log_likelihood: Compute the log-likelihood for the model at a given parameter...
In awstringer1/casecrossover: Approximate Bayesian Inference for Case Crossover Models
Description
Usage
Arguments
Value
View source: R/02-likelihood.R
Description
Compute the model log-likelihood for a given set of parameters.
Usage
1
log_likelihood(W, model_data)
Arguments
W
Parameter vector. First n elements are eta, then Gamma and beta.
model_data
A list of class "cc_modeldata" as returned by model_setup().
Value
A number, the log-likelihood.
awstringer1/casecrossover documentation built on March 11, 2021, 4:41 a.m.
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Description Usage Arguments Value
View source: R/02-likelihood.R
Description
Compute the model log-likelihood for a given set of parameters.
Usage
1 | log_likelihood(W, model_data)
|
Arguments
W |
Parameter vector. First n elements are eta, then Gamma and beta. |
model_data |
A list of class "cc_modeldata" as returned by model_setup(). |
Value
A number, the log-likelihood.
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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