regression Using the Jeffreys Prior
6. Neal - The Short-Cut Metropolis Methods
7. Jain/Neal - Splitting and Merging Components of a Nonconjugate Dirichlet Process Mixture Model
8. Evans/Guttman/Swartz - Optimality and Computations for Relative Surprise Inference
9. Craiu/Duchesne - A Generalized Estimating Equations Approach to Longitudinal Conditional Logistic Regression
10. Shahbaba/Neal - Improving Classification When a Class Hierarchy is Available Using a Hierarchy-Based Prior
11. Neal - Estimating Ratios of Normalizing Constants Using Linked Importance ampling
12. Jain - The GI/G/K/N queue with supplementary variable method

2004

1. Srivastava - Multivariate Theory For Analyzing High Dimensional Data
2. Roberts/Rosenthal - General state space Markov chains and MCMC algorithms
3. Bramson/Quastel/Rosenthal - When Can Martingales Avoid Ruin?
4. Craiu/Lee - Model Selection for the Competing Risks Model with and without masking
5. Roberts/Rosenthal/Sousa - Extremal Indices, Geometric Ergodicity Of Markov Chains, and MCMC
6. Neal - Improving Asymptotic Variance of MCMC Estimators: Non-reversible Chains are Better
7. Craiu - Antithetic Acceleration of the Multiple-Try Metropolis
8. Evans/Guttman/Swartz - Relative Surprise Inferences and Computations For a Reliability Problem
9. Srivastava - Some Tests concerning the Covariance Matrix in High Dimensional Data
10. Srivastava/Kubokawa - Empirical Bayes Regression Analysis with Many Regressors but Fewer Observations
11. Neal - Taking Bigger Metropolis Steps by Dragging Fast Variables
12. Roberts/Rosenthal - Harris Recurrence of Metropolis-Within-Gibbs and Trans-Dimensional Markov Chains
13. Evans/Moshonov - Checking for Prior-Data Conflict

2003

1. Craiu/Duchesne - Inference Based on the EM Algorithm for the Competing Risk Model with Masked Causes of Failure
2. Roberts/Rosenthal - Downweighting Tightly Knit Communities in World Wide Web Rankings
3. Christensen/Roberts/Rosenthal - Scaling Limits for the Transient Phase of Local Metropolis-Hastings Algorithms
4. Neal - Markov Chain Sampling for Non-Linear State Space Models Using Embedded Hidden Markov Models
5. Atchade/Rosenthal - On Adaptive Markov Chain Monte Carlo Algorithms
6. Sun/Bull - Resampling-Based Testing and Effect Estimation in Genomewide Scans

2002

1. Evans/Zou - On the Robustness of Relative Surprise Inferences to the Choice of Prior
2. Duchesne/Rosenthal - Stochastic Justification of Some Simple Reliability Models*
3. Rosenthal - Quantitative convergence rates of Markov chains: A simple account
4. Feuerverger/Rosenthal - Achieving Limiting Distributions for Markov Chains Using Back Buttons
5. Craiu/Meng - Multi-process Parallel Antithetic Coupling For Backward and Forward Markov Chain Monte Carlo
6. Srivastava - Multivariate Analysis With Fewer Observations than the Dimension

2001

1. Pinto/Neal - Improving Markov Chain Monte Carlo Estimators by Coupling to an Approximating Chain
2. Bellhouse/Chipman/Stafford - Additive models for survey data via penalized least squares
3. Drekic/Stafford - Symbolic Computation of Moments in Priority Queues
4. Neal - Defining Priors for Distributions Using Dirichlet Diffusion Trees
5. Roberts/Rosenthal - One-Shot Coupling for Cetain Stochastic Recursive Sequences
6. Duchesne/Stafford - A kernel density estimate for interval censored data
7. Roberts/Rosenthal - Combinatorial identities associated with CFTP
8. Neal - Transferring Prior Information between Models Using Imaginary Data
9. Roberts/Rosenthal - Optimal scaling for various Metropolis-Hastings algorithms
10. Rosenthal - Asymptotic Variance and Convergence Rates of Nearly-Periodic MCMC Algorithms

