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A modified signed likelihood ratio test in elliptical structural models
(SPRINGER, 2010)
In this paper we deal with the issue of performing accurate testing inference on a scalar parameter of interest in structural errors-in-variables models. The error terms are allowed to follow a multivariate distribution ...
INFERENCE FOR EIGENVALUES AND EIGENVECTORS OF GAUSSIAN SYMMETRIC MATRICES
(INST MATHEMATICAL STATISTICS, 2008)
This article presents maximum likelihood estimators (MLEs) and log-likelihood ratio (LLR) tests for the eigenvalues and eigenvectors of Gaussian random symmetric matrices of arbitrary dimension, where the observations are ...
Statistical Inference for the Weibull Distribution Based on delta-Record Data
(MDPI, 2020)
We consider the maximum likelihood and Bayesian estimation of parameters and prediction of future records of the Weibull distribution from delta-record data, which consists of records and near-records. We discuss existence, ...
A matrix formula for the skewness of maximum likelihood estimators
(ELSEVIER SCIENCE BV, 2011)
We give a general matrix formula for computing the second-order skewness of maximum likelihood estimators. The formula was firstly presented in a tensorial version by Bowman and Shenton (1998). Our matrix formulation has ...
Inference for a skew extension of the Grubbs model
(SPRINGER, 2010)
In this paper, we discuss inferential aspects for the Grubbs model when the unknown quantity x (latent response) follows a skew-normal distribution, extending early results given in Arellano-Valle et al. (J Multivar Anal ...
New likelihoods for shape analysis
(World Scientific Publ Co Pte Ltd, 2015)
The beta Laplace distribution
(ELSEVIER SCIENCE BV, 2011)
The Laplace distribution is one of the earliest distributions in probability theory. For the first time, based on this distribution, we propose the so-called beta Laplace distribution, which extends the Laplace distribution. ...
Non-null Distribution of The Likelihood Ratio Statistic for Testing Multisample Compound Symmetry
(Universidad Industrial de Santander, Escuela de MatemáticasAnálisis MultivariadoBucaramanga, Colombia, 2022)
Transformed generalized linear models
(ELSEVIER SCIENCE BV, 2009)
The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models ...
Statistical Models for Small Area Estimation
(CIMAT, 2014)