normal_ll: Gaussian log likelihood
In metropolis: The Metropolis Algorithm
Description
Usage
Arguments
Value
View source: R/loglikelihoods.R
Description
Gaussian log likelihood
Usage
1
Arguments
y
binary outcome
X
design matrix
par
vector of gaussian scale parameter followed by model coefficients
Value
a scalar quantity proportional to a normal likelihood
with linear parameterization, given y, X, and par
metropolis documentation built on Oct. 23, 2020, 7:42 p.m.
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Description Usage Arguments Value
View source: R/loglikelihoods.R
Description
Gaussian log likelihood
Usage
1 |
Arguments
y |
binary outcome |
X |
design matrix |
par |
vector of gaussian scale parameter followed by model coefficients |
Value
a scalar quantity proportional to a normal likelihood with linear parameterization, given y, X, and par
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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