## 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

 sample1 The first sample of observations under study. sample2 The second sample of observations under study.

### 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']])