estim_mar2_link: Fit of a mixture of two autoregressive models of order 1 to a...
In saidqasmi/KCC: Kriging for Climate Change (KCC)
estim_mar2_link R Documentation
Fit of a mixture of two autoregressive models of order 1 to a time series
Description
estim_mar2_link computes the parameters relative to the mixture of the
two autoregressive processes of order 1 (MAR, see equation 9 in Qasmi and
Ribes, 2021) to capture fast and slow components within a given time series.
Parameters are estimated by maximum likelihood via the optim function.
Usage
estim_mar2_link(y)
Arguments
y
a vector time series corresponding to an estimate of observed
internal variability.
Value
a vector containing the MAR1 parameters fitted to y.
var1_ar1 (var2_ar1) is the variance of the white noise
associated with the first (second) AR1. alpha1_ar1
(alpha2_ar1) is the coefficient at lag 1 associated with the first
(second) AR1.
saidqasmi/KCC documentation built on July 8, 2022, 6:02 a.m.
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| estim_mar2_link | R Documentation |
Fit of a mixture of two autoregressive models of order 1 to a time series
Description
estim_mar2_link computes the parameters relative to the mixture of the
two autoregressive processes of order 1 (MAR, see equation 9 in Qasmi and
Ribes, 2021) to capture fast and slow components within a given time series.
Parameters are estimated by maximum likelihood via the optim function.
Usage
estim_mar2_link(y)
Arguments
y |
a vector time series corresponding to an estimate of observed internal variability. |
Value
a vector containing the MAR1 parameters fitted to y.
var1_ar1 (var2_ar1) is the variance of the white noise
associated with the first (second) AR1. alpha1_ar1
(alpha2_ar1) is the coefficient at lag 1 associated with the first
(second) AR1.
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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