sjSDM (version 1.0.6)

summary.sjSDManova: Summary table of sjSDM anova

Description

The function prints and returns invisible a summary table of an sjSDM ANOVA, created by anova.sjSDM

Usage

# S3 method for sjSDManova
summary(
  object,
  method = c("ANOVA"),
  fractions = c("all", "discard", "proportional", "equal"),
  ...
)

Value

The matrix that is printed out is silently returned

Arguments

object

an object of anova.sjSDM

method

method used to calculate the ANOVA

fractions

how to handle the shared fractions. See details

...

optional arguments for compatibility with the generic function, no function implemented

Details

The function returns a ANOVA table with Deviance as well as the pseudo-R2 metrics of Nagelkerke and McFadden

There are four options to handle shared ANOVA fractions, which is variance that can be explained, typically as a result of collinearity, by several of the fractions:

1. "all" returns the shared fractions explicitly

2. "discard" discards the fractions, as typically in a type II Anova

3. "proportional" distributes shared fractions proportional to the unique fractions

4. "equal" distributions shared fractions equally to the unique fractions

Examples

if (FALSE) {
library(sjSDM)
# simulate community:
community = simulate_SDM(env = 3L, species = 10L, sites = 100L)

Occ <- community$response
Env <- community$env_weights
SP <- data.frame(matrix(rnorm(200, 0, 0.3), 100, 2)) # spatial coordinates


# fit model:
model <- sjSDM(Y = Occ, 
               env = linear(data = Env, formula = ~X1+X2+X3), 
               spatial = linear(data = SP, formula = ~0+X1*X2), 
               family=binomial("probit"),
               verbose = FALSE,
               iter = 20) # increase iter for real analysis

# Calculate ANOVA for env, space, associations, for details see ?anova.sjSDM
an = anova(model, samples = 10, verbose = FALSE) # increase iter for real analysis

# Show anova fractions
plot(an)

# ANOVA tables with different way to handle fractions
summary(an)
summary(an, fractions = "discard")
summary(an, fractions = "proportional")
summary(an, fractions = "equal")

# Internal structure
int = internalStructure(an, fractions = "proportional")

print(int)

plot(int) # default is negative values will be set to 0
plot(int, negatives = "scale") # global rescaling of all values to range 0-1
plot(int, negatives = "raw") # negative values will be discarded

plotAssemblyEffects(int)
plotAssemblyEffects(int, negatives = "floor")
plotAssemblyEffects(int, response = "sites", pred = as.factor(c(rep(1, 50), rep(2, 50))))
plotAssemblyEffects(int, response = "species", pred = runif(10))
plotAssemblyEffects(int, response = "species", pred = as.factor(c(rep(1, 5), rep(2, 5))))
}