marlsq {TSSS} | 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 2*sqrt(n), where
n is the length of the time series |
An object of class "marlsq"
, which is a list with the following
elements:
maice.order |
order of the MAICE model. |
aic |
total AIC of the model. |
v |
innovation covariance matrix. |
arcoef |
AR coefficient matrices. |
Kitagawa, G. (2010) Introduction to Time Series Modeling. 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)