dataSDA (version 0.1.8)

interval_uncertainty: Uncertainty and Variability Measures for Interval Data

Description

Functions to compute uncertainty and variability measures for interval-valued data.

Usage

int_entropy(x, var_name, method = "CM", base = 2, ...)
int_cv(x, var_name, method = "CM", ...)
int_dispersion(x, var_name, method = "CM", ...)
int_imprecision(x, var_name, ...)
int_granularity(x, var_name, ...)
int_uniformity(x, var_name, ...)
int_information_content(x, var_name, method = "CM", ...)

Value

A numeric matrix or value

Arguments

x

interval-valued data with symbolic_tbl class.

var_name

the variable name or the column location (multiple variables are allowed).

method

methods to calculate statistics: CM (default), VM, QM, SE, FV, EJD, GQ, SPT.

base

logarithm base for entropy calculation (default: 2)

...

additional parameters

Author

Han-Ming Wu

Details

These functions measure uncertainty and variability:

• int_entropy: Shannon entropy (information content)

• int_cv: Coefficient of variation (CV = SD / Mean)

• int_dispersion: General dispersion index

• int_imprecision: Imprecision based on interval width

• int_granularity: Variability in interval sizes

See Also

int_var int_entropy int_cv

Examples

data(mushroom.int)

# Calculate entropy
int_entropy(mushroom.int, var_name = "Pileus.Cap.Width")

# Coefficient of variation
int_cv(mushroom.int, var_name = c("Stipe.Length", "Stipe.Thickness"), method = c("CM", "EJD"))

# Measure imprecision
int_imprecision(mushroom.int, var_name = c("Stipe.Length", "Stipe.Thickness"))

# Check data granularity
int_granularity(mushroom.int, var_name = 2:4)