Title :
A statistical inference method for a subset of long-range dependent FARIMA processes
Author :
Mossberg, Magnus
Author_Institution :
Dept. of Phys. & Electr. Eng., Karlstad Univ., Karlstad, Sweden
Abstract :
A subset of long-range dependent FARIMA processes is considered. A method for estimating the parameter that describes the long-range dependency of such a process is suggested. The method is based on an asymptotic expression for the covariance function of the process and gives a closed form solution by means of a weighted linear least squares estimate. The variance of the estimate given by themethod is analyzed and, at the same time, the optimal choice of the weighting is expressed. A numerical illustration of the method and the material in the paper is provided.
Keywords :
autoregressive moving average processes; least squares approximations; statistical analysis; asymptotic expression; covariance function; fractional autoregressive integrated moving average process; long-range dependent FARIMA processes subset; numerical illustration; statistical inference method; weighted linear least squares estimate; Covariance matrix; Equations; Estimation; Least squares approximation; Monte Carlo methods; Reactive power; Estimation; FARIMA process; long-range dependency;
Conference_Titel :
Statistical Signal Processing Workshop (SSP), 2012 IEEE
Conference_Location :
Ann Arbor, MI
Print_ISBN :
978-1-4673-0182-4
Electronic_ISBN :
pending
DOI :
10.1109/SSP.2012.6319730
