explore: Exploration

In psolymos/moosecounter: Adaptive Moose Surveys

Exploration

Description

Functions to explore relationships between total Moose or composition as response vs. environmental predictor variables.

Usage

mc_plot_univariate(
  i,
  x,
  dist = "ZINB",
  base = TRUE,
  type = c("density", "map", "fit"),
  interactive = FALSE
)

mc_plot_multivariate(vars, x, alpha = NULL)

mc_plot_comp(i, x)

Arguments

i	Column name from 'x' to be used as a predictor.
x	Data frame with Moose data.
dist	Count distribution ('P', 'NB', 'ZIP', or 'ZINB').
base	Logical, draw base graphics or ggplot2.
type	Character, type of plot to be drawn ('"density"', '"map"', '"fit"'). Base plot can draw all 3, ggplot2 can only draw one at a time.
interactive	Logical, draw interactive plot (not available for base plots).
vars	A vector of column names from 'x' to be used as a predictor.
alpha	Alpha level defining 'mincriterion = 1 - alpha' for 'partykit::ctree()'.

Details

'mc_plot_univariate' implements visual univariate (single predictor) exploration for the total Moose count models.

'mc_plot_multivariate' implements visual multivariate (multiple predictors) exploration based on regression trees (recursive partitioning in a conditional inference framework) for total Moose counts.

'mc_plot_comp' implements visual univariate (single predictor) exploration for the multinomial composition models.

Examples

## Prepare Moose data from Mayo
x <- read.csv(
    system.file("extdata/MayoMMU_QuerriedData.csv",
        package="moosecounter"))
switch_response("total")
x <- mc_update_total(x)

## Univariate exploration for total Moose
mc_plot_univariate("Subalp_Shrub_250buf", x, "ZINB")

## Multivariate exploration for total Moose
vars <- c("ELC_Subalpine", "Fire1982_2012", "Fire8212_DEM815",
    "NALC_Needle", "NALC_Shrub", "Subalp_Shrub_250buf",
    "ELCSub_Fire8212DEM815", "SubShrub250_Fire8212DEM815")
mc_plot_multivariate(vars, x)

## Univariate exploration for composition
mc_plot_comp("Fire8212_DEM815", x)

psolymos/moosecounter documentation built on Feb. 25, 2024, 4:43 p.m.