#' @title LaTeX or HTML regression tables for MCMC Output

#' @description This function creates LaTeX or HTML regression tables for MCMC Output using 

#' the \code{\link[texreg]{texreg}} function from the \code{\link[texreg:texreg-package]{texreg}} R package.

#' @param mod Bayesian model object generated by R2jags, rjags, R2WinBUGS, R2OpenBUGS, 

#' MCMCpack, rstan, rstanarm, and brms, or a list of model objects of the same class.

#' @param pars a scalar or vector of the parameters you wish to include in the table.

#' By default, \code{mcmcReg} includes all parameters saved in a model object. If a

#' model has lots of samples and lots of saved parameters, not explicitly specifying

#' a limited number of parameters to include via \code{pars} may take a long time.

#' \code{pars} can either be a vector with the specific parameters to be included

#' in the table e.g. \code{pars = c("beta[1]", "beta[2]", "beta[3]")}, or they can

#' be partial names that will be matched using regular expressions e.g.

#' \code{pars = "beta"} if \code{regex = TRUE}. Both of these will include

#' \code{beta[1]}, \code{beta[2]}, and \code{beta[3]} in the table. When

#' combining models with different parameters in one table, this argument also

#' accepts a list the length of the number of models.

#' @param pointest a character indicating whether to use the mean or median for

#' point estimates in the table.

#' @param ci a scalar indicating the confidence level of the uncertainty intervals.

#' @param hpdi a logical indicating whether to use highest posterior density

#' intervals instead of equal tailed credible intervals to capture uncertainty

#' (default \code{FALSE}).

#' @param sd a logical indicating whether to report the standard deviation of

#' posterior distributions instead of an uncertainty interval

#' (default \code{FALSE}). If \code{TRUE}, overrides \code{ci}, \code{hpdi}, and

#' \code{pr}.

#' @param pr a logical indicating whether to report the probability that a

#' coefficient is in the same direction as the point estimate for that

#' coefficient (default \code{FALSE}). If \code{TRUE}, overrides \code{ci} and

#' \code{hpdi}.

#' @param coefnames an optional vector or list of vectors containing parameter

#' names for each model. If there are multiple models, the list must have the same

#' number of elements as there are models, and the vector of names in each list

#' element must match the number of parameters. If not supplied, the function

#' will use the parameter names in the model object(s). Note that this replaces

#' the standard \code{custom.coef.names} argument in \code{\link[texreg]{texreg}}

#' because there is no \code{extract} method for MCMC model objects, and many

#' MCMC model objects do not have unique parameter names.

#' @param gof a named list of goodness of fit statistics, or a list of such lists.

#' @param gofnames an optional vector or list of vectors containing

#' goodness of fit statistic names for each model. Like \code{coefnames} in this function

#' (which replaces the \code{custom.coef.names} argument in \code{\link[texreg]{texreg}}),

#' \code{gofnames} replaces the standard \code{custom.gof.names} argument in

#' \code{\link[texreg]{texreg}}. If 

#' there are multiple models, the list must have the same number of elements as

#' there are models, and the vector of names in each list element must match the

#' number of goodness of fit statistics.

#' @param format a character indicating \code{latex} or \code{html} output.

#' @param file optional file name to write table to file instead of printing to

#' console.

#' @param regex use regular expression matching with \code{pars}?

#' @param ... optional arguments to \code{\link[texreg]{texreg}}.

#'

#' @details If using \code{custom.coef.map} with more than one model, you should rename

#' the parameters in the model objects to ensure that different parameters with the

#' same subscript are not conflated by \code{texreg} e.g. \code{beta[1]} could represent age

#' in one model and income in another, and \code{texreg} would combine the two if you

#' do not rename \code{beta[1]} to more informative names in the model objects.

#'

#' If \code{mod} is a \code{brmsfit} object or list of \code{brmsfit} objects, note that the

#' default \code{brms} names for coefficients are \code{b_Intercept} and \code{b}, so both of

#' these should be included in \code{par} if you wish to include the intercept in the

#' table.

#'

#' @return A formatted regression table in LaTeX or HTML format.

