Calculate data to construct partial dependence plots

Usage

data_abund_pdp(
  model,
  predictors,
  resolution = 50,
  resid = FALSE,
  training_data = NULL,
  invert_transform = NULL,
  response_name = NULL,
  projection_data = NULL,
  sample_size = c(11, 11),
  training_raster = NULL,
  x_coord = NULL,
  y_coord = NULL
)

Arguments

model

object returned by any fit_abund or tune_abund family functions

predictors

character. Vector with two predictor name(s) to plot. If NULL all predictors will be plotted. Default NULL

resolution

numeric. Number of equally spaced points at which to predict continuous predictors. Default 50

resid

logical. Calculate residuals based on training data. Default FALSE

training_data

data.frame. Database with response and predictor values used to fit a model. Default NULL. Required for GLM, GAM, DNN, NET, RAF, SVM models

invert_transform

vector. A vector containing method and terms to invert transformation of response variable. Useful for those cases that the response variable was transformed with one of the method in adm_transform. Usage:

For "01": invert_transform = c(method = "01", a = min(x), b = max(x))
For "zscore": invert_transform = c(method = "zscore", a = mean(x), b = sd(x))
For "log" and "log1: not needed.
Can't invert "round" transformations.
Default NULL

response_name

character. Name of the response variable. Default NULL

projection_data

SpatRaster. Raster layer with environmental variables used for model projection. When this argument is used, function will calculate partial dependence curves distinguishing conditions used in training and projection conditions (i.e., projection data present in projection area but not training). Default NULL

sample_size

vector. For CNN only. A vector containing the dimensions, in pixels, of raster samples. See cnn_make_samples beforehand. Default c(11,11)

training_raster

a terra SpatRaster object. For CNN only. A raster containing the predictor variables used in tune_abund_cnn or fit_abund_cnn.

x_coord

character. For CNN only. The name of the column containing longitude information for each observation.

y_coord

character. For CNN only. The name of the column containing latitude information for each observation.

Value

A list with two tibbles "pdpdata" and "resid".

pdpdata: has data to construct partial dependence plots, the first column includes values of the selected environmental variable, the second column with predicted suitability, and the third column with range type, with two values Training and Projecting, referring to suitability calculated within and outside the range of training conditions. Third column is only returned if "projection_data" argument is used
resid: has data to plot residuals. The first column includes values of the selected environmental variable and the second column with predicted suitability.

Examples

if (FALSE) {
require(dplyr)
require(terra)

# Load  data
envar <- system.file("external/envar.tif", package = "adm") %>%
  rast()

data("sppabund")
some_sp <- sppabund %>%
  filter(species == "Species one")

# Fit some models
mglm <- fit_abund_glm(
  data = some_sp,
  response = "ind_ha",
  predictors = c("bio12", "elevation", "sand"),
  predictors_f = c("eco"),
  partition = ".part",
  distribution = "ZAIG",
  poly = 3,
  inter_order = 0,
  predict_part = TRUE
)

# Prepare data for Partial Dependence Plots
pdp_data <- data_abund_pdp(
  model = mglm,
  predictors = "bio12",
  resolution = 25,
  resid = TRUE,
  training_data = some_sp,
  response_name = "Abundance",
  projection_data = envar
)

pdp_data
}

Calculate data to construct partial dependence plots

Usage

Arguments

Value

See also

Examples