scholarly journals A NONPARAMETRIC CONDITIONAL MODE ESTIMATE UNDER LTRC MODEL AND DEPENDENT DATA

2021 ◽  
Vol 133 (1) ◽  
pp. 43-80
Author(s):  
Chaib Yacine ◽  
Barouk Bachir ◽  
Amiri Omeran
Keyword(s):  
Dependent Data ◽  
Conditional Mode

Asymptotic normality of conditional mode estimation for functional dependent data

2020 ◽  
Vol 51 (2) ◽  
pp. 465-481
Author(s):  
Oussama Bouanani ◽  
Saâdia Rahmani ◽  
Ali Laksaci ◽  
Mustapha Rachdi
Keyword(s):  
Asymptotic Normality ◽  
Dependent Data ◽  
Mode Estimation ◽  
Conditional Mode ◽  
Conditional Mode Estimation

Time Dependent Data Mining in RAVEN

2016 ◽  
Author(s):  
Joshua Joseph Cogliati ◽  
Jun Chen ◽  
Japan Ketan Patel ◽  
Diego Mandelli ◽  
Daniel Patrick Maljovec ◽  
...  
Keyword(s):  
Data Mining ◽  
Time Dependent ◽  
Dependent Data

Asymptotic for LS estimators in the EV regression model for dependent errors

Filomat ◽  
2017 ◽  
Vol 31 (15) ◽  
pp. 4845-4856
Author(s):  
Konrad Furmańczyk
Keyword(s):  
Regression Model ◽  
Functional Dependence ◽  
Dependent Data ◽  
Errors In Variables ◽  
Mixing Conditions ◽  
Asymptotic Results ◽  
Dependence Measure ◽  
Wide Range ◽  
Ev Regression Model ◽  
Linear And Nonlinear

We study consistency and asymptotic normality of LS estimators in the EV (errors in variables) regression model under weak dependent errors that involve a wide range of linear and nonlinear time series. In our investigations we use a functional dependence measure of Wu [16]. Our results without mixing conditions complete the known asymptotic results for independent and dependent data obtained by Miao et al. [7]-[10].

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