| AIC.momentuHMM {momentuHMM} | R Documentation | 
AIC
Description
Akaike information criterion of momentuHMM model(s).
Usage
## S3 method for class 'momentuHMM'
AIC(object, ..., k = 2, n = NULL)
Arguments
| object | A  | 
| ... | Optional additional  | 
| k | Penalty per parameter. Default: 2 ; for classical AIC. | 
| n | Optional sample size. If specified, the small sample correction AIC is used (i.e.,  | 
Value
The AIC of the model(s) provided. If several models are provided, the AICs are output in ascending order.
Examples
# m is a momentuHMM object (as returned by fitHMM), automatically loaded with the package
m <- example$m
AIC(m)
## 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))
                
AIC(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)
 
AIC(mod1,mod2,mod3)
# add'l models provided as a list using the !!! operator                              
AIC(mod1, !!!list(mod2,mod3))
## End(Not run)
[Package momentuHMM version 1.5.5 Index]