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Asymptotically Normal Estimators for Zipf’s Law
We study an infinite urn scheme with probabilities corresponding to a power function. Urns here represent words from an infinitely large vocabulary....
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Multiple Categorical Covariates-Based Multinomial Dynamic Response Model
Regression models for multinomial responses with time dependent covariates have been studied recently both in longitudinal and time series setup. For...
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Asymptotic Theory for Longitudinal Data with Missing Responses Adjusted by Inverse Probability Weights
In this article, we propose a new method for analyzing longitudinal data which contain responses that are missing at random. This method consists in...
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A New Look at the Models for Ordinal Categorical Data Analysis
The multinomial/categorical responses, whether they are nominal or ordinal, are recorded in counts under all categories/cells involved. The analysis...
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Inferences in Binary Dynamic Fixed Models in a Semi-parametric Setup
In a longitudinal setup, the so-called generalized estimating equations approach was a popular inference technique to obtain efficient regression...
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Generalised least squares estimation of regularly varying space-time processes based on flexible observation schemes
Regularly varying stochastic processes model extreme dependence between process values at different locations and/or time points. For such stationary...
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Estimators of the Parameters of Beta Distribution
The iteration algorithm of computation of effective estimators of the shape parameters of beta distributions using the unbiased estimators of the end...
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Semi-parametric Dynamic Models for Longitudinal Ordinal Categorical Data
The over all regression function in a semi-parametric model involves a partly specified regression function in some primary covariates and a...
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A Variant of AIC Based on the Bayesian Marginal Likelihood
We propose information criteria that measure the prediction risk of a predictive density based on the Bayesian marginal likelihood from a frequentist...
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A Parameter Dimension-Split Based Asymptotic Regression Estimation Theory for a Multinomial Panel Data Model
In this paper we revisit the so-called non-stationary regression models for repeated categorical/multinomial data collected from a large number of...
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Statistical inference for the unbalanced two-way error component regression model with errors-in-variables
In this paper, we investigate the estimation and testing problems of unbalanced two-way error component regression model with errors-in-variables....
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A supermartingale argument for characterizing the functional Hill process weak law for small parameters
The paper deals with the asymptotic laws of functionals of standard exponential random variables. These classes of statistics are closely related to...
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Distribution-free inference in record series
Let { X t , t = 1} be a time series. A (upper) record is a value X j such that X j > max{ X 1 ,…, X j -1 }. Some popular models in record theory are the...
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Asymptotic behavior of truncated stochastic approximation procedures
We study asymptotic behavior of stochastic approximation procedures with three main characteristics: truncations with random moving bounds, a...
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Adaptive fused LASSO in grouped quantile regression
This article considers the quantile model with grouped explanatory variables. In order to have the sparsity of the parameter groups but also the...
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Rate of convergence of truncated stochastic approximation procedures with moving bounds
The paper is concerned with stochastic approximation procedures having three main characteristics: truncations with random moving bounds, a...
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Semi-Parametric Models for Negative Binomial Panel Data
This paper considers a semi-parametric model for longitudinal negative binomial counts under the assumption that the repeated count responses follow...
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Least squares estimator for non-ergodic Ornstein-Uhlenbeck processes driven by Gaussian processes
The statistical analysis for equations driven by fractional Gaussian process (fGp) is relatively recent. The development of stochastic calculus with...
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Anisotropic Brown-Resnick space-time processes: estimation and model assessment
Spatially isotropic max-stable processes have been used to model extreme spatial or space-time observations. One prominent model is the Brown-Resnick...
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Bivariate zero truncated Poisson INAR(1) process
In this paper, we propose a new stationary bivariate first order integer-valued autoregressive (BINAR(1)) process with zero truncated Poisson...