Esimating parameters for all wolves

Extract all wolves

Viki <- subset(smartwolf, ID == "Viki")
Niki <- subset(smartwolf, ID == "Niki")
Miki <- subset(smartwolf, ID == "Miki")
LU <- subset(smartwolf, ID == "LentuanUros")
YN <- subset(smartwolf, ID == "YlaneNaaras")
H11 <- subset(smartwolf, ID2 == "Hessu 2011")
H13 <- subset(smartwolf, ID2 == "Hessu 2013")
Julla <- subset(smartwolf, ID == "Julla")
Vellu <- subset(smartwolf, ID == "Vellu")

Viki

##       lamda       tau beta
## 1 6.9090909 0.5959596  0.5
## 2 0.5826038 0.2124502   NA

Niki

##       lamda       tau beta
## 1 11.181818 1.0484848  0.5
## 2  1.177185 0.4674299   NA

Miki

##       lamda       tau beta
## 1 12.000000 1.0767677  0.5
## 2  3.271754 0.4987696   NA

Julla

n.zones <- 5
try(load("../results/Julla.fit.robj"))
Julla$Zone <- createZones(Julla, n.zones = n.zones, plotme = TRUE, plotboth = FALSE)
if(!exists("Julla.fit")){
  Julla.fit <- estimateFixedParameters(data = Julla)
  save(Julla.fit, file = "../results/Julla.fit.robj")
} else {
  print(Julla.fit$estimates)
  plotLagTauFits(Julla.fit)
}

##      lamda       tau beta
## 1 7.818182 2.0383838  0.5
## 2 1.327486 0.9428568   NA

Vellu

n.zones <- 5
try(load("../results/Vellu.fit.robj"))
Vellu$Zone <- createZones(Vellu, n.zones = n.zones, plotme = TRUE, plotboth = FALSE)
if(!exists("Vellu.fit")){
  Vellu.fit <- estimateFixedParameters(data = Vellu, lags = seq(4,10,.5,), taus = seq(0.5,2,.1))
  save(Vellu.fit, file = "../results/Vellu.fit.robj")
} else {
  print(Vellu.fit$estimates)
  plotLagTauFits(Vellu.fit)
}

##       lamda      tau beta
## 1 8.5454545 1.424242  0.5
## 2 0.7344446 1.117203   NA

Hessu 2011

n.zones <- 4
H11$Zone <- createZones(H11, n.zones = n.zones, plotme = TRUE, plotboth = FALSE)
try(load("../results/H11.fit.robj"))
if(!exists("H11.fit")){
  H11.fit <- estimateFixedParameters(data = H11, lags = seq(2,9,.5), taus = seq(.5,3,.2))
  save(H11.fit, file = "../results/H11.fit.robj")
} else {
  print(H11.fit$estimates)
  plotLagTauFits(H11.fit)
}

##      lamda       tau beta
## 1 5.323232 1.3000000  0.5
## 2 1.068787 0.9548492   NA

Hessu 2013

n.zones <- 4
H13$Zone <- createZones(H13, n.zones = n.zones, plotme = TRUE, plotboth = FALSE)
try(load("./results/H13.fit.robj"))
if(!exists("H13.fit")){
  H13.fit <- estimateFixedParameters(data = H13, lags = seq(2,9,.5), taus = seq(.5,3,.2))
  save(H13.fit, file = "../results/H13.fit.robj")
} else {
  print(H13.fit$estimates)
  plotLagTauFits(H13.fit)
}

## 
##  1. Estimating best lambdas (span = 0.5)

## 
##  estimate: lambda = 8.363636 (sd = 0.6718646)
## 
##  2. Estimating tau_p (at beta = 0.5)

## 
##  estimate: tau_p = 2.633333 (sd = 3.487781)
## 
##  3. Not bothering to estimate beta, fixed at 0.5

Lentuan Uros

n.zones <- 4
LU$Zone <- createZones(LU, n.zones = n.zones, plotme = TRUE, plotboth = FALSE)
try(load("../results/LU.fit.robj"))
if(!exists("LU.fit")){
  LU.fit <- estimateFixedParameters(data = LU, lags = seq(1,9,.5), taus = seq(.5,3,.2))
  save(LU.fit, file = "../results/LU.fit.robj")
} else {
  print(LU.fit$estimates)
  plotLagTauFits(LU.fit)
}

##      lamda      tau beta
## 1 2.373737 1.833333  0.5
## 2 1.525068 1.839123   NA

Ylane Naaras

n.zones <- 4
YN$Zone <- createZones(YN, n.zones = n.zones, plotme = TRUE, plotboth = FALSE)
try(load("../results/YN.fit.robj"))
if(!exists("YN.fit")){
  YN.fit <- estimateFixedParameters(data = YN, lags = seq(1,9,.5), taus = seq(.1,2,.2))
  save(YN.fit, file = "../results/YN.fit.robj")
} else {
  print(YN.fit$estimates)
  plotLagTauFits(YN.fit)
}

##   lamda      tau beta
## 1     9 0.100000  0.5
## 2   NaN 5.651853   NA