2000

1. Roberts/Rosenthal - Small and Pseudo-Small Sets for Markov Chains.
2. Jain/Rao - State-Dependent Rates In A Finite-Capacity Double-Ended Queue With an Application To Inventory Problem.
3. Jain/Neal - A Split-Merge Markov Chain Monte Carlo Procedure For the Dirichlet Process Mixture Model.
4. Roberts/Breyer/Rosenthal - A note on geometric ergodicity and floating-point roundoff error
5. Neal - Slice Sampling
6. Alkhamisi/Fraser - On Higher Order Likelihood Analysis of The One-Way Random Effects
7. Lu/Rosenthal/Shaffer - Crossword puzzles: Experiments with meta-search in propositional reasoning
8. Gordon/Rosenthal - Capitalism's Growth Imperative
9. Borodin/Roberts/Rosenthal/Tsaparas - Finding Authorities and Hubs From Link Structures on the World Wide Web
10. Srivastava - Nested Growth Curve Models
11. Yuen - Generalization of Discrete-time Geometric Bounds to Convergence Rate of Markov Processes on $ R sup n $
12. Glimm/Srivastava - Multivariate Tests of normal mean vectors with restricted Alternatives
13. Kollo/Srivastava - A New Class of Skewed Multivariate Distributions

1999

1. Hirotsu/Srivastava - Simultaneous Confidence Intervals Based on One-sided max t Test
2. Rosenthal - Parallel computing and Monte Carlo algorithms
3. Rosenthal - A review of asymptotic convergence for general state space Markov chains
4. Roberts/Rosenthal - The Polar Slice Sampler
5. Roberts/Rosenthal - Recent progress on computable bounds and the simple slice sampler
6. Roberts/Rosenthal - Bayesian models with infinite hierarchies
7. Srivastava - Singular Wishart and Multivariate Beta Distributions
8. Srivastava/Solanky - Predicting Multivariate Response In Linear Regression Model
9. Jain/Rao - Computational procedure for the steady-state analysis of a finite-capacity-bulk-service double-ended queueing system
10. Neal - Circularly-Coupled Markov Chain Sampling
11. Israel/Rosenthal/Wei - Finding generators for Markov chains via empirical transition matrices

1998

1. Feuerverger/Robinson/Wong - On the Second Order Relative Accuracy of Certain Bootstrap and Saddlepoint Approximation Procedures
2. Evans/Swartz - Higher Order Envelope Random Variate Generators
3. Escobar $ sup 1 $/West - Computing Bayesian Nonparametric Hierarchical Models
4. Fujkoshi/$ Seo sup * $ - Asymptotic Expansions For The Joint Distribution Of Correlated Hotelling's $ T sup 2 $ Statistics Under Normality
5. Neal - Annealed Importance Sampling
6. Srivastava/von Rosen - Growth Curve Models
7. Srivastava/Oashima - Classification With A Preassigned Error Rate When Two Covariance Matrices Are Equal
8. Gibbs - Bounding Convergence Time of the Gibbs Sampler in Bayesian Image Restoration
9. Petrone/Roberts/Rosenthal - A note on convergence rates of Gibbs sampling for nonparametric mixtures*
10. Murdoch/Rosenthal - Efficient Use of Exact Samples
11. Osborne/Rosenthal/Tanner - Meeetings with costly participation
12. Murdoch/Rosenthal - An extension of Fill's exact sampling algorithm to non-monotone chains
13. Jain/Reiss - Busy Periods and Busy Cycles In Bulk-Arrival Queueing Systems
14. Pemantle/Rosenthal - Moment conditions for a sequence with negative drift to be uniformly bounded in $ L sup r $
15. Neal - Markov Chain Sampling Methods for Dirichlet Process Mixture Models
16. Srivastava/Kubokawa - Improved Nonnegative Estimation of Multivariate Components of Variance
17. Kubokawa/Srivastava - Estimating Risk and Mean Squared Error Matrix in Stein Estimation
18. Roberts/Rosenthal - Sufficient Markov Chain

