require(smartwolf)
data(smartwolf2)
analyzeWolf <- function(wolf.data, wolf.zones = NULL, n.zones = NULL, 
                        filename = paste0(ID, ".fit.rda"), 
                        coerce = FALSE, plotzones = FALSE, ...){
  
  try(load(paste0("../results/", filename)))
  
  if(!exists("wolf.fit") | coerce){
      if(is.null(wolf.zones))
        wolf.zones <- createZones(wolf.data, n.zones = n.zones, plotme = plotzones) else 
            n.zones <- length(wolf.zones$zone.polys)
    
      wolf.data$Zone <- wolf.zones$zone.vector
      wolf.fit <- estimateFixedParameters(data = wolf.data, plotme = FALSE, .parallel = TRUE, cluster = cl, ...)
      save(wolf.fit, file = paste0("../results/", filename))
  } 
  
  print(wolf.fit$estimates)
  plotLagTauFits(wolf.fit)
  
  return(wolf.fit)
}

Analyzing Viki:

Viki <- subset(smartwolf, ID == "Viki")

Prepping a bunch of objects:

palette(rich.colors(7))
Viki.4zones <- createZones(Viki, n.zones = 4, plotme = TRUE)
## [1] 1
## [1] 2
## [1] 3
## [1] 4
Viki.5zones <- createZones(Viki, n.zones = 5, plotme = TRUE)
## [1] 1
## [1] 2
## [1] 3
## [1] 4
## [1] 5
Viki.6zones <- createZones(Viki, n.zones = 6, plotme = TRUE)
## [1] 1
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
Viki.7zones <- createZones(Viki, n.zones = 7, plotme = TRUE)

## [1] 1
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
## [1] 7
lags <- seq(2,13,.5)
taus = seq(0.1,3,.2)

Set up parallel processing:

setupParallel <- function(){
  require(doParallel)
  n.clusters <- detectCores()
  cl <- makeCluster(n.clusters)
  registerDoParallel(cl)
  clusterEvalQ(cl, library(smartwolf))
  clusterExport(cl, c("Viki", "Viki.4zones", "Viki.5zones", "Viki.6zones", "Viki.7zones"))
  return(cl)
}
cl <- setupParallel()

4 zones

Exponential

Viki.z4.g1.fit <- analyzeWolf(Viki, Viki.4zones, gamma = 1, filename = "Viki.z4.g1.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 6.7272727 0.9070707  0.5   134.7381 134.3033
## 2 0.9069978 0.5728359   NA         NA       NA
title("4 zones, gamma = 1", outer=TRUE)

Gaussian

Viki.z4.g2.fit <- analyzeWolf(Viki, Viki.4zones, gamma = 2, filename = "Viki.z4.g2.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 6.7272727 1.6707071  0.5   134.7381 133.5951
## 2 0.9069978 0.5622199   NA         NA       NA
title("4 zones, Gaussian", outer=TRUE)

5 zones

Exponential

Viki.z5.g1.fit <- analyzeWolf(Viki, Viki.5zones, gamma = 1, filename = "Viki.z5.g1.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 6.8181818 0.6242424  0.5   157.9584 161.2055
## 2 0.5670938 0.3884279   NA         NA       NA
title("5 zones, gamma = 1", outer=TRUE)

Gaussian

Viki.z5.g2.fit <- analyzeWolf(Viki, Viki.5zones, gamma = 2, filename = "Viki.z5.g2.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 6.8181818 1.3030303  0.5   157.9584 160.9359
## 2 0.5670938 0.5753056   NA         NA       NA
title("5 zones, gamma = 2", outer=TRUE)

6 zones

Exponential

Viki.z6.g1.fit <- analyzeWolf(Viki, Viki.6zones, gamma = 1, filename = "Viki.z6.g1.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 7.0000000 0.6242424  0.5   187.5983 179.0833
## 2 0.7217854 0.1743752   NA         NA       NA
title("6 zones, gamma = 1", outer=TRUE)

Gaussian

Viki.z6.g2.fit <- analyzeWolf(Viki, Viki.6zones, gamma = 2, filename = "Viki.z6.g2.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 7.0000000 1.2181818  0.5   187.5983 177.6719
## 2 0.7217854 0.2243542   NA         NA       NA
title("6 zones, gamma = 1", outer=TRUE)

7 zones

Exponential

Viki.z7.g1.fit <- analyzeWolf(Viki, Viki.7zones, gamma = 1, filename = "Viki.z7.g1.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 6.9090909 0.5959596  0.5    195.754 193.9275
## 2 0.5010358 0.2285884   NA         NA       NA
title("7 zones, gamma = 1", outer=TRUE)

Gaussian

Viki.z7.g2.fit <- analyzeWolf(Viki, Viki.7zones, gamma = 2, filename = "Viki.z7.g2.rda", plotzones = FALSE)
##      lambda       tau beta aic.lambda  aic.tau
## 1 6.9090909 1.1616162  0.5    195.754 193.0045
## 2 0.5010358 0.3830448   NA         NA       NA
title("7 zones, gamma = 1", outer=TRUE)

Summary analysis

n.zones aic.lambda aic.tau.exp aic.tau.gauss lambda.hat tau.exp tau.gauss
4 134.7381 134.3033 133.5951 6.727273 0.9070707 1.670707
5 157.9584 161.2055 160.9359 6.818182 0.6242424 1.303030
6 187.5983 179.0833 177.6719 7.000000 0.6242424 1.218182
7 195.7540 193.9275 193.0045 6.909091 0.5959596 1.161616