pred,Bayes.fit-method {mixedsde}

Bayesian prediction method for a class object Bayes.fit

Description

Bayesian prediction

Usage

## S4 method for signature 'Bayes.fit'
pred(x, invariant = FALSE, level = 0.05,
  newwindow = FALSE, plot.pred = TRUE, plot.legend = TRUE, burnIn,
  thinning, only.interval = TRUE, sample.length = 500,
  cand.length = 100, trajectories = FALSE, ylim, xlab = "times",
  ylab = "X", col = 3, lwd = 2, ...)

Arguments

x

Bayes.fit class

invariant

logical(1), if TRUE, the initial value is from the invariant distribution X_t~N(\alpha/\beta, \sigma^2/2\beta) for the OU and X_t~\Gamma(2\alpha/\sigma^2, \sigma^2/2\beta) for the CIR process, if FALSE (default) X0 is fixed from the data starting points

level

alpha for the predicion intervals, default 0.05

newwindow

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

plot.pred

logical(1), if TRUE, the results are depicted grafically

plot.legend

logical(1), if TRUE, a legend is added to the plot

burnIn

optional, if missing, the proposed value of the mixedsde.fit function is taken

thinning

optional, if missing, the proposed value of the mixedsde.fit function is taken

only.interval

logical(1), if TRUE, only prediction intervals are calculated, much faster than sampling from the whole predictive distribution

sample.length

number of samples to be drawn from the predictive distribution, if only.interval = FALSE

cand.length

number of candidates for which the predictive density is calculated, i.e. the candidates to be drawn from

trajectories

logical(1), if TRUE, only trajectories are drawn from the point estimations instead of sampling from the predictive distribution, similar to the frequentist approach

ylim

optional

xlab

optional, default 'times'

ylab

optional, default 'X'

col

color for the prediction intervals, default 3

lwd

linewidth for the prediction intervals, default 3

...

optional plot parameters

References

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