#'

#' @author Rob Williams, \email{jayrobwilliams@gmail.com}

#'

#' @examples

#' \dontshow{.old_wd <- setwd(tempdir())}

#' \donttest{

#' ## simulating data

#' set.seed(123456)

#' b0 <- 0.2 # true value for the intercept

#' b1 <- 0.5 # true value for first beta

#' b2 <- 0.7 # true value for second beta

#' n <- 500 # sample size

#' X1 <- runif(n, -1, 1)

#' X2 <- runif(n, -1, 1)

#' Z <- b0 + b1 * X1 + b2 * X2

#' pr <- 1 / (1 + exp(-Z)) # inv logit function

#' Y <- rbinom(n, 1, pr)

#' df <- data.frame(cbind(X1, X2, Y))

#' 

#' ## formatting the data for jags

#' datjags <- as.list(df)

#' datjags$N <- length(datjags$Y)

#' 

#' ## creating jags model

#' model <- function()  {

#' 

#'   for(i in 1:N){

#'     Y[i] ~ dbern(p[i])  ## Bernoulli distribution of y_i

#'     logit(p[i]) <- mu[i]    ## Logit link function

#'     mu[i] <- b[1] +

#'       b[2] * X1[i] +

#'       b[3] * X2[i]

#'   }

#' 

#'   for(j in 1:3){

#'     b[j] ~ dnorm(0, 0.001) ## Use a coefficient vector for simplicity

#'   }

#' 

#' }

#' 

#' params <- c("b")

#' inits1 <- list("b" = rep(0, 3))

#' inits2 <- list("b" = rep(0, 3))

#' inits <- list(inits1, inits2)

#' 

#' ## fitting the model with R2jags

#' set.seed(123)

#' fit <- R2jags::jags(data = datjags, inits = inits,

#'                     parameters.to.save = params,

#'                     n.chains = 2,

#'                     n.iter = 2000, n.burnin = 1000,

#'                     model.file = model)

#' 

#' ## generating regression table with all parameters

#' mcmcReg(fit)

#' 

#' ## generating regression table with only betas and custom coefficent names

#' mcmcReg(fit, pars = c('b'), coefnames = c('Variable 1',

#'                                           'Variable 2',

#'                                           'Variable 3'),

#'         regex = TRUE)

#' ## generating regression tables with all betas and custom names

#' mcmcReg(fit, coefnames = c('Variable 1', 'Variable 2',

#'                            'Variable 3', 'deviance'))

#' }

#' 

#' \dontshow{setwd(.old_wd)}

#' @export

#' 

mcmcReg <- function(mod, 

                    pars = NULL, 

                    pointest = 'mean', 

                    ci = .95, 

                    hpdi = FALSE,

                    sd = FALSE,

                    pr = FALSE,

                    coefnames = NULL, 

                    gof = numeric(0),

                    gofnames = character(0),

                    format = 'latex', 

                    file, 

                    regex = FALSE,

                    ...) {

  ## pull in unexported functions from other packages

  ## other options for future versions might include lifting this and adding authors as copr holders

  ## if only one model object, coerce to a list

  ## check for heterogeneous model objects

  ## if only one custom coefficient names vector, coerce to a list

  ## if only one parameter vector, coerce to a list

  ## if only one gof statistic scalar or vector, coerce to a list

  ## if only one gof statistic name scalar or vector, coerce to a list

  ## extract samples and variable names from jags or rjags objects

    ## extract posterior samples from list of model objects

  }

  ## extract samples and variable names from bugs object

    ## extract posterior samples from list of model objects

  }

  ## extract samples and variable names from runjags object

  }

  ## extract samples and variable names from remaining objects

  }

  ## limit samples to supplied parameters

  }

  ## calculate point estimate of posterior density

  ## calculate uncertainty interval for or standard deviation

  } else {

  }

  ## if coefficent names supplied, replace names from model object(s)

  }

  ##

  }

  ## create list of texreg object(s) with point estimates and interval

  } else {

  }

  ## create LaTeX output

    ## create LaTeX code

    } else {

      ## replace confidence w/ credible or highest posterior density in texreg output

      } else {

      }

    }

    ## return LaTeX code to console or write to file

    } else {

      ## remove newline at start of LaTeX code

    }

  }

  ## create HTML output

    } else {

      ## replace confidence w/ credible or highest posterior density in texreg output

      } else {

      }

    }

    ## return html code to console or write to file

    } else {

    }

  }

}