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test_grap_ci.R
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test_grap_ci.R
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param_name = function(model){
param_name = list()
counter = 1
for (j in 1:length(model$desc)){
# is quantization noise?
if (model$process.desc[j] == "QN"){
param_name[[counter]] = expression(paste(hat(Q)^2))
counter = counter + 1
}
# is white noise?
if (model$process.desc[j] == "WN"){
param_name[[counter]] = expression(paste(hat(sigma)^2))
counter = counter + 1
}
# is AR1?
if (model$process.desc[j] == "AR1"){
param_name[[counter]] = expression(paste(hat(phi)))
counter = counter + 1
}
# is random walk?
if (model$process.desc[j] == "RW"){
param_name[[counter]] = expression(paste(hat(gamma)^2))
counter = counter + 1
}
# is random walk?
if (model$process.desc[j] == "SIGMA2"){
param_name[[counter]] = expression(paste(hat(nu)^2))
counter = counter + 1
}
# is drift?
if (model$process.desc[j] == "DR"){
param_name[[counter]] = expression(paste(hat(omega)^2))
counter = counter + 1
}
}
param_name
}
plot_CI = function(obj_list, units = NULL, xlab = NULL, ylab = NULL,
col_dens = NULL, col_ci = NULL, nb_ticks_x = NULL,
nb_ticks_y = NULL, ci_wv = NULL, point_cex = NULL,
point_pch = NULL,col_line = NULL, main = NULL, ...){
n_param = obj_list$model_hat$plength
windows_col = ceiling((obj_list$model_hat$plength)/2)
windows_row = floor((obj_list$model_hat$plength)/2)
#par(mfrow=c(windows_row,windows_row), mar = c(4,4,4,2))
for (i in 1:n_param){
density_param_ns = (density(na.omit(obj_list$distrib_param[,i])))
density_param_s = (density(na.omit(boot_para_ci[,i])))
# Labels
if (is.null(xlab)){
xlab = obj_list$model_hat$process.desc[i]
}else{
xlab = xlab
}
### to do
if (is.null(ylab)){
ylab = "Smoothed Density"
}else{
ylab = ylab
}
param_name = param_name(obj_list$model_hat)
if(is.null(main)){
main = param_name[[i]]
}
# Line and CI colors
if (is.null(col_dens)){
col_dens = hcl(h = 240, c = 65, l =70, alpha = 0.2, fixup = TRUE)
}
if (is.null(col_ci)){
col_ci = hcl(h = 210, l = 65, c = 100, alpha = 1)
}
# Line and CI colors
if (is.null(col_line)){
col_line = "darkblue"
}
# Range
x_range = c(obj_list$ci_low[[i]],obj_list$ci_high[[i]])
x_low = obj_list$ci_low[[i]] - obj_list$ci_low[[i]]/10
x_high = obj_list$ci_high[[i]] + obj_list$ci_high[[i]]/10
y_range = range(density_param$y)
y_low = min(y_range)
y_high = max(y_range)
x_ticks = obj_list$model_hat$theta[[i]]
x_labels = obj_list$model_hat$process.desc[i]
# Main Plot
plot(NA, xlim = x_range, ylim = c(y_low, y_high), xlab = xlab, ylab = ylab
, yaxt = 'n' , bty = "n", ann = FALSE)
win_dim = par("usr")
par(new = TRUE)
plot(NA, xlim = x_range, ylim = c(win_dim[3], win_dim[4] + 0.09*(win_dim[4] - win_dim[3])),
xlab = xlab, ylab = ylab, xaxt = 'n', yaxt = 'n', bty = "n")
win_dim = par("usr")
# Add Title
x_vec = c(win_dim[1], win_dim[2], win_dim[2], win_dim[1])
y_vec = c(win_dim[4], win_dim[4],
win_dim[4] - 0.09*(win_dim[4] - win_dim[3]),
win_dim[4] - 0.09*(win_dim[4] - win_dim[3]))
polygon(x_vec, y_vec, col = "grey95", border = NA)
text(x = mean(c(win_dim[1], win_dim[2])), y = (win_dim[4] - 0.09/2*(win_dim[4] - win_dim[3])), main)
# Add Axes and Box
lines(x_vec[1:2], rep((win_dim[4] - 0.09*(win_dim[4] - win_dim[3])),2), col = 1)
#y_ticks = y_ticks[(2^y_ticks) < 10^(win_dim[4] - 0.09*(win_dim[4] - win_dim[3]))]
box()
axis(1, at = x_ticks, padj = 0.3)
lines(density_param$x,density_param$y, type = "l", col = col_line)
polygon(c(obj_list$ci_low[[i]],density_param_ns$x[density_param$x>=obj_list$ci_low[[i]] & density_param_ns$x<=obj_list$ci_high[[i]]],obj_list$ci_high[[i]])
,c(obj_list$ci_low[[i]],density_param_ns$y[density_param$x>=obj_list$ci_low[[i]] & density_param_ns$x<=obj_list$ci_high[[i]]],obj_list$ci_hig[[i]]),
col=col_dens, border = F)
polygon(c(obj_list$ci_low[[i]],density_param_s$x[density_param$x>=obj_list$ci_low[[i]] & density_param_s$x<=obj_list$ci_high[[i]]],obj_list$ci_high[[i]])
,c(obj_list$ci_low[[i]],density_param_s$y[density_param$x>=obj_list$ci_low[[i]] & density_param_s$x<=obj_list$ci_high[[i]]],obj_list$ci_hig[[i]]),
col=col_dens, border = F)
lines(rep(obj_list$model_hat$theta[[i]],2), c(win_dim[3],
win_dim[4] - 0.09*(win_dim[4] - win_dim[3])), col = "red", lwd = 2)
}
}