kmo: Kaiser Meyer Olkin Sampling Adequacy Index
In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities
Description
Usage
Arguments
Value
Description
Kaiser Meyer Olkin Sampling Adequacy Index
Usage
1
Arguments
x
a data frame or matrix of numeric variables
rho
a custom correlation or covariance matrix if one is so desired
(ie one of the robust estimators). if left as NULL the pearson correlation
matrix is calculated.
Value
a list containing the measure of sampling adequacy for each variable, the KMO
index for overall adequacy, and the Lederman bound which defines the maximum number of
latent variables that can be extracted.
abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.
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Description Usage Arguments Value
Description
Kaiser Meyer Olkin Sampling Adequacy Index
Usage
1 |
Arguments
x |
a data frame or matrix of numeric variables |
rho |
a custom correlation or covariance matrix if one is so desired (ie one of the robust estimators). if left as NULL the pearson correlation matrix is calculated. |
Value
a list containing the measure of sampling adequacy for each variable, the KMO index for overall adequacy, and the Lederman bound which defines the maximum number of latent variables that can be extracted.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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