momentuHMM (version 1.5.7)

pseudoRes: Pseudo-residuals

Description

The pseudo-residuals of momentuHMM models, as described in Zucchini and McDonad (2009).

Usage

pseudoRes(m, ncores = 1)

Value

If m is a momentuHMM, miHMM, or miSum object, a list of pseudo-residuals for each data stream (e.g., 'stepRes', 'angleRes') is returned. If m is a list of momentuHMM objects, then a list of length length(m) is returned where each element is a list of pseudo-residuals for each data stream.

Arguments

m

A momentuHMM, miHMM, HMMfits, or miSum object.

ncores

number of cores to use for parallel processing

Details

If some turning angles in the data are equal to pi, the corresponding pseudo-residuals will not be included. Indeed, given that the turning angles are defined on (-pi,pi], an angle of pi results in a pseudo-residual of +Inf (check Section 6.2 of reference for more information on the computation of pseudo-residuals).

A continuity adjustment (adapted from Harte 2017) is made for discrete probability distributions. When the data are near the boundary (e.g. 0 for ``pois''; 0 and 1 for ``bern''), then the pseudo residuals can be a poor indicator of lack of fit.

For multiple imputation analyses, if m is a miHMM object or a list of momentuHMM objects, then the pseudo-residuals are individually calculated for each model fit. Note that pseudo-residuals for miSum objects (as returned by MIpool) are based on pooled parameter estimates and the means of the data values across all imputations (and therefore may not be particularly meaningful).

References

Harte, D. 2017. HiddenMarkov: Hidden Markov Models. R package version 1.8-8.

Zucchini, W. and MacDonald, I.L. 2009. Hidden Markov Models for Time Series: An Introduction Using R. Chapman & Hall (London).

Examples

# m is a momentuHMM object (as returned by fitHMM), automatically loaded with the package
m <- example$m
res <- pseudoRes(m)
stats::qqnorm(res$stepRes)
stats::qqnorm(res$angleRes)