1997

1. Pavlenko - Asymptotic behavior of the probabilities misclassification for discriminant functions with weighting
2. Neal - Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification
3. Roberts/Rosenthal - Two convergence properties of hybrid samplers
4. Efron/Tibshirani - The Problem of Regions
5. Roberts/Rosenthal - Markov chain Monte Carlo: Some practical implications of theoretical results
6. Srivastava - Resampling Methods for Imputing Missing Observations
7. Resampling Methods for Imputing Missing Observations in Regression Models
8. Rosenthal/Schwartz - Gambling Systems and Multiplication-Invariant Measures
9. Zarepour/Knight - Bootstrapping point processes with some applications
10. Andrews/Austin/Quigley - Measuring Warehouse Performance
11. Roberts/Rosenthal - On convergence rates of Gibbs samplers for uniform distributions
12. Roberts/Rosenthal - Convergence of slice sampler Markov chains
13. Nagao/Srivastava - Fixed Width Confidence Region for The Mean of A Multivariate Normal Distribution
14. Kubokawa/Srivastava - Robust Improvements in Estimation of Mean and Covariance Matrices in Elliptically Contoured Distribution
15. Fujikoshi/ $ Seo sup 1 $ - Asymptotic Approximations for EPMC's of the Linear and the Quadratic Discriminant Functions When the Sample Sizes and the Dimension are Large
16. Knight - Asymptotics for $ L sub 1 $ regression estimtors under general conditions
17. $ Yuen sup * $ - Applications of Cheeger's Constant to The Convergence Rate of Markov Chains on $ R sup n $
18. Srivastava - Generalized Multivariate Analysis of Variance Models
19. Evans/Swartz - An Algorithm For The Approximation Of Integrals With Exact Error Bounds
20. Oyet/Wiens - Robust Designs for Wavelet Approximations of Regression Models
21. Tibshirani/Knight - The covariance inflation criterion for adaptive model selection
22. Neal - Markov Chain Monte Carlo Methods Based on `Slicing' the Density Function
23. $ Seo sup * $ /Srivastava - Testing Equality of Means and Simultaneous Confidence Intervals in Repeated Measures with Missing Data
24. Cowles/Roberts/Rosenthal - Possible biases induced by MCMC convergence diagnostics

1996

1. Roberts/Rosenthal - Quantitative bounds for convergence rates of continuous time Markov processes
2. Tibshirani - Bias, variance and prediction error for classification rules
3. Haste/Ikeda/Tibshirani - Computer-aided diagnosis of mammographic masses
4. Cowles/Rosenthal - A simulation approach to convergence rates for Markov chain Monte Carlo algorithms
5. Redelmeier/Tibshirani - Cellular telephones and automobile collisions: some variations on matched case-control analysis
6. Evans/Swartz - Random Variable Generation Using Concavity Properties of Transformed Densities
7. Neal/Dayan - Factor Analysis Using Delta-Rule Wake-Sleep Learning
8. Jain - Autoregressive process and its Applications To Queueing Model
9. Roberts/Rosenthal - Geometric Ergodicity and Hybrid Markov Chains
10. Tibshirani - Who is the fastest man in the world?
11. Hastie/Tibshirani - Classification by Pairwise Coupling
12. Fraser/Reid/Wu - A simple general formula for tail probabilities for frequentist and Bayesian inference

1995

1. Srivastava - Robustness of Control Procedures For Integrated Moving Average Provess of Order One
2. Willmot/Lin - Bounds On The Tails of Convolutions Of Compound Distributions
3. Srivastava/Wu - Evaluation of Optimum Weights and Average Run Lengths in EWMA Control Schemes
4. Zarepour/Knight - Bootstrapping unstable first order autoregressive processes with errors in the domain of attraction of stable law
5. Reid - Higher order asymptotics and likelihood: a review
6. Reid - Statistics in the twenty-first century: Asymptotic theory and the foundations of statistics
7. Roberts/Rosenthal - Optimal scaling of discrete approximations to Langevin diffusions
8. Neal - Suppressing Random Walks in Markov Chain Monte Carlo Using Ordered Overrelaxation
9. Rosenthal - Faithful couplings of Markov chain: now equals forever
10. Srivastava - Reduced Rank Discrimination
11. Evans/Swartz - Bayesian Integration Using Multivariate Student Importance Sampling
12. Srivastava - CUSUM Procedure for Monitoring Variability
13. Willmot/Lin - Simplified Bounds on the Tails of Compound Distributions
14. Jain - A Comparison of Stochastically Ordered Que
15. Roberts/Rosenthal/Schwartz - Convergence properties of perturbed Markov chains
16. Tibshirani/Knight - Model search and inference by bootstrap ``bumping''
17. Kubokawa/Srivastava - Double Shrinkage Estimators of Ratio of Variances

