# AICweights: Calculate Akaike information criterion model weights In momentuHMM: Maximum Likelihood Analysis of Animal Movement Behavior Using Multivariate Hidden Markov Models

## Description

Calculate Akaike information criterion model weights

## Usage

 `1` ```AICweights(..., k = 2, n = NULL) ```

## Arguments

 `...` `momentuHMM`, `HMMfits`, or `miHMM` objects, to compare AIC weights of the different models. The first object must be a `momentuHMM`, `HMMfits`, or `miHMM` object, but additional model objects can be passed as a list using the `!!!` operator (see `rlang`). `k` Penalty per parameter. Default: 2 ; for classical AIC. `n` Optional sample size. If specified, the small sample correction AIC is used (i.e., `AICc = AIC + kp(p+1)/(n-p-1)` where p is the number of parameters).

## Details

• Model objects must all be either of class `momentuHMM` or multiple imputation model objects (of class `HMMfits` and/or `miHMM`).

• AIC is only valid for comparing models fitted to the same data. The data for each model fit must therefore be identical. For multiple imputation model objects, respective model fits must have identical data.

## Value

The AIC weights of the models. If multiple imputation objects are provided, then the mean model weights (and standard deviations) are provided.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35``` ```## Not run: # HMM specifications nbStates <- 2 stepDist <- "gamma" angleDist <- "vm" mu0 <- c(20,70) sigma0 <- c(10,30) kappa0 <- c(1,1) stepPar0 <- c(mu0,sigma0) anglePar0 <- c(-pi/2,pi/2,kappa0) formula <- ~cov1+cov2 # example\$m is a momentuHMM object (as returned by fitHMM), automatically loaded with the package mod1 <- fitHMM(example\$m\$data,nbStates=nbStates,dist=list(step=stepDist,angle=angleDist), Par0=list(step=stepPar0,angle=anglePar0), formula=~1,estAngleMean=list(angle=TRUE)) Par0 <- getPar0(mod1,formula=formula) mod2 <- fitHMM(example\$m\$data,nbStates=nbStates,dist=list(step=stepDist,angle=angleDist), Par0=Par0\$Par,beta0=Par0\$beta, formula=formula,estAngleMean=list(angle=TRUE)) AICweights(mod1,mod2) Par0nA <- getPar0(mod1,estAngleMean=list(angle=FALSE)) mod3 <- fitHMM(example\$m\$data,nbStates=nbStates,dist=list(step=stepDist,angle=angleDist), Par0=Par0nA\$Par,beta0=Par0nA\$beta, formula=~1) AICweights(mod1,mod2,mod3) # add'l models provided as a list using the !!! operator AICweights(mod1, !!!list(mod2,mod3)) ## End(Not run) ```

momentuHMM documentation built on July 7, 2021, 9:06 a.m.