Creates a time series plot typical for an MCMC / SMC fit
plotTimeSeriesResults(sampler, model, observed, error = NULL,
plotResiduals = TRUE, start = 1, prior = FALSE, ...)Either a) a matrix b) an MCMC object (list or not), or c) an SMC object
function that calculates model predictions for a given parameter vector
observed values
function with signature f(mean, par) that generates error expectations from mean model predictions. Par is a vector from the matrix with the parameter samples (full length). f needs to know which of these parameters are parameters of the error function
logical determining whether residuals should be plotted
numeric start value for the plot (see getSample)
if a prior sampler is implemented, setting this parameter to TRUE will draw model parameters from the prior instead of the posterior distribution
further arguments passed to plot