marlsq | R Documentation |
Fit a multivariate AR model by least squares method.
marlsq(y, lag = NULL)
y |
a multivariate time series. |
lag |
highest AR order. Default is |
An object of class "marlsq"
, which is a list with the following
components:
maice.order |
order of the MAICE model. |
aic |
AIC of the MAR model with minimum AIC orders. |
v |
innovation covariance matrix. |
arcoef |
AR coefficient matrices. |
Kitagawa, G. (2020) Introduction to Time Series Modeling with Applications in R. Chapman & Hall/CRC.
# Yaw rate, rolling, pitching and rudder angle of a ship
data(HAKUSAN)
y <- as.matrix(HAKUSAN[, c(1,2,4)]) # Yaw rate, Rolling, Rudder angle
z <- marlsq(y)
z
marspc(z$arcoef, v = z$v)
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