kmo {FactorAssumptions}

Calculates the Kayser-Meyer-Olkin (KMO)

Description

kmo() handles both positive definite and not-positive definite matrix by employing the Moore-Penrose inverse (pseudoinverse)

Usage

kmo(x, squared = TRUE)

Arguments

x

a matrix or dataframe

squared

TRUE if matrix is squared (such as adjacency matrices), FALSE otherwise

Value

A list with

1. overall - Overall KMO value

2. individual - Individual KMO's dataframe

3. AIS - Anti-image Covariance Matrix

4. AIR - Anti-image Correlation Matrix

Examples

set.seed(123)
df <- as.data.frame(matrix(rnorm(100*10, 1, .5), ncol=10))
kmo(df, squared = FALSE)