#' @export
#' @title posterior density plots
#' @param obj an estimated BVAR-model
#' @param lag lag for parameters (0=intercept)
#' @param hpd level for credible interval
#' @param ... not used
#' @rdname plot_density
plot_density <- function(obj,lag=1,hpd=NULL,...) UseMethod("plot_density")
#' @export
#' @rdname plot_density
plot_density.bvar <- function(obj,lag=1,hpd=NULL,...){
# input check
# want to plot density of intercept but no intercept -> stop
intercept = obj$general_info$intercept
if((lag == 0) && (intercept == FALSE)){
stop("Model has no intercept")
}
# want to plot density of lag greater than used in the model -> stop
if(lag > obj$general_info$nolags){
stop("Number of lags is lower!")
}
# Sanity check: is lag-number of positive
if(lag<0){
stop("Number of lags must be positive")
}
coefs <- obj$mcmc_draws$Alpha
ndim <- dim(coefs)
nruns <- ndim[3] # number of draws
nvar <- ndim[2] # number of variables
pltlist <- list()
if(lag == 0){
trace_coefs <- coefs[1,,]
for(ii in 1:nvar){
tmp.df <- data.frame(draws = trace_coefs[ii,])
p1 <- ggplot2::ggplot(data = tmp.df) + ggplot2::geom_density(mapping = ggplot2::aes_(x=~draws),fill="lightblue",alpha=0.75,size=1)
p1 <- p1 + ggplot2::ylab(obj$data_info$var_names[ii])
# Compute highest posterior density
if(!is.null(hpd)){
upper <- 1-hpd/2
lower <- hpd/2
lower_quantile <- stats::quantile(tmp.df$draws,probs=lower)
upper_quantile <- stats::quantile(tmp.df$draws,probs=upper)
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=lower_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=upper_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
}
if(ii == nvar){
p1 <- p1 + ggplot2::xlab("Value")
}
else{
p1 <- p1 + ggplot2::theme(axis.title.x=ggplot2::element_blank())
}
pltlist[[ii]] <- p1
}
}
if(lag > 0){
# get coefficients
const <- 0
if(intercept == TRUE) constant <- 1
nlow <- (lag - 1) * nvar + 1 + const
nhigh <- lag * nvar + const
trace_coefs <- coefs[nlow:nhigh,,]
for(ii in 1:nvar){
for(jj in 1:nvar){
tmp.df <- data.frame(draws=trace_coefs[ii,jj,])
p1 <- ggplot2::ggplot(data = tmp.df) + ggplot2::geom_density(mapping = ggplot2::aes_(x=~draws),fill="lightblue",alpha=0.75,size=1)
if(!is.null(hpd)){
upper <- 1-hpd/2
lower <- hpd/2
lower_quantile <- stats::quantile(tmp.df$draws,probs=lower)
upper_quantile <- stats::quantile(tmp.df$draws,probs=upper)
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=lower_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=upper_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
}
if(ii == 1){
p1 <- p1 + ggplot2::ylab(obj$data_info$var_names[jj])
}
else{
p1 <- p1 + ggplot2::theme(axis.title.y = ggplot2::element_blank())
}
if(jj == 1){
p1 <- p1 + ggplot2::ggtitle(obj$data_info$var_names[ii]) + ggplot2::theme(plot.title = ggplot2::element_text(size = 10))
}
if(jj == nvar){
p1 <- p1 + ggplot2::xlab("Value")
}
else{
p1 <- p1 + ggplot2::theme(axis.title.x=ggplot2::element_blank())
}
pltlist[[(jj - 1) * nvar + ii]] <- p1
}
}
}
# Draw plots
do.call("grid.arrange",c(pltlist,nrow=nvar))
}
#' @export
#' @param regime Regime for the density plot
#' @rdname plot_density
plot_density.msvar <- function(obj,lag=1,hpd=NULL,regime=1,...){
# want to plot density of intercept but no intercept -> stop
intercept = obj$general_info$intercept
if((lag == 0) && (intercept == FALSE)){
stop("Model has no intercept")
}
# want to plot density of lag greater than used in the model -> stop
if(lag > obj$general_info$nolags){
stop("Number of lags is lower!")
}
# Sanity check: is lag-number of positive
if(lag<0){
stop("Number of lags must be positive")
}
# Possible regime?
if(regime > obj$general_info$noregimes){
stop("Regime selected is higher than the number of regimes in the model")
}
if(regime < 1){
stop("Selected Regime must be strictly positive")
}
coefs <- obj$mcmc_draws$Alpha[,,regime,]
ndim <- dim(coefs)
nruns <- ndim[3] # number of draws
nvar <- ndim[2] # number of variables
pltlist <- list()
if(lag == 0){
trace_coefs <- coefs[1,,]
for(ii in 1:nvar){
tmp.df <- data.frame(draws = trace_coefs[ii,])
p1 <- ggplot2::ggplot(data = tmp.df) + ggplot2::geom_density(mapping = ggplot2::aes_(x=~draws),fill="lightblue",alpha=0.75,size=1)
p1 <- p1 + ggplot2::ylab(obj$data_info$var_names[ii])
# Compute highest posterior density
if(!is.null(hpd)){
upper <- 1-hpd/2
lower <- hpd/2
lower_quantile <- stats::quantile(tmp.df$draws,probs=lower)
upper_quantile <- stats::quantile(tmp.df$draws,probs=upper)
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=lower_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=upper_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
}
if(ii == nvar){
p1 <- p1 + ggplot2::xlab("Value")
}
else{
p1 <- p1 + ggplot2::theme(axis.title.x=ggplot2::element_blank())
}
pltlist[[ii]] <- p1
}
}
if(lag > 0){
# get coefficients
const <- 0
if(intercept == TRUE) constant <- 1
nlow <- (lag - 1) * nvar + 1 + const
nhigh <- lag * nvar + const
trace_coefs <- coefs[nlow:nhigh,,]
for(ii in 1:nvar){
for(jj in 1:nvar){
tmp.df <- data.frame(draws=trace_coefs[ii,jj,])
p1 <- ggplot2::ggplot(data = tmp.df) + ggplot2::geom_density(mapping = ggplot2::aes_(x=~draws),fill="lightblue",alpha=0.75,size=1)
if(!is.null(hpd)){
upper <- 1-hpd/2
lower <- hpd/2
lower_quantile <- stats::quantile(tmp.df$draws,probs=lower)
upper_quantile <- stats::quantile(tmp.df$draws,probs=upper)
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=lower_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
p1 <- p1 + ggplot2::geom_vline(mapping = ggplot2::aes_(xintercept=upper_quantile),color="dodgerblue1",size=1.1,linetype="dashed")
}
if(ii == 1){
p1 <- p1 + ggplot2::ylab(obj$data_info$var_names[jj])
}
else{
p1 <- p1 + ggplot2::theme(axis.title.y = ggplot2::element_blank())
}
if(jj == 1){
p1 <- p1 + ggplot2::ggtitle(obj$data_info$var_names[ii]) + ggplot2::theme(plot.title = ggplot2::element_text(size = 10))
}
if(jj == nvar){
p1 <- p1 + ggplot2::xlab("Value")
}
else{
p1 <- p1 + ggplot2::theme(axis.title.x=ggplot2::element_blank())
}
pltlist[[(jj - 1) * nvar + ii]] <- p1
}
}
}
# Draw plots
do.call("grid.arrange",c(pltlist,nrow=nvar))
}
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