1994

1. Hastie/Tibshirani- Discriminant Analysis by Gaussian Mixtures
2. Tibshirani - Regression shrinkage and selection via the Lasso
3. Reid - The roles of conditioning in inference
4. Oman/Srivastava - Exact Mean Squared Error Comparisons of the Inverse and Classical Estimators in Multi-univariate Linear Calibration
5. Lin - Tail of Compound Distributions and Excess Time
6. Baxter/Rosenthal - Rates of Convergence for Everywhere-Positive Markov Chains
7. Srivastava - Admissibility of the Inverse and the Inadmissibility of the Classical Estimators in Multi-univariate Linear Calibration
8. Boyle/Lin - Optimal Portfolio Selection With Transaction Costs
9. Tibshirani - A proposal for variable selection in the Cox model
10. Tibshirani - A comparison of some error estimates for neural network models
11. Jain - Diffusion Approximation and Estimation for G/G/1 Queueing Systems
12. Banjevic - Recurrent Relations for Distribution of Waiting Time in Markov Chain
13. Rosenthal - Analysis of the Gibbs sampler for a model related to James-Stein estimators
14. Mojirsheibani/Tibshirani - Bootstrap Prediction Intervals For a Future MLE
15. Tibshirani/Hinton - ``Coaching'' variables for regression and classification
16. Evans/Swartz - Methods for Approximating Integrals With Applications to Statistics
17. Jain - Problem of Statistical Inference for Heavy Traffic in M/M/1 Queue
18. Jain - Sequential Probability Ratio Test to Control the Traffic Intensity for M/M/1 Queueing Model
19. Evans - Bayesian Hypothesis Testing via the Concept of Surprise
20. LeBlanc/Tibshirani - Monotone Shrinkage of Trees
21. Neal - Sampling from Multimodal Distributions Using Tempered Transitions
22. Roberts/Rosenthal - Shift-coupling and convergence rates of ergodic averages
23. Rosenthal - Markov chain convergence: from finite to infinite
24. Abdolell/LeBlanc/McLaughlin - Poisson Regression Trees

1993

1. Guttman/Olkin/Philips - Estimating The Number Of Aberrant Laboratories
2. Tang - Selection Of U-Designs
3. Fraser/Reid - Ancillaries and third order significance
4. Jing/Feuerverger/Robinson - Saddlepoint Approximations in Bootstrap Applications
5. Rao/Tibshirani - Bootstrap Model Selection Via The Cost Complexity Parameter In Regression
6. Leblanc/Crowley - Step-function Covariate Effects in the Proportional Hazards Model
7. LeBlanc - An Adaptive Expansion Method for Regression
8. Andrews/Feuerverger - General Saddlepoint Approximation Methods for Bootstrap Configurations
9. Berhane/Tibshirani - Generalized Additive Models for Longitudinal Data
10. Mojirsheibani/Tibshirani - Bootstrap Prediction Intervals for a Future MLE
11. Evans/Guttman/Haitovsky/Swartz - Bayesian Analysis of Binary Data Subject to Misclassification
12. Kim - Group Representations and Nonparametric Density and Deconvolution Estimation on Compact Lie Groups
13. Srivastava - Economical Quality Control Procedures Based on Integrated Moving Average Process of Order One
14. Yao/Tritchler - Directed Acyclic Graphs, Linear Recursive Regression, and Inference about Causal Ordering
15. Evans/Gilula/Guttman/Swartz - Bayesian Analysis of Stochastically Ordered Distributions of Categorical Variables
16. LeBlanc/Tibshirani - Combining estimates in regression and classification
17. Healy/Kim - An Empirical Bayes Approach to Directional Data and Efficient Computation on the Sphere*
18. Rosenthal - Markov Chains, Eigenvalues, and Coupling
19. Rosenthal - Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo
20. Rosenthal - Rates of Convergence for Gibbs Sampling for Variance Component Models

