Kernel conditional density and mode estimation for psi-weakly dependent observations

2021 ◽  
pp. 1-27
Author(s):  
Soumia Rih ◽  
Abdelkader Tatachak
Keyword(s):  
Conditional Density ◽  
Mode Estimation ◽  
Dependent Observations ◽  
Weakly Dependent

BICKEL–ROSENBLATT TEST FOR WEAKLY DEPENDENT DATA

2012 ◽  
Vol 17 (3) ◽  
pp. 383-395 ◽  
Author(s):  
Janis Valeinis ◽  
Audris Locmelis
Keyword(s):  
Goodness Of Fit ◽  
Simulation Analysis ◽  
Dependent Data ◽  
Practical Implementation ◽  
Test Statistic ◽  
Goodness Of Fit Test ◽  
Dependent Observations ◽  
Simple Hypothesis ◽  
Weakly Dependent Data ◽  
Weakly Dependent

The aim of this paper is to analyze the Bickel–Rosenblatt test for simple hypothesis in case of weakly dependent data. Although the test has nice theoretical properties, it is not clear how to implement it in practice. Choosing different band-width sequences first we analyze percentage rejections of the test statistic under H0 by some empirical simulation analysis. This can serve as an approximate rule for choosing the bandwidth in case of simple hypothesis for practical implementation of the test. In the recent paper [12] a version of Neyman goodness-of-fit test was established for weakly dependent data in the case of simple hypotheses. In this paper we also aim to compare and discuss the applicability of these tests for both independent and dependent observations.

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