brms (version 1.1.0)

make_stancode: Stan Code for brms Models

Description

Generate Stan code for brms models

Usage

make_stancode(formula, data = NULL, family = gaussian(), prior = NULL, autocor = NULL, nonlinear = NULL, partial = NULL, threshold = c("flexible", "equidistant"), sparse = FALSE, cov_ranef = NULL, sample_prior = FALSE, stan_funs = NULL, save_model = NULL, ...)

Arguments

formula

An object of class brmsformula (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are explained in brmsformula.

data

An optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which brm is called. Although it is optional, we strongly recommend to supply a data.frame.

family

A description of the response distribution and link function to be used in the model. This can be a family function, a call to a family function or a character string naming the family. Every family function has a link argument allowing to specify the link function to be applied on the response variable. If not specified, default links are used. For details of supported families see brmsfamily.

prior

One or more brmsprior objects created by function set_prior and combined using the c method. A single brmsprior object may be passed without c() surrounding it. See also get_prior for more help.

autocor

An optional cor_brms object describing the correlation structure within the response variable (i.e. the 'autocorrelation'). See the documentation of cor_brms for a description of the available correlation structures. Defaults to NULL, corresponding to no correlations.

nonlinear

An optional list of formuluas, specifying linear models for non-linear parameters. If NULL (the default) formula is treated as an ordinary formula. If not NULL, formula is treated as a non-linear model and nonlinear should contain a formula for each non-linear parameter, which has the parameter on the left hand side and its linear predictor on the right hand side. Alternatively, it can be a single formula with all non-linear parameters on the left hand side (separated by a +) and a common linear predictor on the right hand side. More information is given under 'Details'.

partial

(Deprecated) A one sided formula of the form ~expression allowing to specify predictors with category specific effects in non-cumulative ordinal models (i.e. in families cratio, sratio, or acat). As of brms > 0.8.0 category specific effects should be specified directly within formula using function cse.

threshold

A character string indicating the type of thresholds (i.e. intercepts) used in an ordinal model. "flexible" provides the standard unstructured thresholds and "equidistant" restricts the distance between consecutive thresholds to the same value.

sparse

Logical; indicates whether the population-level design matrix should be treated as sparse (defaults to FALSE). For design matrices with many zeros, this can considerably reduce required memory. For univariate sparse models, it may be sensible to prevent the design matrix from being centered (see 'Details' for more information), as centering may reduce sparsity. For all models using multivariate syntax (i.e. multivariate linear models, zero-inflated and hurdle models as well as categorical models), setting sparse = TRUE, is generally worth a try to decrease memory requirements. However, sampling speed is currently not improved or even slightly decreased.

cov_ranef

A list of matrices that are proportional to the (within) covariance structure of the random effects. The names of the matrices should correspond to columns in data that are used as grouping factors. All levels of the grouping factor should appear as rownames of the corresponding matrix. This argument can be used, among others, to model pedigrees and phylogenetic effects.

sample_prior

A flag to indicate if samples from all specified proper priors should be drawn additionally to the posterior samples (defaults to FALSE). Among others, these samples can be used to calculate Bayes factors for point hypotheses. Alternatively, sample_prior can be set to "only" to sample solely from the priors. In this case, all parameters must have proper priors.

stan_funs

An optional character string containing self-defined Stan functions, which will be included in the functions block of the generated Stan code.

save_model

Either NULL or a character string. In the latter case, the model code is saved in a file named after the string supplied in save_model, which may also contain the full path where to save the file. If only a name is given, the file is saved in the current working directory.

...

Other arguments for internal usage only

Value

A character string containing the fully commented Stan code to fit a brms model.

Examples

make_stancode(rating ~ treat + period + carry + (1|subject), 
              data = inhaler, family = "cumulative")

make_stancode(count ~ log_Age_c + log_Base4_c * Trt_c 
              + (1|patient) + (1|visit), 
              data = epilepsy, family = "poisson")