Statistical inference for a heteroscedastic regression model with φ-mixing errors

2020 ◽  
pp. 1-19
Author(s):  
Liwang Ding ◽  
Ping Chen ◽  
Li Yongming
Keyword(s):  
Regression Model ◽  
Statistical Inference ◽  
Heteroscedastic Regression

Statistical inference for the functional quadratic quantile regression model

Metrika ◽  
2020 ◽  
Vol 83 (8) ◽  
pp. 937-960
Author(s):  
Gongming Shi ◽  
Tianfa Xie ◽  
Zhongzhan Zhang
Keyword(s):  
Quantile Regression ◽  
Regression Model ◽  
Statistical Inference ◽  
Quantile Regression Model

Estimation in a Heteroscedastic Regression Model

1968 ◽  
Vol 63 (322) ◽  
pp. 552 ◽  
Author(s):  
Herbert C. Rutemiller ◽  
David A. Bowers
Keyword(s):  
Regression Model ◽  
Heteroscedastic Regression

scholarly journals Generalized Odd Power Cauchy Family and Its Associated Heteroscedastic Regression Model

2021 ◽  
Vol 9 (3) ◽  
pp. 516-528
Author(s):  
Emrah Altun EA ◽  
Morad Alizadeh ◽  
Thiago Ramires ◽  
Edwin Ortega
Keyword(s):  
Monte Carlo ◽  
Regression Model ◽  
Data Structures ◽  
Generating Functions ◽  
Shape Parameter ◽  
Model Parameters ◽  
Data Sets ◽  
Complex Data ◽  
Linear Representations ◽  
Heteroscedastic Regression

This study introduces a generalization of the odd power Cauchy family by adding one more shape parameter togain more flexibility modeling the complex data structures. The linear representations for the density, moments, quantile,and generating functions are derived. The model parameters are estimated employing the maximum likelihood estimationmethod. The Monte Carlo simulations are performed under different parameter settings and sample sizes for the proposedmodels. In addition, we introduce a new heteroscedastic regression model based on the special member of the proposedfamily. Three data sets are analyzed with competitive and proposed models.

Estimation in a Heteroscedastic Regression Model

1968 ◽  
Vol 63 (322) ◽  
pp. 552-557 ◽  
Author(s):  
Herbert C. Rutemiller ◽  
David A. Bowers
Keyword(s):  
Regression Model ◽  
Heteroscedastic Regression
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