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#
# StartingParams.R
# Version 1.2
# 18/08/2016
#
# Updates:
# 18/08/2016: names of starting parameters harmonised with paper
# 30/01/2015: Thomas model added
#
# Dataframes containing the starting parameters for the optimisation procedure
# fitting model parameters to observed coarse-scale occupancy data:
# Nachman Nachman model
# PL Power Law model
# Logis Logistic model
# Poisson Poisson model
# NB Negative binomial model
# GNB Generalised negative binomial model
# INB Improved negative binomial model
# FNB Finite negative binomial model
# Thomas Thomas model
#
################################################################################
### Nachman model
ParamsNachman <- data.frame("C" = 0.01, "z" = 0.01)
### Power Law model
ParamsPL <- data.frame("C" = 0.01, "z" = 0.01)
### Logistic model
ParamsLogis <- data.frame("C" = 0.01, "z" = 0.01)
### Poisson model
ParamsPoisson <- data.frame("gamma" = 1e-8)
### Negative binomial model
ParamsNB <- data.frame("gamma" = 0.01, "k" = 0.01)
### Generalised negative binomial model
ParamsGNB <- data.frame("C" = 0.00001, "z" = 1, "k" = 0.01)
### Improved negative binomial model
ParamsINB <- data.frame("C" = 1, "gamma" = 0.01, "b" = 0.1)
### Finite negative binomial model
ParamsFNB <- data.frame("N" = 10, "k" = 10)
### Thomas model
ParamsThomas <- data.frame("rho" = 1e-8, "mu" = 10,"sigma" = 1)
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