calculate one-step-ahead (prediction) residuals from a foieGras fit
calculate one-step-ahead (prediction) residuals from a foieGras fit
osar(x, method = "fullGaussian", ...)
x |
a compound |
method |
method to calculate prediction residuals (default is "oneStepGaussianOffMode"; see |
... |
other arguments to TMB::oneStepPrediction |
One-step-ahead residuals are useful for assessing goodness-of-fit in latent variable models. This is a wrapper function for TMB::oneStepPredict (beta version). osar tries the "fullGaussian" (fastest) method first and falls back to the "oneStepGaussianOffMode" (slower) method for any failures. Subsequent failures are dropped from the output and a warning message is given. Note, OSA residuals can take a considerable time to calculate if there are many individual fits and/or deployments are long. The method is automatically parallelized across 2 x the number of individual fits, up to the number of processor cores available.
Thygesen, U. H., C. M. Albertsen, C. W. Berg, K. Kristensen, and A. Neilsen. 2017. Validation of ecological state space models using the Laplace approximation. Environmental and Ecological Statistics 24:317–339.
## generate a fG_ssm fit object (call is for speed only) xs <- fit_ssm(sese2, spdf=FALSE, model = "rw", time.step=72, control = ssm_control(se = FALSE, verbose = 0)) ## just use one seal to save time dres <- osar(xs[2,])
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