var2prof: Variables to profiles

In parsec: Partial Orders in Socio-Economics

Variables to profiles

Description

The function computes the list of all of the profiles from a list of input ordinal variables. See details for how to define variables.

Usage

var2prof(varmod = lapply(as.list(varlen), function(x) 1:x),
    varlen = sapply(varmod, length), freq = NULL,
    labtype = c("profiles", "progressive"), y=NULL)

Arguments

varmod	list of variables and their grades. See details.
varlen	a vector of number of grades of each variable. See details.
freq	profiles frequency distribution. By default, the frequencies are set equal to 1.
labtype	type of labels to assign to profiles. See details.
y	a matrix of observations, used to count profiles frequencies. See details.

Details

Variables can be defined through their names and grades, using a list as argument varmod. The names of the objects in the list are taken as variable names. The objects in the list must be ordered vectors or numeric vectors.

A faster way to define variables is through a vector with the number of grades of each variable, as argument varlen. This way, variables and their grades are assigned arbitrary names. In particular, grades are identified by their ranks in the variable definition.

The user can choose the type of label to assign to profiles. profiles is the combination of grades identifying the profiles. When the names of the grades are too long, it is suggested to choose progressive.

y is a matrix of observations on the ordinal variables (observations by rows and variables by columns). Variables must be ordered as defined in the previous arguments. The names of variable grades must match their definition. By this argument, the function counts the number of times a profile is observed in the population, assigning the result to the freq output. This method should be used when the variables and their grades are known, otherwise the function pop2prof is available.

Value

The function returns a S3 class object wprof, "weighted profiles", comprising the data.frame profiles and the vector of frequencies freq.

See Also

pop2prof, getzeta

Examples

# 2 variables with 2 modalities, frequencies detected from population
pop <- matrix(sample(1:2, 100, replace=TRUE), 50, 2)
var2prof(varlen=c(2, 2))

# 2 variables:
# - mood: 2 modalities
# - weather: 3 modalities
# 2*3 profiles and frequencies sampled from a Binomial distribution n = 10, p = 0.5
var <- list(
    mood = ordered(c("bad", "good"), levels = c("bad", "good")),
    weather = ordered(c("rainy", "cloudy", "sunny"), levels = c("rainy", "cloudy", "sunny"))
)
var2prof(var, freq = rbinom(2*3, 10, 0.5), labtype = "progressive")

parsec documentation built on Aug. 19, 2023, 5:07 p.m.