loglikelihood_normal: Calculate the log likelihood for a normally distributed...
In jbryer/visualMLE: Visual Maximum Likelihood Estimation
Description
Usage
Arguments
Value
View source: R/likelihood_normal.R
Description
Calculate the log likelihood for a normally distributed dependent variable.
Usage
1
loglikelihood_normal(parameters, predictor, outcome)
Arguments
parameters
the regression parameters. Element one is the intercept,
element two is the slope, and element three is the error (root mean
square error).
predictor
vector of predictors.
outcome
vector of outcomes.
Value
the log likelihood.
jbryer/visualMLE documentation built on Nov. 22, 2021, 12:18 a.m.
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Description Usage Arguments Value
View source: R/likelihood_normal.R
Description
Calculate the log likelihood for a normally distributed dependent variable.
Usage
1 | loglikelihood_normal(parameters, predictor, outcome)
|
Arguments
parameters |
the regression parameters. Element one is the intercept, element two is the slope, and element three is the error (root mean square error). |
predictor |
vector of predictors. |
outcome |
vector of outcomes. |
Value
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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