moments | R Documentation |
moments
returns the sample moments of a data vector/matrix
moments( x, skew.type = NULL, kurt.type = NULL, kurt.excess = FALSE, na.rm = TRUE, include.sd = FALSE )
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 |
na.rm |
Logical value; if |
include.sd |
Logical value; if |
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.)
A data frame containing the sample moments of the data vector/matrix
#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)
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