Yule-Walker type estimator of first-order time-varying periodic bilinear differential model for stochastic processes

This paper, studies the class of diffusion processes generated by a first-order continuous-time bilinear processes (COBL(1, 1)) with time-varying coefficients. So, we used the It formula approach for examining the structure of the process and its powers. In time-invariant case, an expression of the...

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Bibliographic Details
Published inCommunications in statistics. Theory and methods Vol. 49; no. 16; pp. 4046 - 4072
Main Authors Bibi, Abdelouahab, Merahi, Fateh
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 17.08.2020
Taylor & Francis Ltd
Subjects
Algorithms
Brownian motion
Computer simulation
Diffusion processes
Electricity consumption
Itô's formula
maximum likelihood estimates
Primary 40A05
Representations
Secondary 45G05
Stochastic processes
Yule-Walker estimates
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Summary:This paper, studies the class of diffusion processes generated by a first-order continuous-time bilinear processes (COBL(1, 1)) with time-varying coefficients. So, we used the It formula approach for examining the structure of the process and its powers. In time-invariant case, an expression of the moments of any order are given and the continuous autoregressive representation of such version is given, in particular the moments properties of some specifications are however derived. Based on these results we are able to examine the statistical properties as well as we develop an estimation method of the process via the so-called Yule-Walker (YW) type algorithm which relates with unknown parameters of CAR representation. The method is illustrated by a Monte Carlo study and applied to modeling the electricity consumption sampled at each 15 mn in Algeria.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2019.1594300