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Two-Sample Tests
Chapter 4 describes connections, equivalencies, and relationships relating to two-sample tests of null...
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Estimating Sample Skewness from Sample Data Summaries and Associated Evaluation of Normality
AbstractWe propose a method to estimate a sample skewness from the given summary statistics and give explicit formulas for the most common scenarios....
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A note on the application of stochastic approximation to computerized adaptive testing
In the study of item response theory (IRT), the maximum information (item selection) method (or procedure, rule) is prevailing in test constructions,...
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The One-Sample Case
As explained in Chap. 1 , outliers are a serious concern when using the sample mean. This chapter describes two...
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Strong Approximation of Bessel Processes
We consider the path approximation of Bessel processes and develop a new and efficient algorithm. This study is based on a recent work by the...
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Inference about the arithmetic average of log transformed data
A common practice in statistics is to take the log transformation of highly skewed data and construct confidence intervals for the population average...
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On estimation of nonparametric regression models with autoregressive and moving average errors
The nonparametric regression model with correlated errors is a powerful tool for time series forecasting. We are interested in the estimation of such...
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Gaussian Approximation for Penalized Wasserstein Barycenters
AbstractIn this work we consider regularized Wasserstein barycenters (average in Wasserstein distance) in Fourier basis. We prove that random Fourier...
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Sparse Constrained Projection Approximation Subspace Tracking
In this paper we revisit the well-known constrained (orthogonal) projection approximation subspace tracking algorithm and derive, for the first time,...
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Robust estimation of average treatment effects from panel data
In order to evaluate the impact of a policy intervention on a group of units over time, it is important to correctly estimate the average treatment...
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Slice weighted average regression
It has previously been shown that ordinary least squares can be used to estimate the coefficients of the single-index model under only mild...
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A weighted average limited information maximum likelihood estimator
In this article, a Stein-type weighted limited information maximum likelihood (LIML) estimator is proposed. It is based on a weighted average of the...
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Basic Large-Sample Theory
Chapters 3 , 4 , 5...
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Small area estimation of average compositions under multivariate nested error regression models
This paper investigates the small area estimation of population averages of unit-level compositional data. The new methodology transforms the...
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Improved Test Procedure and Sample Size Calculation for Assessing Similarity in Two-Group Comparative Studies with Heterogeneous Variances
The two one-sided tests (TOST) method for mean equivalence or average equivalence has been extended to assessing similarity or switchability for...
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Two-sample Behrens–Fisher problems for high-dimensional data: a normal reference F-type test
The problem of testing the equality of mean vectors for high-dimensional data has been intensively investigated in the literature. However, most of...
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A Comparison of Bayesian Approximation Methods for Analyzing Large Spatial Skewed Data
Commonly, environmental processes are observed across different locations, and observations present skewed distributions. Recent proposals for...
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Generative models and Bayesian inversion using Laplace approximation
The Bayesian approach to solving inverse problems relies on the choice of a prior. This critical ingredient allows expert knowledge or physical...
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A non-classical parameterization for density estimation using sample moments
Probability density estimation is a core problem in statistics and data science. Moment methods are an important means of density estimation, but...
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Outcome regression-based estimation of conditional average treatment effect
The research is about a systematic investigation on the following issues. First, we construct different outcome regression-based estimators for...
