Results 351 to 360 of about 21,619,172 (379)

Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data

, 1998
This paper proposes a new statistical model for the analysis of data which arrive at irregular intervals. The model treats the time between events as a stochastic process and proposes a new class of point processes with dependent arrival rates.
R. Engle, Jeffrey R. Russell
semanticscholar   +1 more source

A Note on Autoregressive Modeling

Econometric Theory, 1994
This paper addresses the problem of estimating vector autoregressive models. An approach to handling nonstationary (integrated) time series is briefly discussed, but the main emphasis is upon the estimation of autoregressive approximations to stationary processes. Three alternative estimators are considered–the Yule-Walker, least-squares, and Burg-type
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Bootstrapping Threshold Autoregressive Models [PDF]

, 2002
Threshold autoregressive (TAR) models have been widely used for periodic time series, as they are nonlinear models relatively simple to handle being linear in different regions of the state space, see e.g. Tong (1990). One of the main problems regards the decision of the selection of the correct order of a TAR model.
OHRVIK J, SCHOIER, GABRIELLA
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REGRESSION, AUTOREGRESSION MODELS

Journal of Time Series Analysis, 1986
Abstract.The accuracy of least squares fitted regression autoregression models as approximations to more general stochastic structures is considered, attention being paid to the accuracy of the estimates of coefficients, of the innovations sequence and to the behaviour of the order (i.e., maximum lag) as determined by methods such as IAC, BIC.
L. Kavalieris, E. J. Hannan
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Improved autoregressive model

2002 International Zurich Seminar on Broadband Communications Access - Transmission - Networking (Cat. No.02TH8599), 2003
The autoregressive process has been used by several authors to model MPEG video traffic and attempts to capture the frame correlation as well as the Gaussian shape of the bit rate variation. However, the autoregressive process alone does not capture scene changes.
K. Ravindran, C. Amo-Quarm, M. Mezhoudi
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Likelihood-Based Inference in Cointegrated Vector Autoregressive Models

, 1996
This book gives a detailed mathematical and statistical analysis of the cointegrated vector autoregresive model. This model had gained popularity because it can at the same time capture the short-run dynamic properties as well as the long-run equilibrium
S. Johansen
semanticscholar   +1 more source

An adaptive autoregressive model

Computers & Industrial Engineering, 1985
Abstract A state space modeling approach for autoregressive integrated-moving average time series is presented. By means of the Kalman filter minimum-variance forecasts can be obtained in real time. The filter is able to recursively adjust its estimates similar to the exponential smoothing algorithms.
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Functional autoregressive model

2012
This chapter studies the functional autoregressive (FAR) process which has found many applications. The theory of autoregressive and more general linear processes in Hilbert and Banach spaces is developed in the monograph of Bosq (2000), on which Sections 13.1 and 13.2 are based.
Piotr Kokoszka, Lajos Horváth
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Least absolute deviations estimation for uncertain autoregressive model

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2020
Xiangfeng Yang, Gyei-Kark Park, Yancai Hu   +2 more
semanticscholar   +1 more source

Uncertain vector autoregressive model with imprecise observations

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2020
Han Tang
semanticscholar   +1 more source