gendis: Calculates a generalized discriminant function

In CajoterBraak/Gendis2unmix: Calculates a generalized discriminant function to unmix two classes, typically sexes of birds

Calculates a generalized discriminant function

Description

gendis calculates a generalized discriminant function to distinguish two classes, typically sexes (male and female birds) based on measurements of a number of indicators for individuals from each of the two sexes from a series of different populations in which individuals may have a different mean size but a common-within covariance matrix.

Usage

gendis(
  population = "population",
  sex = "sex",
  measurements = "other_variables",
  verbose = FALSE,
  data
)

Arguments

population	a name of the variable for the populations in the data (default "population")
sex	a name of the variable indicating the two classes to distinguish in the data (default "sex") (0 vs 1 or "female" vs "male")
measurements	character ("other_variables", default) or character vector with names of measurement variables. gendis maintains the order of the names.
verbose	logical (default = FALSE)
data	data frame with variables

Value

An object of class gendis which is a named list, among which,

population	name of variable indicating populations
sex	name of variable indicating the two sexes or classes
classnames	names for the classes of sex (level or value)
measurements	names of the variables in the GDF
GDF	the Generalized Discriminant Function, matrix with two columns differing in scaling of the GDF
mean.male	overall mean of males (the second level of factor(sex))
mean.female	overall mean of females (the first level of factor(sex))
within.sd	overall within standard deviation
cov_overall	overall within-group covariance matrix
means.male	mean of males per population
means.female	mean of females per population
within.sds	within standard deviation per population
ind_mv	number of males and females per population
cov_list	within-group covariance matrix per population
Nind	number of individuals
Np	number of populations

References

van Franeker, J A. ter Braak, C J F. 1993. A generalized discriminant for sexing fulmarine petrels from external measurements. The Auk 110: pp 492-502, https://doi.org/10.2307/4088413 https://edepot.wur.nl/249350

See Also

predict.gendis, summary.gendis, print.gendis.

Examples

data("fulmarin")
names(fulmarin)
result <- gendis(population = "population", sex = "sex",
                 measurements = "other_variables", verbose = FALSE ,  data=fulmarin )
result$GDF
summary(result)
print(result)

# populations may have names:
fulmarin$pop <- factor(c("a1","a2","a3","a4","a5","a6")[fulmarin$population])
levels(fulmarin$pop)
names(fulmarin)
result2 <- gendis(population = "pop", sex = "sex",
                  measurements = c("HB","BD2","TL","CL"), verbose = FALSE ,  data=fulmarin )
# all equal should not give numeric differences.
#all.equal(result, result2)

result2$GDF - result$GDF

CajoterBraak/Gendis2unmix documentation built on Aug. 5, 2023, 1:36 p.m.