R/print.binaryGP.R

In binaryGP: Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response

#' Print Fitted results of Binary Gaussian Process
#'
#' @description The function shows the estimation results by \code{binaryGP_fit}.
#'
#' @param x a class binaryGP object estimated by binaryGP_fit.
#' @param ... for compatibility with generic method \code{print}.
#'
#' @return a list of estimates by binaryGP_fit.
#' @seealso \code{\link{binaryGP_fit}} for estimation of the binary Gaussian process.
#' @author Chih-Li Sung <iamdfchile@gmail.com>
#' @examples
#'
#' library(binaryGP)
#'
#' #####      Testing function: cos(x1 + x2) * exp(x1*x2) with TT sequences      #####
#' #####   Thanks to Sonja Surjanovic and Derek Bingham, Simon Fraser University #####
#' test_function <- function(X, TT)
#' {
#'   x1 <- X[,1]
#'   x2 <- X[,2]
#'
#'   eta_1 <- cos(x1 + x2) * exp(x1*x2)
#'
#'   p_1 <- exp(eta_1)/(1+exp(eta_1))
#'   y_1 <- rep(NA, length(p_1))
#'   for(i in 1:length(p_1)) y_1[i] <- rbinom(1,1,p_1[i])
#'   Y <- y_1
#'   P <- p_1
#'   if(TT > 1){
#'     for(tt in 2:TT){
#'       eta_2 <- 0.3 * y_1 + eta_1
#'       p_2 <- exp(eta_2)/(1+exp(eta_2))
#'       y_2 <- rep(NA, length(p_2))
#'       for(i in 1:length(p_2)) y_2[i] <- rbinom(1,1,p_2[i])
#'       Y <- cbind(Y, y_2)
#'       P <- cbind(P, p_2)
#'       y_1 <- y_2
#'     }
#'   }
#'
#'   return(list(Y = Y, P = P))
#' }
#'
#' set.seed(1)
#' n <- 30
#' n.test <- 10
#' d <- 2
#' X <- matrix(runif(d * n), ncol = d)
#'
#' ##### without time-series #####
#' Y <- test_function(X, 1)$Y  ## Y is a vector
#'
#' binaryGP.model <- binaryGP_fit(X = X, Y = Y)
#' print(binaryGP.model)   # print estimation results
#' summary(binaryGP.model) # significance results
#' \donttest{
#' ##### with time-series, lag 1 #####
#' Y <- test_function(X, 10)$Y  ## Y is a matrix with 10 columns
#'
#' binaryGP.model <- binaryGP_fit(X = X, Y = Y, R = 1)
#' print(binaryGP.model)   # print estimation results
#' summary(binaryGP.model) # significance results
#' }
#' @export

print.binaryGP <- function(x, ...){

  if (is.binaryGP(x) == FALSE) {
    stop("The object in question is not of class binaryGP \n")
  }

  return(list(alpha_hat = x$alpha_hat,
              varphi_hat = x$varphi_hat,
              gamma_hat = x$gamma_hat,
              theta_hat = x$theta_hat,
              sigma_hat = x$sigma_hat))
}