summary.sjSDManova | R Documentation |
The function prints and returns invisible a summary table of an sjSDM ANOVA, created by anova.sjSDM
## S3 method for class 'sjSDManova'
summary(
object,
method = c("ANOVA"),
fractions = c("all", "discard", "proportional", "equal"),
...
)
object |
an object of |
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 |
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:
"all" returns the shared fractions explicitly
"discard" discards the fractions, as typically in a type II Anova
"proportional" distributes shared fractions proportional to the unique fractions
"equal" distributions shared fractions equally to the unique fractions
The matrix that is printed out is silently returned
## Not run:
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))))
## End(Not run)
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