Minimum density power divergence estimator for negative binomial integer-valued GARCH models
L Xiong, F Zhu - Communications in Mathematics and Statistics, 2022 - Springer
In this paper, we study a robust estimation method for the observation-driven integer-valued
time-series models in which the conditional probability mass of current observations is …
time-series models in which the conditional probability mass of current observations is …
Conditional minimum density power divergence estimator for self-exciting integer-valued threshold autoregressive models
M Sun, K Yang, A Li - TEST, 2024 - Springer
To overcome the sensitivity of maximum likelihood estimation to outliers in integer-valued
time series of counts, we develop a conditional version of minimum density power …
time series of counts, we develop a conditional version of minimum density power …
Improving the efficiency of robust estimators for the generalized linear model
A Marazzi - Stats, 2021 - mdpi.com
The distance constrained maximum likelihood procedure (DCML) optimally combines a
robust estimator with the maximum likelihood estimator with the purpose of improving its …
robust estimator with the maximum likelihood estimator with the purpose of improving its …
Robust Wald-type tests 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 …
stochastic covariates. We derive the properties of the minimum density power divergence …
Regresión robusta para composiciones con distribución Dirichlet generalizada.
M Fragalá - union-matematica.org.ar
El problema del análisis estadıstico de datos composicionales sigue siendo una fuente de
preocupación desde que en 1897 Karl Pearson pusiera de manifiesto la inadecuación de …
preocupación desde que en 1897 Karl Pearson pusiera de manifiesto la inadecuación de …