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A Time‐Domain Semi‐parametric Estimate for Strongly Dependent Continuous‐Time Stationary Processes
Author(s) -
Kato Takeshi,
Masry Elias
Publication year - 2003
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2003.00329.x
Subject(s) - mathematics , estimator , asymptotic distribution , consistency (knowledge bases) , covariance , strong consistency , parametric statistics , time domain , normality , mathematical proof , statistics , discrete mathematics , computer science , geometry , computer vision
. A covariance‐based estimator of the memory parameter of strongly dependent continuous‐time stationary processes is proposed. The consistency and asymptotic normality of the estimator are established. All assumptions, the form of the estimator, and the proofs are made in time‐domain only.