# plot2compare-Bayes.pred-method: Comparing plot method plot2compare for three Bayesian... In charlottedion/mixedsde: Estimation Methods for Stochastic Differential Mixed Effects Models

## Description

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

## Usage

 ```1 2 3``` ```## 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```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')) ```

charlottedion/mixedsde documentation built on May 13, 2019, 3:35 p.m.