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Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sun, Jul 23, 2017 at 7:08 AM, Gavan McGrath <gavan.mcgr...@uwa.edu.au> wrote:
> Hi,
>
> Using the example in ?VSEM in the package BayesianTools I'm attempting to
> iteratively update the prior but find the plotTimeSeriesResults produces the
> following errors when I extend the VSEM example in BayesianTools. With the
> Code below (the errors) I get:
> " Error in quantile.default(x, probs = quantiles[i]) :
> missing values and NaN's not allowed if 'na.rm' is FALSE"
>
> The error appears to come from the function getPredictiveIntervals,
> specifically the lines:
> for (i in 1:nrow(predDistr)) {
> predDistr[i, ] = error(mean = pred[i, ], par = parMatrix[i,
> ])
> }
> predInt = getCredibleIntervals(sampleMatrix = predDistr,
> quantiles = quantiles)
>
> I suspect lower and upper bounds on the parameters are not being enforced
> leading to a negative standard deviation being passed to rnorm?.
> Any suggestions on how to proceed would be welcome.
>
> Code:
> #run the example in ?VSEM first then:
>
> newPrior = createPriorDensity(out, method = "multivariate",
> eps = 1e-10,
> lower = refPars$lower[parSel],
> upper = refPars$upper[parSel])
>
> bayesianSetup <- createBayesianSetup(likelihood = likelihood,
> prior = newPrior,
> names = rownames(refPars)[parSel] )
>
>
> out <- runMCMC(bayesianSetup = bayesianSetup, settings = settings)
> plotTimeSeriesResults(sampler = out,
> model = createPredictions,
> observed = obs,
> error = createError,
> prior = TRUE,
> main = "Prior predictive")
>
> [[alternative HTML version deleted]]
>
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