View source: R/bothsidesmodel.chisquare.R
| bothsidesmodel.chisquare | R Documentation |
\beta are zeroTests the null hypothesis that an arbitrary subset of the \beta _{ij}'s
is zero, based on the least squares estimates, using the \chi^2 test as
in Section 7.1. The null and alternative are specified by pattern matrices
P_0 and P_A, respectively. If the P_A is omitted, then the
alternative will be taken to be the unrestricted model.
bothsidesmodel.chisquare(
x,
y,
z,
pattern0,
patternA = matrix(1, nrow = ncol(x), ncol = ncol(z))
)
x |
An |
y |
The |
z |
A |
pattern0 |
An |
patternA |
An optional |
A 'list' with the following components:
The vector of estimated parameters of interest.
The estimated covariance matrix of the estimated parameter vector.
The degrees of freedom in the test.
T^2 statistic in (7.4).
The p-value for the test.
bothsidesmodel, bothsidesmodel.df,
bothsidesmodel.hotelling, bothsidesmodel.lrt,
and bothsidesmodel.mle.
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