osar: calculate one-step-ahead (prediction) residuals from a foieGras fit
Description
calculate one-step-ahead (prediction) residuals from a foieGras fit
Usage
osar(x, method = "fullGaussian", ...)
Arguments
x
a compound fG tbl fit object
method
method to calculate prediction residuals (default is "oneStepGaussianOffMode"; see `?TMB::oneStepPrediction` for details)
...
other arguments to TMB::oneStepPrediction
Details
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.
References
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<U+2013>339.
# NOT RUN {## see summary fit output## load example foieGras fit object (to save time)data(fssm)
d <- fssm[1, ] ## just use the first seal to save timedres <- osar(d)
# }