Results 131 to 140 of about 45,001 (165)

On a matrix‐valued autoregressive model

Journal of Time Series Analysis
Many data sets in biology, medicine, and other biostatistical areas deal with matrix‐valued time series. The case of a single univariate time series is very well developed in the literature; and single multi‐variate series (i.e., vector time series) though less well studied have also been developed.
S. Yaser Samadi, Lynne Billard
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Agent Learning and Autoregressive Modeling

2020 Information Theory and Applications Workshop (ITA), 2020
Relative entropy is used to investigate whether a sequence is memoryless or has memory and to discern the presence of any structure in the sequence. Particular emphasis is placed on obtaining expressions for finite sequence length N and autoregressive sequences with known and unknown autocorrelations.
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IDENTIFICATION IN MODELS WITH AUTOREGRESSIVE ERRORS

Journal of Econometrics, 1981
Abstract Consider the model A(L)x t =B(L)y t +C(L)z t =u t , t=1,…,T , where A(L)=(B(L):C(L)) is a matrix of polynomials in the lag operator so that L r x t =x t−r , and y t is a vector of n endogenous variables, B(L)= ∑ s=0 k B s L s B 0 I
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On the Autoregressive Model with Random Coefficients

Calcutta Statistical Association Bulletin, 1983
The first and second order stationarity conditions for an autore-gressive model with random coefficients are obtained. In addition, for such a type of model, the asymptotic mean squared error of an h-step ahead forecast is also considered.
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NON‐NEGATIVE AUTOREGRESSIVE MODELS

Journal of Time Series Analysis, 1992
Abstract. Consider a stationary non‐negative autoregressive (AR) model given xt=b1xt‐1, +…+bpxt‐p+et, where the et are independent identically distributed non‐negative variables and b1, …, bp are non‐negative parameters, and all the roots of the equation 1 –b1u–…–bpup= 0 are outside the unit circle.
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Testing Normality in Autoregressive Models

Biometrika, 1985
It is shown that any test of normality computed from autoregressive residuals has the same limiting null distribution as for the standard case of independent, identically distributed observations with estimated parameters. Some numerical results are given to indicate that this approximation is acceptable for sample size 20 in first- and second-order ...
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Missing Data in an Autoregressive Model

International Economic Review, 1974
Sargan, J D, Drettakis, E G
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Unbounded heteroscedasticity in autoregressive models

The Journal of Economic Asymmetries, 2023
Nikolaos Kourogenis, Nikitas Pittis, Panagiotis Samartzis   +2 more
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Random autoregressive models: A structured overview

Econometric Reviews, 2022
Marta Regis, Edwin R Van den Heuvel
exaly  

Autoregressive Modeling

SSRN Electronic Journal, 2013
Fred Viole, David N. Nawrocki
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