Mlm: Multivariate Linear Model
In d-/MTS: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models
Mlm R Documentation
Multivariate Linear Model
Description
Fit a multivariate multiple linear regression model via the least
squares method
Usage
Mlm(y, z, constant=TRUE, output=TRUE)
Arguments
y
data matrix of dependent variable. Each column contains one
variable.
z
data matrix of the explanatory variables. Each column contains one
variable.
constant
A logical switch for including the constant term
output
A logical switch to print the output
Value
beta
coefficient matrix
se.beta
standard errors of the coefficient matrix
residuals
The residual series
sigma
Residual covariance matrix
Author(s)
Ruey S. Tsay
d-/MTS documentation built on June 12, 2022, 12:50 a.m.
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| Mlm | R Documentation |
Multivariate Linear Model
Description
Fit a multivariate multiple linear regression model via the least squares method
Usage
Mlm(y, z, constant=TRUE, output=TRUE)
Arguments
y |
data matrix of dependent variable. Each column contains one variable. |
z |
data matrix of the explanatory variables. Each column contains one variable. |
constant |
A logical switch for including the constant term |
output |
A logical switch to print the output |
Value
beta |
coefficient matrix |
se.beta |
standard errors of the coefficient matrix |
residuals |
The residual series |
sigma |
Residual covariance matrix |
Author(s)
Ruey S. Tsay
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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