Function reference • rstap

All functions
`adapt_delta`	Target average acceptance probability
`as.matrix(<stapreg>)` `as.array(<stapreg>)` `as.data.frame(<stapreg>)`	Extract the posterior sample via matrix
`check_constant_vars()`	Check if any variables in a model frame are constants (the exception is that a constant variable of all 1's is allowed)
`example_model`	Example model
`get_stapless_formula()`	get_stapless_formula
`log_lik(<stapreg>)`	Pointwise log-likelihood matrix
`pairs(<stapreg>)`	Pairs method for stapreg objects
`plot(<stapreg>)`	Plot method for stapreg objects
`posterior_interval(<stapreg>)`	Posterior uncertainty intervals
`posterior_predict(<stapreg>)`	Draw from posterior predictive distribution
`predictive_error(<stapreg>)`	In-sample or out-of-sample predictive errors
`predictive_interval(<stapreg>)` `predictive_interval(<ppd>)`	Predictive intervals
`print(<stapreg>)`	Print method for stapreg objects
`prior_summary(<stapreg>)`	Summarize the priors used for an rstap model
`normal()` `student_t()` `cauchy()` `laplace()` `lasso()` `product_normal()` `exponential()` `log_normal()` `decov()`	Prior distributions and options
`rstap-datasets`	Datasets for rstap examples
`rstap-package`	The 'rstap' package.
`stap_data()`	Create a stap_data object
`stap_glm()` `stap_lm()`	Bayesian generalized spatial-temporal aggregated predictor(STAP) models via Stan
`stap_glm.fit()`	Fitting Generalized Linear STAP models
`stap_glmer()` `stap_lmer()` `stapdnd_lmer()`	Bayesian spatial-temporal generalized linear models with group-specific terms via Stan
`stap_termination()`	Spatial-Temporal Exposure Termination-Maximization Estimates
`stapdnd_glm()` `stapdnd_lm()`	Bayesian generalized spatial-temporal aggregated predictor(STAP) models via Stan
`stapdnd_glm.fit()`	Fitting Generalized Linear STAP Difference in Difference models
`stapdnd_glmer()`	Bayesian spatial-temporal generalized linear models with group-specific terms via Stan
`coef(<stapreg>)` `confint(<stapreg>)` `fitted(<stapreg>)` `nobs(<stapreg>)` `nstap(<stapreg>)` `ntap(<stapreg>)` `nsap(<stapreg>)` `nfix(<stapreg>)` `residuals(<stapreg>)` `se(<stapreg>)` `vcov(<stapreg>)` `fixef(<stapreg>)` `ngrps(<stapreg>)` `ranef(<stapreg>)` `sigma(<stapreg>)` `VarCorr(<stapreg>)`	Methods for stapreg objects
`stapreg-objects`	Fitted model objects
`stapreg()`	Create a stapreg object
`summary(<stapreg>)` `print(<summary.stapreg>)` `as.data.frame(<summary.stapreg>)`	Summary method for stapreg objects
`validate_distancedata()`	Validate distance_data
`validate_family()`	Check family argument
`validate_newdata()`	Validate newsubjdata argument for posterior_predict, log_lik, etc.
`validate_timedata()`	Validate time_data
`validate_weights()`	Check weights argument
`waic()`	Method for calculating Widely Applicable Information Criteria

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