1992

1. Evans - The surprise distribution and some uses in statistical inference
2. Srivastava/Chow - Fast Accurate Approximations for the ARLs of the FIR CUSUM Scheme and a Simple Method to Calculate the Decision Boundary for the CUSUM Scheme
3. Srivastava/Wu - On-line Quality Control Procedures based on Random Walk Model and Integrated Moving Average Model of Order (0,1,1)
4. Guttman/Pena - A Bayesian Look At Diagnostics In The Univariate Linear Model
5. Wang - Smoothing Splines for Non-parametric Regression Percentiles
6. Pena/Guttman - Comparing Probabilistic Methods for Outlier Detection
7. Reiser/Guttman/Lin/Guess/Usher - Bayesian Inference for Masked System Life Time Data
8. Srivastava/Chow - Comparison of the CUSUM Procedure with Other Procedures that Detect an Increase in the Variance and a Fast Accurate Approximation For the ARL of the CUSUM Procedure
9. Hastie/Buja/Tibshirani - Penalized Discriminant Analysis
10. Hastie/Tibshirani - Handwritten Digit Recognition via Deformable Prototypes
11. Guttman/Pena - A Bayesian Look At Diagnostics In The Univariate Linear Model
12. Lin/Guttman - Handling spuriosity in the Kalman filter
13. Mo/Wang - Asymptotic Normality for Estimators of Eigenvectors
14. Srivastava/Chow - A Comparison of Some OMNIBUS CUSUM and OMNIBUS EWMA Statistical Process Control Procedures

1991

1. Lin/Guttman - Handling Spuriosity in the Kalman Filter
2. Tibshirani/LeBlanc - A Strategy for Binary Classification and Description
3. O'Rourke/Naylor/McGeer/L'Abbe/Detsky - Incorporating Quality Appraisals into Meta-analyses of Randomized Clinical Trials
4. Guttman - A Bayesian Look At The Question Of Diagnostics
5. Andrews/Stafford - Tools for the Symbolic Computation of Asymptotic Expansions
6. Brunner - Bayesian nonparametric methods for data from a unimodal density
7. DiCiccio/Tibshirani - On the implementation of profile likelihood methods
8. Hastle/Tibshirani - Varying-coefficient models
9. Mo - Sensitivity Analysis For Additive Regression And Its By-products
10. Tibshirani/LeBlanc - A Strategy for Binary Classification and Description;
11. O'Rourke/Naylor/McGeer/L'Abbe/Detsky - Incorporating Quality Appraisals into Meta-analyses of Randomized Clinical Trails
12. Guttman/Olkin - A Model For Estimating The Number of Aberrant Laboratories
13. Lin/Guttman - Handling Spuriosity in the Kalman Filter
14. Srivastava/Wu - On Taguchi's On-Line Control Procedure With Measurement Error
15. LeBlanc/Tibshirani - Adaptive Principal Surfaces
16. Mo - Nonparametric Estimation by (Parametric) Linear Regression
17. Tibshirani - Principal Curves Revisited
18. Mo - Asymptotic Normality of Minimum Contrast Estimators
19. Evans/Guttman/Olkin - Numerical Aspects In Estimating The Parameters Of A Mixture Of Normal Distributions;
20. Chen - Extended Quasi-likelihoods and Optimal Estimating Functions
21. Chen - Quasi-likelihood Estimation in Stochastic Regression Models
22. Srivastava/Wu - An Improved Version of Taguchi's On-line Control Procedure;
23. Srivastava/Wu - Taguchi's On-line Control Procedures and Some Improvements;
24. Srivastava/Wu - A Comparison of EWMA and CUSUM Procedures in the Two-sided Case
25. Srivastava/Wu - Dynamic Sampling Plan in CUSUM Procedure for Detecting a Change in the Drift of Brownian Motion
26. Srivastava/Wu - Dynamic Sampling Plan in Shiryayev-Roberts Procedure for Detecting a Change in the Drift of Brownian Motion

