dot-dinformation2-internal: Compute the First Derivative of the Expected Information...
In bozenne/lavaSearch2: Tools for Model Specification in the Latent Variable Framework
.dinformation2-internal R Documentation
Compute the First Derivative of the Expected Information Matrix
Description
Compute the first derivative of the expected information matrix.
Usage
.dInformation2(
dmu,
dOmega,
d2mu,
d2Omega,
OmegaM1,
missing.pattern,
unique.pattern,
name.pattern,
grid.3varD1,
grid.2meanD1.1varD1,
grid.2meanD2.1meanD1,
grid.2varD2.1varD1,
name.param,
leverage,
n.cluster,
weights
)
Details
calc_dinformation will perform the computation individually when the
argument index.Omega is not null.
bozenne/lavaSearch2 documentation built on Feb. 13, 2024, 10:18 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| .dinformation2-internal | R Documentation |
Compute the First Derivative of the Expected Information Matrix
Description
Compute the first derivative of the expected information matrix.
Usage
.dInformation2(
dmu,
dOmega,
d2mu,
d2Omega,
OmegaM1,
missing.pattern,
unique.pattern,
name.pattern,
grid.3varD1,
grid.2meanD1.1varD1,
grid.2meanD2.1meanD1,
grid.2varD2.1varD1,
name.param,
leverage,
n.cluster,
weights
)
Details
calc_dinformation will perform the computation individually when the
argument index.Omega is not null.
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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