Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator [PDF]
In this paper, a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator.
Elena Castilla +3 more
doaj +9 more sources
Monitoring Parameter Change for Time Series Models of Counts Based on Minimum Density Power Divergence Estimator [PDF]
In this study, we consider an online monitoring procedure to detect a parameter change for integer-valued generalized autoregressive heteroscedastic (INGARCH) models whose conditional density of present observations over past information follows one ...
Sangyeol Lee, Dongwon Kim
doaj +6 more sources
Robust small area estimation for unit level model with density power divergence. [PDF]
Unit level model is one of the classical models in small area estimation, which plays an important role with unit information data. Empirical Bayesian(EB) estimation, as the optimal estimation under normal assumption, is the most commonly used parameter ...
Xijuan Niu, Zhiqiang Pang, Zhaoxu Wang
doaj +3 more sources
Robust Wald-type tests for non-homogeneous observations based on the minimum density power divergence estimator [PDF]
Pre-print, Under ...
Ayanendranath Basu +3 more
semanticscholar +7 more sources
Extreme Precipitation Frequency Analysis Using a Minimum Density Power Divergence Estimator [PDF]
The recently observed hydrologic extremes are unlike what has been experienced so far. Both the magnitude and frequency of extremes are important indicators that determine the flood safety design criteria. Therefore, how are design criteria updated faced with these extremes?
Yongwon Seo, Junshik Hwang, Byungsoo Kim
semanticscholar +5 more sources
An asymptotically unbiased minimum density power divergence estimator for the Pareto-tail index
We introduce a robust and asymptotically unbiased estimator for the tail index of Pareto-type distributions. The estimator is obtained by fitting the extended Pareto distribution to the relative excesses over a high threshold with the minimum density power divergence criterion.
Dierckx, Goedele +2 more
semanticscholar +5 more sources
Restricted Distance-Type Gaussian Estimators Based on Density Power Divergence and Their Applications in Hypothesis Testing [PDF]
In this paper, we introduce the restricted minimum density power divergence Gaussian estimator (MDPDGE) and study its main asymptotic properties. In addition, we examine it robustness through its influence function analysis.
Ángel Felipe +3 more
doaj +2 more sources
The Minimum Squared Distance Estimator and the Minimum Density Power Divergence Estimator [PDF]
Abstract Basu et al. (1998) proposed the minimum divergence estimating method which is free from using the painfulkernel density estimator. Their proposed class of density power divergences is indexed by a single parameter which controls the trade-o between robustness and eciency.
Saraceno, Giovanni +3 more
semanticscholar +4 more sources
Robust estimation of fixed effect parameters and variances of linear mixed models: the minimum density power divergence approach [PDF]
AbstractMany real-life data sets can be analyzed using linear mixed models (LMMs). Since these are ordinarily based on normality assumptions, under small deviations from the model the inference can be highly unstable when the associated parameters are estimated by classical methods.
Saraceno, Giovanni +3 more
openaire +3 more sources
In this study, we consider the problem of testing for a parameter change in general integer-valued time series models whose conditional distribution belongs to the one-parameter exponential family when the data are contaminated by outliers. In particular,
Byungsoo Kim, Sangyeol Lee
doaj +2 more sources