1990

1. Srivastava/Wu - Optimal Bayes search for the change point in a finite interval
2. Wong/Reid - Solutions to Selected Exercises/Analysis of Survival Data
3. Srivastava/Wu - A second order approximation on Taguchi's on-line control procedure
4. Fraser/Reid - From multiparameter likelihood to tail probability for a scalar parameter
5. Andrews - Calculations with Random Variables using Mathematica
6. Brant/Tibshirani - Missing covariate values in generalized regression models
7. Evans - Adaptive Importance Sampling and Chaining
8. Evans/Swartz - Inferential and Computational Uses of a Class of Density Functions
9. Efron/Tibshirani - Statistical Data Analysis In The Computer Age
10. Evans/Gilula/Guttman - Log-Linear And Goodman's RC Model
11. Reiser/Faraggi/Guttman - Choice of Sample Size for Stress-Strength Models
12. Draper/Guttman - Treating Bias as Variance for Experimental Design Purposes
13. Mo - Robust Additive Regression I: Population Aspect
14. Mo - Robust Additive Regression II: Finite Sample Approximations
15. Srivastava/Wu - On Beta-Binomial Model for Extrabinomial Variation
16. Srivastava/Wu - Comparison of Cusum, Ewma, and Shiryayev-Roberts Procedures for Detecting A Shift In The Mean

1989

1. Tibshirani - Smoothing Methods For The Study of Synergism
2. Bell/Reid - Statistical Problems in Rainfall Measurements From Space
3. Draper/Guttman - Rationalization of The "Alphabetic-Optimal" and "Variance Plus Bias" Aproaches to Experimental Desin
4. Srivastava/Khan - Multivariate Cusum Procedures for The Normal Mean Vector
5. Guttman/Bagchi - Prediction In Circular Distributions
6. Keen/Srivastava - The Asymptotic Variance of the Interclass Correlation Coefficient
7. Lin/Chen - On The Identity Relationships of $ 2 sup { k-p } $ Designs
8. Srivastava/Wu - Optimal Bayes Stopping Rules for Detecting the Change Point In A Bernoulli Process
9. Srivastava/Wu - Change Point Problem In A Diffusion Process With Partial Observations
10. Bagchi/Draper/Guttman - Bayesian Assessment of Assumptions of Regression Analysis
11. Guttman/Olkin - Modeling Interlaboratory Differences: A Bayesian Analysis
12. Srivastava/Wu - Statistical Inference and Optimal Inspection with Incomplete Inspections
13. Srivastava/Wu - Optimal Bayes Stopping Rules for Detecting the Change Point In A Bernoulli Process
14. Srivastava/Wu - Change Point Problem In A Diffusion Process With Partial Observations
15. Bagchi/Draper/Guttman - Bayesian Assessment of Assumptions of Regression Analysis
16. Guttman/Olkin - Modeling Interlaboratory Differences: A Bayesian Analysis
17. Srivastava/Wu - Statistical Inference and Optimal Inspection with Incomplete Inspections
18. Bhattacharyya/Johnson/Guttman/Reiser - Bayesian Inference for Stress-Strength Models with Explanatory Variables
19. Brunner - Bayesian linear regression with error terms that have symmetric unimodal densities
20. Keen/Srivastava - The Asymptotic Variance of the Interclass Correlation Coefficient

