plot2compare,Bayes.pred-method {mixedsde}

Comparing plot method plot2compare for three Bayesian prediction class objects

Description

Comparison of the results for up to three S4 class Bayes.pred objects

Usage

## S4 method for signature 'Bayes.pred'
plot2compare(x, y, z, newwindow = FALSE,
  plot.legend = TRUE, names, ylim, xlab = "times", ylab = "X", ...)

Arguments

x

Bayes.pred class

y

Bayes.pred class

z

Bayes.pred class (optional)

newwindow

logical(1), if TRUE, a new window is opened for the plot

plot.legend

logical(1), if TRUE, a legend is added

names

character vector with names for the three objects appearing in the legend

ylim

optional

xlab

optional, default 'times'

ylab

optional, default 'X'

...

optional plot parameters

References

Dion, C., Hermann, S. and Samson, A. (2016). Mixedsde: a R package to fit mixed stochastic differential equations.

Examples

random <- 1; sigma <- 0.1; fixed <- 5; param <- c(3, 0.5)
sim <- mixedsde.sim(M = 20, T = 1, N = 50, model = 'OU', random = random, fixed = fixed,
       density.phi = 'normal',param= param, sigma= sigma, X0 = 0, op.plot = 1)

# here: only 100 iterations for example - should be much more!
estim_Bayes_withoutprior <- mixedsde.fit(times = sim$times, X = sim$X, model = 'OU',
             random, estim.method = 'paramBayes',  nMCMC = 100)
prior <- list( m = c(param[1], fixed), v = c(param[1], fixed), alpha.omega = 11,
            beta.omega = param[2]^2*10, alpha.sigma = 10, beta.sigma = sigma^2*9)
estim_Bayes <- mixedsde.fit(times = sim$times, X = sim$X, model = 'OU', random, 
           estim.method = 'paramBayes', prior = prior, nMCMC = 100) 
plot2compare(estim_Bayes, estim_Bayes_withoutprior, names = c('with prior', 'without prior'))