Sigma_mar2: Compute the covariance matrix corresponding to a mixture of...
In saidqasmi/KCC: Kriging for Climate Change (KCC)
Sigma_mar2 R Documentation
Compute the covariance matrix corresponding to a mixture of two
autoregressive (MAR) processes of order 1
Description
Sigma_mar2 takes the parameters returned by estim_mar2_link
(coefficient at lag 1 and variance) to calculate the matrix coefficients
whose formulation is given in equations 2 and 3 in Supplementary Material of
Qasmi and Ribes (2021).
Usage
Sigma_mar2(theta, y)
Arguments
theta
a vector containing the MAR parameters returned by
estim_mar2_link
y
a vector containing the observation time series associated with
theta
Value
a symmetric matrix corresponding to the MAR model.
saidqasmi/KCC documentation built on July 8, 2022, 6:02 a.m.
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| Sigma_mar2 | R Documentation |
Compute the covariance matrix corresponding to a mixture of two autoregressive (MAR) processes of order 1
Description
Sigma_mar2 takes the parameters returned by estim_mar2_link
(coefficient at lag 1 and variance) to calculate the matrix coefficients
whose formulation is given in equations 2 and 3 in Supplementary Material of
Qasmi and Ribes (2021).
Usage
Sigma_mar2(theta, y)
Arguments
theta |
a vector containing the MAR parameters returned by
|
y |
a vector containing the observation time series associated with
|
Value
a symmetric matrix corresponding to the MAR model.
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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