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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 (see Faculty and Staff or from the Department's anonymous ftp site. 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

2009

Bai - Simultaneous drift conditions for Adaptive Markov Chain Monte Carlo algorithms
Craiu/Di Narzo - A Mixture-Based Approach to Regional Adaptation for MCMC
Bai - An Adaptive Directional Metropolis-within-Gibbs algorithms
Atchade/Roberts/Rosenthal - Optimal Scaling of Metropolis-Coupled Markov Chain Monte Carlo
Proschan/Rosenthal – Beyond the Quintessential Quincunx

2008

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

2007

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

2006

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

2005

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

2004

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

2003

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

2002

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

2001

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

2000

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

1999

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

1998

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

1997

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

1996

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

1995

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

1994

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

1993

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

1992

Evans - The surprise distribution and some uses in statistical inference
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
Srivastava/Wu - On-line Quality Control Procedures based on Random Walk Model and Integrated Moving Average Model of Order (0,1,1)
Guttman/Pena - A Bayesian Look At Diagnostics In The Univariate Linear Model
Wang - Smoothing Splines for Non-parametric Regression Percentiles
Pena/Guttman - Comparing Probabilistic Methods for Outlier Detection
Reiser/Guttman/Lin/Guess/Usher - Bayesian Inference for Masked System Life Time Data
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
Hastie/Buja/Tibshirani - Penalized Discriminant Analysis
Hastie/Tibshirani - Handwritten Digit Recognition via Deformable Prototypes
Guttman/Pena - A Bayesian Look At Diagnostics In The Univariate Linear Model
Lin/Guttman - Handling spuriosity in the Kalman filter
Mo/Wang - Asymptotic Normality for Estimators of Eigenvectors
Srivastava/Chow - A Comparison of Some OMNIBUS CUSUM and OMNIBUS EWMA Statistical Process Control Procedures

1991

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

1990

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

1989

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

1988

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

1987

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

1986

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

1985

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

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

1983

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

1982

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

1981

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

1980

Srivastava/Carter - Asymptotic Distribution of Latent Roots and Applications
Srivastava - Multivariate Data with Missing Observations
Srivastava - On Tests for Detecting Change in the Multivariate Mean
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
Waugh - Application of the Galton-Watson Process to the Kin Number Problem

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