Gaussian and non-Gaussian limit distributions of estimates of the regression coefficients of a long-memory time series

1999 ◽  
Vol 51 (7) ◽  
pp. 1044-1054 ◽  
Author(s):  
M. M. Leonenko ◽  
M. M. Sharapov
Keyword(s):  
Time Series ◽  
Long Memory ◽  
Regression Coefficients ◽  
Limit Distributions ◽  
Memory Time ◽  
Non Gaussian

scholarly journals On nonparametric regression for bivariate circular long-memory time series

2021 ◽  
Author(s):  
Jan Beran ◽  
Britta Steffens ◽  
Sucharita Ghosh
Keyword(s):  
Time Series ◽  
Nonparametric Regression ◽  
Long Range ◽  
Long Memory ◽  
Regression Function ◽  
Confidence Bands ◽  
Long Range Dependence ◽  
Asymptotic Results ◽  
Memory Time ◽  
Circular Time Series

AbstractWe consider nonparametric regression for bivariate circular time series with long-range dependence. Asymptotic results for circular Nadaraya–Watson estimators are derived. Due to long-range dependence, a range of asymptotically optimal bandwidths can be found where the asymptotic rate of convergence does not depend on the bandwidth. The result can be used for obtaining simple confidence bands for the regression function. The method is illustrated by an application to wind direction data.

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