model.apply: Apply any function over models

In wilsonfrantine/landscapeDecoupler: Landscape Decoupler: Tools for Multi-scale Landscape Analysis

Apply any function over models

Description

this function allow users to apply any function over models nested in tibbles as the output of the fitscales() function. Users may use this function to retrieve model info, as using summary, or apply their own personalized functions over the models. The function will return a similar tibble to the input table, but with an extra column with the result of the function applied.

Usage

model.apply(fun, data, result_to = NULL)

Arguments

fun	vector. The name of a function to be applied. Any function that can handle model objects are allowed, specially tidy(), glance(), augment() from broom, broom.mixed and broomExtra packages. Custom functions are also allowed, but they have to be loaded in the environment space.
data	a tibble. An output from fitscales function
result_to	the new collumn name. It is optional. If null, the new collumn name will be 'model.'+fun

Details

This function was designed to help users expanding the possibility in handle data from model objects, specially for those not covered by broom API. The package broom.mixed can be used to handle mixed models. Users only need to install and library the package, so the functions tidy, glance, and augment will be also applied for packages like 'lme4' and others.

See Also

fitscales() calc_lsm() decouple() nestedscales()

Examples

## Not run: 
ls <- decouple(r,p,c(1000,2000,3000))
lsm <- calc_lsm(ls, c("pland","shdi"))
models <- fitscales(lsm, bio=euglossini, model="lm")
model.apply("summary",models, result_to="mod.summ")

## End(Not run)

wilsonfrantine/landscapeDecoupler documentation built on Oct. 31, 2024, 3:45 a.m.