carx: an R Package to Estimate Censored Autoregressive Time Series with Exogenous Covariates

The R Journal ◽

10.32614/rj-2017-064 ◽

2017 ◽

Vol 9 (2) ◽

pp. 213 ◽

Author(s):

Chao Wang ◽

Kung-Sik Chan

Keyword(s):

Time Series ◽

R Package ◽

Autoregressive Time Series

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Reversed Residuals in Autoregressive Time Series Analysis

10.21236/ada222711 ◽

1990 ◽

Author(s):

Peter A. Lewis ◽

A. J. Lawrance

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Autoregressive Time Series ◽

Series Analysis

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On causal and noncausal cointegrated vector autoregressive time series

Journal of Time Series Analysis ◽

10.1111/jtsa.12607 ◽

2021 ◽

Author(s):

Anders Rygh Swensen

Keyword(s):

Time Series ◽

Autoregressive Time Series ◽

Vector Autoregressive

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Priors and component structures in autoregressive time series models

Journal of the Royal Statistical Society Series B (Statistical Methodology) ◽

10.1111/1467-9868.00208 ◽

1999 ◽

Vol 61 (4) ◽

pp. 881-899 ◽

Author(s):

G. Huerta ◽

M. West

Keyword(s):

Time Series ◽

Time Series Models ◽

Autoregressive Time Series

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Image Segmentation by Autoregressive Time Series Model

Image Segmentation ◽

10.5772/15570 ◽

2011 ◽

Author(s):

Pei-Gee Peter

Keyword(s):

Time Series ◽

Image Segmentation ◽

Time Series Model ◽

Autoregressive Time Series

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Modeling a nonlinear process using the exponential autoregressive time series model

Nonlinear Dynamics ◽

10.1007/s11071-018-4677-0 ◽

2018 ◽

Vol 95 (3) ◽

pp. 2079-2092 ◽

Author(s):

Huan Xu ◽

Feng Ding ◽

Erfu Yang

Keyword(s):

Time Series ◽

Nonlinear Process ◽

Time Series Model ◽

Autoregressive Time Series

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Statistical Estimation of Parameters for Binary Conditionally Nonlinear Autoregressive Time Series

Mathematical Methods of Statistics ◽

10.3103/s1066530718020023 ◽

2018 ◽

Vol 27 (2) ◽

pp. 103-118 ◽

Author(s):

Yu. S. Kharin ◽

V. A. Voloshko ◽

E. A. Medved

Keyword(s):

Time Series ◽

Statistical Estimation ◽

Estimation Of Parameters ◽

Autoregressive Time Series ◽

Nonlinear Autoregressive

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tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models

Journal of Statistical Software ◽

10.18637/jss.v082.i05 ◽

2017 ◽

Vol 82 (5) ◽

Author(s):

Tobias Liboschik ◽

Konstantinos Fokianos ◽

Roland Fried

Keyword(s):

Time Series ◽

Generalized Linear Models ◽

Linear Models ◽

R Package ◽

Count Time Series

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Modelling nonlinear random vibrations using an amplitude-dependent autoregressive time series model

10.1093/biomet/68.1.189 ◽

1981 ◽

Vol 68 (1) ◽

pp. 189-196 ◽

Author(s):

V HAGGAN ◽

T. OZAKI

Keyword(s):

Time Series ◽

Time Series Model ◽

Random Vibrations ◽

Autoregressive Time Series

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A robust regression model for a first-order autoregressive time series with unequal spacing: application to water monitoring

Journal of the Royal Statistical Society Series C (Applied Statistics) ◽

10.1111/j.1467-9876.2005.05511.x ◽

2005 ◽

Vol 54 (4) ◽

pp. 769-780 ◽

Author(s):

E. Andres Houseman

Keyword(s):

Time Series ◽

Regression Model ◽

Robust Regression ◽

Water Monitoring ◽

Autoregressive Time Series ◽

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Multiple change point detection and validation in autoregressive time series data

Statistical Papers ◽

10.1007/s00362-020-01198-w ◽

2020 ◽

Vol 61 (4) ◽

pp. 1507-1528 ◽

Author(s):

Lijing Ma ◽

Andrew J. Grant ◽

Georgy Sofronov

Keyword(s):

Time Series ◽

Change Point ◽

Time Series Data ◽

Change Point Detection ◽

Series Data ◽

Autoregressive Time Series ◽

Point Detection

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