MAR: A funtion to generate a multivariate autoregressive process...
In SNSeg: Self-Normalization(SN) Based Change-Point Estimation for Time Series
MAR R Documentation
A funtion to generate a multivariate autoregressive process (MAR) in time
series
Description
The function MAR is used for generating MAR model(s) for examples
of the functions SNSeg_Uni, SNSeg_Multi, and SNSeg_HD.
Usage
MAR(n, reptime, rho)
Arguments
n
the size (length) of time series to be generated
reptime
the number of time series to be generated
rho
value of autocorrelation
Value
Returns a matrix of the simulated MAR processes. The number of columns
of this matrix is equivalent to the value of input argument reptime, and
the number of rows is the value of input argument n.
Examples
MAR(n = 1000, reptime = 2, rho = -0.7)
SNSeg documentation built on June 22, 2024, 10:50 a.m.
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| MAR | R Documentation |
A funtion to generate a multivariate autoregressive process (MAR) in time series
Description
The function MAR is used for generating MAR model(s) for examples
of the functions SNSeg_Uni, SNSeg_Multi, and SNSeg_HD.
Usage
MAR(n, reptime, rho)
Arguments
n |
the size (length) of time series to be generated |
reptime |
the number of time series to be generated |
rho |
value of autocorrelation |
Value
Returns a matrix of the simulated MAR processes. The number of columns
of this matrix is equivalent to the value of input argument reptime, and
the number of rows is the value of input argument n.
Examples
MAR(n = 1000, reptime = 2, rho = -0.7)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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