1988

1. Fraser - Normed Likelihood as Saddlepoint Approximation
2. Evans - An Example Concerning the Likelihood Function
3. Fraser/Reid - On Conditional Inference for a Real Parameter: a Differential Approach on the Sample Space
4. Tibshirani and Hastie - Exploring the nature of covariate effects in the proportional hazards model
5. Andrews - General Monte Carlo Methods for Research in Statistics
6. Bagchi/Guttman - Spuriosity and Outliers in Circular Data
7. Bagchi/Draper/Guttman - Bayesian Assessment of Assumptions of Regression Analysis
8. Feuerverger - On the Empirical Saddlepoint
9. McCullagh/Tibshirani - A simple method for the adjustment of profile likelihoods
10. Fraser/Reid - Adjustments to profile likelihood
11. Evans - Monte Carlo Computation of Marginal Posterior Quantiles
12. Tibshirani - Non-informative priors for one parameter of many
13. Guttman/Menzefricke - Bayesian Estimation in Two-Way Tables with Heterogeneous Variances
14. Evans - Chaining via anealing
15. Srivastava/Ng - Comparison of the Estimators of Intraclass Correlation in The Presence of Covariables
16. Srivastava/Yau - Tail Probability Approximations of a General Statistic With Application to Durbin-Watson Statistic
17. Yau/Srivastava - Approximation of tail probability of a linear combination of non-central chi-squares by saddlepoint method
18. Evans/Gilula/Guttman - Latent Class Analysis of Two-Way Contingency Tables by Bayesian Methods
19. Srivastava/Yau - Saddlepoint method for obtaining tail probability of Wilk's likelihood ratio test
20. Bilodeau - How should one choose the loss function to estimate the covariance structure of a generalized linear model?
21. Reiser/Guttman - Sample Size Choice For Strength Stress Models
22. Tibshirai/Wasserman - Some aspects of the reparameterization of statistical models
23. Pena/Guttman - Optimal collapsing of mixture distributions in robust recursive estimation

1987

1. Srivastava/Keen/Katapa - Estimation of Interclass and Intraclass Correlations in Multivariate
2. Srivastava - Testing for Block Effects and Analysis of Regression Models Based Testing
3. Srivastava/Bilodeau - Stein Estimation Under Elliptical Distributions
4. Hastie/Tibshirani - Generalized Additive Models, Cubic Splines and Penalized Likelihood
5. Reid - Saddlepoint Methods and Statistical Inference, Revised
6. Srivastava/Keen - Monte Carlo Comparisons of Bootstrap Methods
7. Srivastava/Keen - Point and Interval Estimation of the Intraclass Correlation Coefficient
8. Manchester/Trueman - Duchen I: An Interactive Computer Program for Calculating Risks in X
9. Bagchi/Guttman - Bayesian Regression Analysis under Non-Normal Errors
10. Buja/Hastie/Tibshirani - Linear Smoothers and Additive Models
11. Srivastava/Keen - Multivariate Intraclass & Interclass Correlations
12. Wasserman - Prior Envelopes Based on Belief Functions
13. Tibshirani - Variance Stabilization and the Bootstrap
14. Feuerverger - The Analysis of Linear and Nonlinear Time Series by Independence - Testing Procedures
15. Feuerverger/McLeish/Rubinstein - Sensitivity Analysis, the "What If" Problem, and Simulation of Queueing Networks in Heavy Traffic
16. Feuerverger - Some New Perspectives on the MLE and LRT
17. Guttman/Bagchi - Theoretical Considerations of the Multivariate Von Mises-Fisher Distribution

1986

1. T. DiCiccio/R. Tibshirani- Approximating the Profile Likelihood Through Stein's Least Favourable Family
2. M.S. Srivastava -Bootstrap Method in Ranking Slippage Problems 1,2
3. A. Dobriyal/D.A.S. Fraser - Linear Calibration - A Fiductial Method for Interval Estimation
4. R. Tibshirani - Estimating Transformations for Regression - A Variation on ACE
5. I. Guttman/U. Menzefricke - Bayesian Power
6. R. Tibshirani/L. Wasserman - Non Resistent Parameters
7. M. Evans/T. Swartz - Monte Carlo Computation of Some Multivariate Normal Probabilities
8. Bhatt/Guttman/Johnson/Reiser - Statistical Inference for Stress-Strength Models With Covariates
9. N.Draper/M.Evans/I.Guttman - A Bayesian Approach To System Reliability When Two Components Are Dependent
10. Guttman/Draper - Model Selection Problems
11. S. Chakravorti/I. Guttman - A Large Sample Analysis of the Magnitudinal Model in Multivariate Analysis
12. R. Tibshirani - Estimating Transformation for Regression

