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pro vyhledávání: '"Martín, Nirian"'
Autor:
Martin, Nirian
In Econometrics, the Breusch-Pagan test-statistic has become an iconic application of the Lagrange multipliers (LM) test. We shall introduce beta-score LM tests for heteroscedasticity in linear regression models, which trades-off the degree of robust
Externí odkaz:
http://arxiv.org/abs/2301.07245
Since the two seminal papers by Fisher (1915, 1921) were published, the test under a fixed value correlation coefficient null hypothesis for the bivariate normal distribution constitutes an important statistical problem. In the framework of asymptoti
Externí odkaz:
http://arxiv.org/abs/2202.00982
Autor:
Martín, Nirian
Even though the Rao's score tests are classical tests, such as the likelihood ratio tests, their application has been avoided until now in a multivariate framework, in particular high-dimensional setting. We consider they could play an important role
Externí odkaz:
http://arxiv.org/abs/2012.14238
This paper presents new families of Rao-type test statistics based on the minimum density power divergence estimators which provide robust generalizations for testing simple and composite null hypotheses. The asymptotic null distributions of the prop
Externí odkaz:
http://arxiv.org/abs/1908.09794
Analyzing polytomous response from a complex survey scheme, like stratified or cluster sampling is very crucial in several socio-economics applications. We present a class of minimum quasi weighted density power divergence estimators for the polytomo
Externí odkaz:
http://arxiv.org/abs/1904.02219
The log-normal distribution is one of the most common distributions used for modeling skewed and positive data. It frequently arises in many disciplines of science, specially in the biological and medical sciences. The statistical analysis for compar
Externí odkaz:
http://arxiv.org/abs/1804.10950
Robust Wald-type test in GLM with random design based on minimum density power divergence estimators
We consider the problem of robust inference under the generalized linear model (GLM) with stochastic covariates. We derive the properties of the minimum density power divergence estimator of the parameters in GLM with random design and use this estim
Externí odkaz:
http://arxiv.org/abs/1804.00160
Publikováno v:
Metrika (2018) 81: 493
This paper considers the problem of robust hypothesis testing under non-identically distributed data. We propose Wald-type tests for both simple and composite hypothesis for independent but non-homogeneous observations based on the robust minimum den
Externí odkaz:
http://arxiv.org/abs/1707.02333
Publikováno v:
The International Journal of Biostatistics (2018)
Parametric hypothesis testing associated with two independent samples arises frequently in several applications in biology, medical sciences, epidemiology, reliability and many more. In this paper, we propose robust Wald-type tests for testing such t
Externí odkaz:
http://arxiv.org/abs/1702.04552
A new family of minimum distance estimators for binary logistic regression models based on $\phi$-divergence measures is introduced. The so called "pseudo minimum phi-divergence estimator"(PM$\phi$E) family is presented as an extension of "minimum ph
Externí odkaz:
http://arxiv.org/abs/1611.02583