Detect the support of the random variables under study

Description

Given one or two sets of observations (two samples), the function provides with the most plausible type of support for the underlying random variables to be studied. Basically, if less than 3 percent of the observations have different values, we consider that the support is discrete. Otherwise, we consider it as a continuous support.

Usage

detect_support_type(sample1, sample2 = NULL)

Arguments

Value

The type of support, either discrete or continuous.

Author(s)

Xavier Milhaud xavier.milhaud.research@gmail.com

Examples

## Simulate the two mixture samples:
list.comp <- list(f1 = 'norm', g1 = 'norm',
                  f2 = 'norm', g2 = 'norm')
list.param <- list(f1 = list(mean = 3, sd = 0.5), g1 = list(mean = 0, sd = 1),
                    f2 = list(mean = 1, sd = 0.1), g2 = list(mean = 5, sd = 2))
sample1 <- rsimmix(n=1500, unknownComp_weight=0.5, comp.dist = list(list.comp$f1,list.comp$g1),
                   comp.param=list(list.param$f1,list.param$g1))
sample2 <- rsimmix(n=2000, unknownComp_weight=0.7, comp.dist = list(list.comp$f2,list.comp$g2),
                   comp.param=list(list.param$f2,list.param$g2))
## Test the type of support:
detect_support_type(sample1[['mixt.data']], sample2[['mixt.data']])