Nothing
#' @export
#' @noRd
summary.mcmc_hsar <- function(object, ...)
{
x<-object
cat("\nCall:\n")
print(x$call)
cat("Type:", ' hsar ', "\n")
cat("\nCoefficients:\n")
dfb <- as.data.frame(t(rbind(x$Mbetas,x$SDbetas)))
names(dfb)<-c("Mean","SD")
print( dfb )
cat("\n Spatial Coefficients:\n")
print(cbind( rho= x$Mrho, lambda=x$Mlambda))
cat("\n Diagnostics \n")
cat("Deviance information criterion (DIC):", x$DIC, "\n")
cat("Effective number of parameters (pd):", x$pD, "\n")
cat("Log likelihood:", x$Log_Likelihood, "\n")
cat("Pseudo R squared:", x$R_Squared, "\n")
cat("\n Impacts:\n")
df <- as.data.frame(cbind( t(x$impact_direct), t(x$impact_indirect), t(x$impact_total)))
names(df)<-c("direct","indirect","total")
row.names(df)<- x$labels
print(df)
cat("\n Quantiles:\n")
v <- c(0.05, 0.25, 0.5, 0.75, 0.95)
print(t(sapply(x$cbetas,function(i) stats::quantile(i, v))))
invisible(x)
}
#' @export
#' @noRd
summary.mcmc_sar <- function(object, ...)
{
x<-object
cat("\nCall:\n")
print(x$call)
cat("Type:", ' sar ', "\n")
cat("\nCoefficients:\n")
dfb <- as.data.frame(t(rbind(x$Mbetas,x$SDbetas)))
names(dfb)<-c("Mean","SD")
print( dfb )
rho<-x$Mrho
names(rho)<-'rho'
cat("\n Spatial Coefficients:\n")
print( rho )
cat("\n Diagnostics \n")
cat("Deviance information criterion (DIC):", x$DIC, "\n")
cat("Effective number of parameters (pd):", x$pD, "\n")
cat("Log likelihood:", x$Log_Likelihood, "\n")
cat("Pseudo R squared:", x$R_Squared, "\n")
cat("\n Impacts:\n")
df <- as.data.frame(cbind( t(x$impact_direct), t(x$impact_indirect), t(x$impact_total)))
names(df)<-c("direct","indirect","total")
row.names(df)<- x$labels
print( df )
cat("\n Quantiles:\n")
v <- c(0.05, 0.25, 0.5, 0.75, 0.95)
print(t(sapply(x$cbetas, function(i) stats::quantile(i, v))))
invisible(x)
}
#' @export
#' @noRd
summary.mcmc_hsar_rho_0 <- function(object, ...)
{
x <- object
cat("\nCall:\n")
print(x$call)
cat("Type:", ' hsar with rho = 0 ', "\n")
cat("\nCoefficients:\n")
dfb <- as.data.frame( t(rbind(x$Mbetas,x$SDbetas)) )
names(dfb)<-c("Mean","SD")
print( dfb )
lambda<-x$Mlambda
names(lambda)<-'lambda'
cat("\n Spatial Coefficients:\n")
print( lambda )
cat("\n Diagnostics \n")
cat("Deviance information criterion (DIC):", x$DIC, "\n")
cat("Effective number of parameters (pd):", x$pD, "\n")
cat("Log likelihood:", x$Log_Likelihood, "\n")
cat("Pseudo R squared:", x$R_Squared, "\n")
cat("\n Quantiles:\n")
v <- c(0.05, 0.25, 0.5, 0.75, 0.95)
print( t(sapply( x$cbetas, function(i) stats::quantile(i, v))) )
invisible(x)
}
#' @export
#' @noRd
summary.mcmc_hsar_lambda_0 <- function(object, ...)
{
x <- object
cat("\nCall:\n")
print(x$call)
cat("Type:", ' hsar with lambda = 0 ', "\n")
cat("\nCoefficients:\n")
dfb <- as.data.frame( t(rbind(x$Mbetas,x$SDbetas)) )
names(dfb)<-c("Mean","SD")
print( dfb )
rho<-x$Mrho
names(rho)<-'rho'
cat("\n Spatial Coefficients:\n")
print( rho )
cat("\n Diagnostics \n")
cat("Deviance information criterion (DIC):", x$DIC, "\n")
cat("Effective number of parameters (pd):", x$pD, "\n")
cat("Log likelihood:", x$Log_Likelihood, "\n")
cat("Pseudo R squared:", x$R_Squared, "\n")
cat("\n Quantiles:\n")
v <- c(0.05, 0.25, 0.5, 0.75, 0.95)
print( t(sapply( x$cbetas, function(i) stats::quantile(i, v))) )
invisible(x)
}
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