ldmvnorm: Log Multivariate Normal Density
In sbgcop: Semiparametric Bayesian Gaussian Copula Estimation and Imputation
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
Computes the log of the multivariate normal density
Usage
1
ldmvnorm(Y, S)
Arguments
Y
an n x p matrix
S
a p x p positive definite matrix
Details
This function computes the log density of the data matrix Y under the
model that the rows are independent samples from a mean-zero multivariate
normal distribution with covariance matrix S.
Value
A real number.
Author(s)
Peter Hoff
Examples
1
2
sbgcop documentation built on May 2, 2019, 9:48 a.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
Computes the log of the multivariate normal density
Usage
1 | ldmvnorm(Y, S)
|
Arguments
Y |
an n x p matrix |
S |
a p x p positive definite matrix |
Details
This function computes the log density of the data matrix Y under the
model that the rows are independent samples from a mean-zero multivariate
normal distribution with covariance matrix S.
Value
A real number.
Author(s)
Peter Hoff
Examples
1 2 |
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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