island (version 0.2.4)

all_environmental_fit: Environmental fit for a single dataset

Description

all_environmental_fit estimates the best expressions for colonization and extinction rates given their dependency on environmental variables. greedy_environmental_fit estimates expressions for colonization and extinction rates given their dependency on environmental variables using a greedy algorithm. custom_environmental_fit estimates the m.l.e. of the parameters describing the relationship between colonization and extinction rates and environmental variables. NLL_env returns the Negative Log-Likelihood of a pair of colonization and extinction rates for a given dataset with an specific relationship with environmental variables.

Usage

all_environmental_fit(dataset, vector, env, c, e, aic, verbose = F)
custom_environmental_fit(dataset, vector, params, c_expression,
  e_expression)
NLL_env(dataset, vector, params, c_expression, e_expression)
greedy_environmental_fit(dataset, vector, env, c, e, aic, verbose = F)

Arguments

dataset

A single dataset.

vector

A vector indicating the columns with presence-absence data.

env

The names of the environmental variables to be considered.

c

Tentative colonization rate.

e

Tentative extinction rate.

aic

Tentative AIC to be improved by the optimizer.

verbose

Logical. Do you want to get the intermediate steps looking for the best model?

params

A vector with priors of the parameters in c_expression and e_expression.

c_expression

Expression for colonization.

e_expression

Expression for extinction.

Value

A list with three components: a expression for colonization, a expression for extinction and the output of the optimization function, or the output of the optimization function in the custom environmental fit. In the case of NLL_env, returns the NLL of an specific set or parameters describing the relationship of environmental covariates with colonizaiton and extinction.

Details

all_environmental_fit calculates all the combinations of parameters, that increase exponentially with the number of parameters. We advise to keep low the number of parameters. greedy_environmental_fit adds sequentially environmental variables to the expressions of colonization and extinction rates and fix one at a time until termination, when only adding one variable does not improve the AIC of the last accepted model.

See Also

rates_calculator

Examples

# NOT RUN {
all_environmental_fit(idaho[[1]],3:23,c("idaho[[2]]$TOTAL.ppt",
"idaho[[2]]$ANNUAL.temp"),0.13,0.19,100000)
greedy_environmental_fit(idaho[[1]],3:23,c("idaho[[2]]$TOTAL.ppt",
"idaho[[2]]$ANNUAL.temp"),0.13,0.19,100000)
# }
# NOT RUN {
custom_environmental_fit(idaho[[1]], 3:23, c(-0.00497925, -0.01729602,
0.19006501, 0.93486956), expression(params[1] * idaho[[2]]$TOTAL.ppt[i] +
params[3]), expression(params[2] * idaho[[2]]$ANNUAL.temp[i] + params[4]))
NLL_env(idaho[[1]], 3:23, c(-0.00497925, -0.01729602,
0.19006501, 0.93486956), expression(params[1] * idaho[[2]]$TOTAL.ppt[i] +
params[3]), expression(params[2] * idaho[[2]]$ANNUAL.temp[i] + params[4]))

# }