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Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises
by
Liu, Xiao-hui
, Zhang, Han-jun
, Deng, Zi-wei
, Zhu, En-wen
, Cao, Jun
in
Applications of Mathematics
/ Asymptotic properties
/ Autoregressive models
/ Data science
/ Economics
/ Math Applications in Computer Science
/ Mathematical and Computational Physics
/ Mathematics
/ Mathematics and Statistics
/ Normality
/ Random variables
/ Regression analysis
/ Social sciences
/ Theoretical
/ Time series
/ Variance
2024
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Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises
by
Liu, Xiao-hui
, Zhang, Han-jun
, Deng, Zi-wei
, Zhu, En-wen
, Cao, Jun
in
Applications of Mathematics
/ Asymptotic properties
/ Autoregressive models
/ Data science
/ Economics
/ Math Applications in Computer Science
/ Mathematical and Computational Physics
/ Mathematics
/ Mathematics and Statistics
/ Normality
/ Random variables
/ Regression analysis
/ Social sciences
/ Theoretical
/ Time series
/ Variance
2024
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Do you wish to request the book?
Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises
by
Liu, Xiao-hui
, Zhang, Han-jun
, Deng, Zi-wei
, Zhu, En-wen
, Cao, Jun
in
Applications of Mathematics
/ Asymptotic properties
/ Autoregressive models
/ Data science
/ Economics
/ Math Applications in Computer Science
/ Mathematical and Computational Physics
/ Mathematics
/ Mathematics and Statistics
/ Normality
/ Random variables
/ Regression analysis
/ Social sciences
/ Theoretical
/ Time series
/ Variance
2024
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Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises
Journal Article
Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises
2024
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Overview
This paper considers the random coefficient autoregressive model with time-functional variance noises, hereafter the RCA-TFV model. We first establish the consistency and asymptotic normality of the conditional least squares estimator for the constant coefficient. The semiparametric least squares estimator for the variance of the random coefficient and the nonparametric estimator for the variance function are constructed, and their asymptotic results are reported. A simulation study is presented along with an analysis of real data to assess the performance of our method in finite samples.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
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