library(bdskytools)
rm(list = ls())
x0 <- c(1,1.5,2,5)
xlim <- c(0,5)
#####################################################################
# Example 1: With fixed parameter values (get theoretical quantiles)
plotOUProcessFlexibility(xlim, dt=0.025, x0, mu=1, sigma=1, nu=1)
plotOUProcessFlexibility(xlim, dt=0.1, x0, mu=1, sigma=1, nu=1)
plotOUProcessFlexibility(xlim, dt=10, x0, mu=1, sigma=1, nu=1)
plotOUProcessFlexibility(xlim, dt=0.025, x0, mu=1, sigma=1, nu=10)
plotOUProcessFlexibility(xlim, dt=0.1, x0, mu=1, sigma=1, nu=10)
plotOUProcessFlexibility(xlim, dt=10, x0, mu=1, sigma=1, nu=10)
plotOUProcessFlexibility(xlim, dt=0.025, x0, mu=1, sigma=5, nu=10)
plotOUProcessFlexibility(xlim, dt=0.1, x0, mu=1, sigma=5, nu=10)
plotOUProcessFlexibility(xlim, dt=10, x0, mu=1, sigma=5, nu=10)
#####################################################################
# Example 2: Sample parameters from priors
# (get empirical HPDs from simulated trajectories)
mu_p <- getPrior(rlnorm, 1, meanlog=0, sdlog=1.25)
sigma_p <- getPrior(rlnorm, 1, meanlog=0, sdlog=0.25)
nu_p <- getPrior(rexp, 1, rate=1)
plotOUProcessFlexibilityEmpirical(xlim, dt=0.025, x0, mu_p, sigma_p, nu_p)
plotOUProcessFlexibilityEmpirical(xlim, dt=0.1, x0, mu_p, sigma_p, nu_p)
plotOUProcessFlexibilityEmpirical(xlim, dt=0.5, x0, mu_p, sigma_p, nu_p)
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