observedmoments: Compute Moments of Observed Value Distribution.

In betafunctions: Functions for Working with Two- And Four-Parameter Beta Probability Distributions and Psychometric Analysis of Classifications

Compute Moments of Observed Value Distribution.

Description

Computes Raw, Central, or Standardized moment properties of a vector of observed scores.

Usage

observedmoments(
  x,
  type = c("raw", "central", "standardized"),
  orders = 4,
  correct = TRUE
)

Arguments

x	A vector of values, the distribution of which moments are to be calculated.
type	A character vector determining which moment-types are to be calculated. Permissible values are "raw", "central", and "standardized".
orders	The number of moment-orders to be calculated for each of the moment-types.
correct	Logical. Whether to include bias correction in estimation of orders. Default is TRUE.

Value

A list of moment types, each a list of moment orders.

Examples

# Generate some fictional data. Say, 100 individuals take a test with a
# maximum score of 100 and a minimum score of 0.
set.seed(1234)
testdata <- rbinom(100, 100, rBeta.4P(100, 0.25, 0.75, 5, 3))
hist(testdata, xlim = c(0, 100))

# To compute the first four raw, central, and standardized moments for this
# distribution of observed scores using observedmoments():
observedmoments(x = testdata, type = c("raw", "central", "standardized"),
orders = 4, correct = TRUE)

betafunctions documentation built on May 29, 2024, 1:13 a.m.