pred.error.bands: Prediction uncertainty

In vitaliskim/msco: Multi-Species Co-Occurrence Analyses

Prediction uncertainty

Description

This function plots the response curves showing the effect of the predictors (i.e. trait-based and neutral forces) on joint occupancy as the response variable, with prediction error bands (as the standard deviation from the mean of the response variable) for all orders of joint occupancy.

Usage

pred.error.bands(
  s.data,
  t.data,
  p.d.mat,
  metric = "Simpson_eqn",
  gbsm.model,
  d.f = 4,
  simm = 10,
  orders,
  degree = 3,
  n = 1000,
  max.vif = 40,
  max.vif2 = 30,
  start.range = c(-0.1, 0)
)

Arguments

s.data	A species-by-site presence/absence data.frame with entries indicating occurrence (1) and non-occurrence (0) of species in a site.
t.data	A data.frame with traits as columns and species as rows. The species must be the same as in s.data.
p.d.mat	A symmetric matrix with dimnames as species and entries indicating the phylogenetic distance between any two of them (species).
metric	As for gbsm_m.orders.
gbsm.model	As for gbsm_m.orders.
d.f	As for gbsm_m.orders.
simm	Number of Monte Carlo simulations performed
orders	As for gbsm_m.orders
degree	As for gbsm_m.orders.
n	As for gbsm_m.orders.
max.vif	As for gbsm.
max.vif2	As for gbsm.
start.range	As for gbsm_m.orders.

Value

pred.error.bands function returns:

predictors	a data.frame of predictors
responses	a data.frame of response values of predictors
responses.sim_stats	a data.frame of the reponses' mean and standard deviation (from simm replicates), and

• the response curves with prediction error bands for all orders of joint occupancy

References

1. Lagat, V. K., Latombe, G. and Hui, C. (2021a). A multi-species co-occurrence index to avoid type II errors in null model testing. DOI: ⁠<To be added>⁠.

2. Lagat, V. K., Latombe, G. and Hui, C. (2021b). Dissecting the effects of random encounter versus functional trait mismatching on multi-species co-occurrence and interference with generalised B-spline modelling. DOI: ⁠<To be added>⁠.

Examples

## Not run: 
 my.path <- system.file("extdata/gsmdat", package = "msco")
 setwd(my.path)
 s.data <- get(load("s.data.csv")) ## Species-by-site matrix
 t.data <- get(load("t.data.csv")) ## Species-by-Trait matrix
 p.d.mat <- get(load("p.d.mat.csv")) ## Species-by-species phylogenetic distance matrix

 RNGkind(sample.kind = "Rejection")
 set.seed(1)
 pe <- msco::pred.error.bands(s.data, t.data, p.d.mat, metric="Simpson_eqn", d.f=4, simm=10,
  orders = c(2:5, 8, 10, 15), degree=3, n=1000, gbsm.model, start.range=c(-0.2, 0))

 pe$predictors$`order 2`
 pe$responses$`order 2`
 pe$responses.sim_stats$`order 2`

 pe$predictors$`order 3`
 pe$responses$`order 3`
 pe$responses.sim_stats$`order 3`

 pe$predictors$`order 10`
 pe$responses$`order 10`
 pe$responses.sim_stats$`order 10`

 
## End(Not run)

vitaliskim/msco documentation built on Sept. 29, 2023, 9:22 p.m.