generate_vital_rate_coefs: Generate coefficients for obtaining vital rates

View source: R/generate_vital_rate_coefs.R

generate_vital_rate_coefsR Documentation

Generate coefficients for obtaining vital rates

Description

Any vital rate is a function of several parameters, potentially including interactions or environmental effects. This function generates the coefficients for these parameters, so that users do not have to introduce them all manually in a 'param' list. Coefficients can be generated from a random sampling of a normal distribution with specified mean and standard deviation, or they can be retrieved from a model object that accepts a 'tidy' function from the broom/broom.mixed packages. This is because coefficients for vital rates can be understood as coefficients from statistical regressions.

Usage

generate_vital_rate_coefs(
  param,
  sp = NULL,
  sites = NULL,
  vital.rate = NULL,
  vr.coef = NULL,
  mean.coef = NULL,
  sd.coef = NULL,
  glm.object = NULL,
  glm.coef.equivalence = NULL
)

Arguments

param

the original list with the structure of species, sites, vital rates to calculate, and parameters affecting them. See the function 'build_param'

sp

number or character of the species to calculate coefficients for. If empty, all species are assumed.

sites

number or character of the sites to calculate coefficients for. If empty, all sites are assumed.

vital.rate

character giving the vital rate to calculate coefficients for. If empty, all vital rates are assumed.

vr.coef

character giving a specific coefficient to calculate. If empty, all coefficients are assumed.

mean.coef

optional numeric value, mean for sampling coefficient values

sd.coef

optional numeric value, standard deviation for sampling coefficient values

glm.object

optional model object/coef table

glm.coef.equivalence

if a glm table is provided and its names differ from the 'param' data structure, you can include a named list in which names are the names from 'param' and its elements are the equivalent names from the glm table

Details

In the current version, we assume that the model coefficients come from a logistic regression with binomial family. Otherwise, the function will probably not fail, but the coefficients will not be interpretable and the results in terms of obtaining the actual vital rates from these will be meaningless.

Also note that you need to take care manually of the signs of the coefficients, if entered through mean/sd pairs.

Value

the updated parameter list


RadicalCommEcol/cxr documentation built on Oct. 29, 2023, 10:07 p.m.