utilities (version 0.4.0)

moments: Sample Moments

Description

moments returns the sample moments of a data vector/matrix

Usage

moments(
  x,
  skew.type = NULL,
  kurt.type = NULL,
  kurt.excess = FALSE,
  na.rm = TRUE,
  include.sd = FALSE
)

Arguments

x

A data vector/matrix/list

skew.type

The type of kurtosis statistic used ('Moment', 'Fisher Pearson' or 'Adjusted Fisher Pearson')

kurt.type

The type of kurtosis statistic used ('Moment', 'Fisher Pearson' or 'Adjusted Fisher Pearson')

kurt.excess

Logical value; if TRUE the function gives the excess kurtosis (instead of raw kurtosis)

na.rm

Logical value; if TRUE the function removes NA values

include.sd

Logical value; if TRUE the output includes a column for the sample standard deviation (if needed)

Value

A data frame containing the sample moments of the data vector/matrix

Details

This function computes the sample moments for a data vector, matrix or list (sample mean, sample variance, sample skewness and sample kurtosis). For a vector input the function returns a single value for each sample moment of the data. For a matrix or list input the function treats each column/element as a data vector and returns a matrix of values for the sample moments of each of these datasets. The function can compute different types of skewness and kurtosis statistics using the skew.type, kurt.type and kurt.excess inputs. (For details on the different types of skewness and kurtosis statistics, see Joanes and Gill 1998.)

Examples

# NOT RUN {
#Create some subgroups of mock data and a pooled dataset
set.seed(1)
N    <- c(28, 44, 51)
SUB1 <- rnorm(N[1])
SUB2 <- rnorm(N[2])
SUB3 <- rnorm(N[3])
DATA <- list(Subgroup1 = SUB1, Subgroup2 = SUB2, Subgroup3 = SUB3)
POOL <- c(SUB1, SUB2, SUB3)

#Compute sample moments for subgroups and pooled data
MOMENTS <- moments(DATA)
POOLMOM <- moments(POOL)

#Compute pooled moments via sample decomposition
sample.decomp(moments = MOMENTS)
# }