simpleVAR: Simple VAR estimation
In amvillegas/iMoMo: Mortality Improvement Rate Modelling
Description
Function to fit VAR mole of the form:
Δ^d y_t = C + ∑_{i=1}^p A_i Δ^d y_{t-i} + ε_t
where C is a K-dimensional vector of parameters and
A_1,...,A_p are K\times K matrices of autoregressive parampeters.
Usage
1
simpleVAR(y, p = 1, d = 0)
Arguments
y
a matrix containing the multivariate timeseries
p
Integer for the lag order (default is p=1)
d
Degree of differencing (default is d=0)
amvillegas/iMoMo documentation built on Sept. 18, 2020, 11:25 p.m.
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Description
Function to fit VAR mole of the form:
Δ^d y_t = C + ∑_{i=1}^p A_i Δ^d y_{t-i} + ε_t
where C is a K-dimensional vector of parameters and A_1,...,A_p are K\times K matrices of autoregressive parampeters.
Usage
1 | simpleVAR(y, p = 1, d = 0)
|
Arguments
y |
a matrix containing the multivariate timeseries |
p |
Integer for the lag order (default is p=1) |
d |
Degree of differencing (default is d=0) |
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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