1985

1. I. Guttman/D. Pena - Robust Kalman Filtering and its Applications
2. D.A.S. Fraser/R.J. Gebotys - Non-Nested Linear Models: A Conditional Confidence Approach
3. R. Tibshirani - How Many Bootstraps?
4. B. Efron/R. Tibshirani - The Bootstrap Method for Assessing Statistical Accuracy
5. M.S. Srivastava - Bootstrapping Durbin-Watson Statistics
6. M.S. Srivastava - Bootstrapping in Ranking and Slippage Problems
7. Y.M. Chan/M.S. Srivastava - Robustness ofFieller's Theorem & Comparison with Bootstrap Method
8. R. Tibshirani/L. Wasserman - A Note on Profile Likelihood, Least Favourable Families and Kullback-Leibler Distance
9. I. Guttman/M.S. Srivastava - Bayesian Method of Detecting Change Point in Regression and Growth Curve Models
10. I. Guttman/U. Menzefricke/D. Tyler - Magnitudinal Effects in the Normal Multivariate Model
11. S.A. Bartlett/I. Guttman - Predictive and Posterior Distributionns for Normal Multivariate Data With Missing Monotone Patterns.
12. M. Evans/D.A.S. Fraser/G. Monette - On the Sufficiency-Conditionality to Likelihood Argument
13. M. Evans/T. Swartz - Sampling from Gauss Rules
14. T. Hastie/R. Tibshirani - Generalized Additive Models
15. T. DiCiccio/R. Tibshirani - Bootstrap Confidence Intervals & Bootstrap Approximations
16. T. Hastie/R. Tibshirani - Generalized Additive Models: Some Applications
17. B. Reiser/I. Guttman - A Comparison of Three Point Estimators for P(Y lt X):The Normal Case
18. B. Reiser/I. Guttman - Statistical Inference for P(Y lt X) - The Normal Case
19. M.S. Srivastava - Multivariate Bioassay, Combination of Bioassays, and Fieller's Theorem
20. Y.M. Chan/M.S. Srivastava - Comparison of Powers for the Sphericity Tests Using Both the Asymtotic Distribution and the Bootstrap Method.
21. M. Bilodeau/M.S. Srivastava - Stein Estimators Under Elliptical Distributions
22. M.S. Srivastava/Y.M. Chan - A Comparison of Bootstrap Method and Edgeworth Expansion in Approximating The Distribution of Sample Variance -- One Sample and Two Sample Cases.

1984

1. I. Guttman/P. Hougaar - Studentization and Prediction Problems in Multivariate Multiple Regression

1983

1. M.S. Srivastava/T.K. Hui - Tests for Multivarate Normality Based on Multivariate Skewness and Kurtosis
2. H. Niederhausen - Some Problems Connected with the Number of Records in a Sequence of Observations
3. H. Niederhausen - Sequences of Binomial Type with Polynomial Coefficients

1982

1. M.S. Srivastava/G.C. Lee - On the Robustness of Tests for Correlation Coefficient in the Presence of an Outlier.
2. M.S. Srivastava/G.C. Lee - On the Choice of Transformations of the Correlation Coefficient With or Without an Outlier.
3. I. Guttman/N.R. Draper - Dropping Observations Without Affecting Posterior and Predictive Distributions
4. I. Guttman/U. Menzefricke - Bayesian Inference in Multivariate Regression with Missing Observations on the Response Variables.
5. M.S. Srivastava - A Graphical Method for Assessing Multivarate Normality and a Measure of Skewness and Kurtosis.
6. M.S. Srivastava/T.K. Hui - Measures of Multivariate Skewness & Kurtosis

1981

1. Dahiya/Guttman - Shortest Confidence and Prediction Intervals for the Log-normal.
2. Chikara/Guttman - Tolerance for the Inverse Gaussian Distribution

1980

1. Srivastava/Carter - Asymptotic Distribution of Latent Roots and Applications
2. Srivastava - Multivariate Data with Missing Observations
3. Srivastava - On Tests for Detecting Change in the Multivariate Mean
4. Srivastava/Awan - On the Robustness of Hotelling's T2-test and Distribution of Linear and Quadratic Forms in Sampling from a Mixture of Two Multivariate Normal
5. Waugh - Application of the Galton-Watson Process to the Kin Number Problem