getclf: Create likelihood function for multivariate data with missing...
In mvnmle: ML estimation for multivariate normal data with missing values.
Description
Usage
Arguments
Details
Value
References
See Also
Description
getclf returns a function proportional to twice the negative
log likelihood function for multivariate normal data with missing
values. This is a private function used in mlest.
Usage
1
Arguments
data
A data frame sorted so that records with identical
patterns of missingness are grouped together.
freq
An integer vector specifying the number of records in each
block of data with identical patterns of missingness.
Details
The argument of the returned function is the vector of parameters.
The parameterization is: mean vector first, followed
by the log of the diagonal elements of the inverse of the Cholesky
factor, and then the elements of the inverse of the Cholesky
factor above the main diagonal. These off-diagonal elements are
ordered by column (left to right), and then by row within column
(top to bottom).
Value
A function proportional to twice the negative log likelihood of the
parameters given the data.
References
Little, R. J. A., and Rubin, D. B. (1987) Statistical Analysis
with Missing Data. New York: Wiley.
See Also
mvnmle documentation built on May 29, 2017, 5:46 p.m.
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Description Usage Arguments Details Value References See Also
Description
getclf returns a function proportional to twice the negative
log likelihood function for multivariate normal data with missing
values. This is a private function used in mlest.
Usage
1 |
Arguments
data |
A data frame sorted so that records with identical patterns of missingness are grouped together. |
freq |
An integer vector specifying the number of records in each block of data with identical patterns of missingness. |
Details
The argument of the returned function is the vector of parameters. The parameterization is: mean vector first, followed by the log of the diagonal elements of the inverse of the Cholesky factor, and then the elements of the inverse of the Cholesky factor above the main diagonal. These off-diagonal elements are ordered by column (left to right), and then by row within column (top to bottom).
Value
A function proportional to twice the negative log likelihood of the parameters given the data.
References
Little, R. J. A., and Rubin, D. B. (1987) Statistical Analysis with Missing Data. New York: Wiley.
See Also
R Package Documentation
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