Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Alberto Contreras-Cristán"'
Publikováno v:
Entropy, Vol 23, Iss 3, p 318 (2021)
Statistical methods to produce inferences based on samples from finite populations have been available for at least 70 years. Topics such as Survey Sampling and Sampling Theory have become part of the mainstream of the statistical methodology. A wide
Externí odkaz:
https://doaj.org/article/04316a81f1214fb89e0dad7257912c8f
Publikováno v:
Miscelánea Matemática de la Sociedad Matemática Mexicana. 73
Publikováno v:
Canadian Journal of Statistics. 47:560-579
Priors are introduced into goodness‐of‐fit tests, both for unknown parameters in the tested distribution and on the alternative density. Neyman–Pearson theory leads to the test with the highest expected power. To make the test practical, we see
Publikováno v:
Entropy, Vol 23, Iss 318, p 318 (2021)
Entropy
Volume 23
Issue 3
Entropy
Volume 23
Issue 3
Statistical methods to produce inferences based on samples from finite populations have been available for at least 70 years. Topics such as Survey Sampling and Sampling Theory have become part of the mainstream of the statistical methodology. A wide
Autor:
Eduardo Gutiérrez-Peña, Alberto Contreras-Cristán, Gabriel Núñez-Antonio, Manuel Mendoza, Eduardo Mendoza
Publikováno v:
Environmental and Ecological Statistics. 25:471-494
The study of the interaction among species is an active area of research in Ecology. In particular, it is of interest to evaluate the overlap of their ecological niches. Temporal activity is one of the niche’s axes most commonly used to explore eco
On the asymptotic power of a goodness-of-fit test based on a cumulative Kullback–Leibler discrepancy
Publikováno v:
Statistics & Probability Letters. 120:118-125
We discuss a goodness-of-fit test arising from information-theoretical considerations. We show that, for a simple null hypothesis, our test has superior asymptotic power compared to the Anderson–Darling test when the alternative lies in a certain l
Publikováno v:
Communications in Statistics - Theory and Methods. 39:2241-2263
In this article, several methods to make inferences about the parameters of a finite mixture of distributions in the context of centrally censored data with partial identification are revised. These methods are an adaptation of the work in Contreras-
Publikováno v:
Communications in Statistics - Simulation and Computation. 38:1856-1869
In this article, we propose a nonparametric method to test for symmetry in bivariate data. By using the extension of Fisher's exact treatment for 2 × 2 contingency tables proposed by Freeman and Halton (1951), we can test the hypothesis of equal dis
Publikováno v:
Computational Statistics & Data Analysis. 53:4255-4265
In this paper we propose objective Bayes procedures for model selection. To this end, we follow Gutierrez-Pena and Walker [Gutierrez-Pena, E., Walker, S.G., 2005. Statistical decision problems and Bayesian nonparametric methods. International Statist
Publikováno v:
Statistics. 43:227-240
We explore a method for constructing first-order stationary autoregressive-type models with given marginal distributions. We impose the underlying dependence structure in the model using Bayesian non-parametric predictive distributions. This approach