singleRcapture (version 0.2.3)

summary.singleRmargin: Statistical tests of goodness of fit

Description

Performs two statistical test on observed and fitted marginal frequencies. For G test the test statistic is computed as:

G = 2_kO_k(O_kE_k) and for ^2 the test statistic is computed as: ^2 = _k(O_k-E_k)^2E_k where O_k,E_k denoted observed and fitted frequencies respectively. Both of these statistics converge to ^2 distribution asymptotically with the same degrees of freedom.

The convergence of G, ^2 statistics to ^2 distribution may be violated if expected counts in cells are too low, say < 5, so it is customary to either censor or omit these cells.

Usage

# S3 method for singleRmargin
summary(object, df, dropl5 = c("drop", "group", "no"), ...)

Value

A chi squared test and G test for comparison between fitted and observed marginal frequencies.

Arguments

object

object of singleRmargin class.

df

degrees of freedom if not provided the function will try and manually but it is not always possible.

dropl5

a character indicating treatment of cells with frequencies < 5 either grouping them, dropping or leaving them as is. Defaults to drop.

...

currently does nothing.

Examples

# Create a simple model
Model <- estimatePopsize(
  formula = capture ~ ., 
  data = netherlandsimmigrant, 
  model = ztpoisson, 
  method = "IRLS"
)
plot(Model, "rootogram")
# We see a considerable lack of fit
summary(marginalFreq(Model), df = 1, dropl5 = "group")