Function reference • likelihood.model

All functions
`assumptions()`	Retrieve the assumptions the likelihood model makes about the data.
`assumptions(<likelihood_contr_model>)`	Retrieve the assumptions in the likelihood contributions model.
`assumptions(<likelihood_exact_weibull>)`	List the assumptions made by the model.
`assumptions(<likelihood_name_model>)`	List the assumptions made by the model.
`dof()`	Generic method for extracting the degrees of freedom from a hypothesis test
`fim()`	Fisher information matrix method
`fit(<likelihood_model>)`	Default MLE solver for subclasses of `likelihood_model`.
`hess_loglik()`	Hessian of log-likelihood method
`hess_loglik(<likelihood_contr_model>)`	Hessian of log-likelihood method for likelihood_contr_model
`hess_loglik(<likelihood_exact_weibull>)`	Hessian of the log-likelihood function generator for the weibull likelihood model.
`hess_loglik(<likelihood_model>)`	Default method to compute the hessian of the log-likelihood.
`hypothesis_test()`	Hypothesis test structure
`is_likelihood_model()`	Likelihood model
`likelihood_contr_model`	Likelihood_contr_model
`likelihood_exact_weibull()`	Exact Weibull likelihood model
`likelihood_name()`	This is a likelihood model generator based on the convention used in R, where we have a name for a distribution, like `normal`, `weibull`, `exp`, etc. and then we have a set of functions that are named `p<name>`, `d<name>`, `q<name>`, `r<name>`, etc., where the first letter is the first letter of the distribution name. For instance, for the normal distribution, we have `pnorm`, `dnorm`, `qnorm`, `rnorm`, respectively for the cdf, pdf, quantile function, and random variate generator.
`loglik()`	Log-likelihood method
`loglik(<likelihood_contr_model>)`	Log-likelihood method for likelihood_contr_model
`loglik(<likelihood_exact_weibull>)`	Log-likelihood function generator for the exact Weibull likelihood model.
`loglik(<likelihood_name_model>)`	Log-likelihood function generator for the named likelihood model.
`lrt()`	Likelihood ratio test
`pval()`	Generic method for extracting the p-value from a hypothesis test
`pval(<hypothesis_test>)`	p-value method for hypothesis tests
`sampler(<likelihood_model>)`	Estimate the sampling distribution of the MLE for a likelihood model.
`score()`	Score method
`score(<likelihood_contr_model>)`	Score method for likelihood_contr_model
`score(<likelihood_exact_weibull>)`	Score function generator for the exact Weibull likelihood model.
`score(<likelihood_model>)`	Default score method

Reference

All functions