miic.evaluate.effn: Evaluate the effective number of samples

Description Usage Arguments Value

View source: R/evaluate_efn.R

Description

This function evaluates the effective number of samples in a dataset.

Usage

1
miic.evaluate.effn(inputData = NULL, plot = T)

Arguments

inputData

[a data frame] A data frame that contains the observational data. Each column corresponds to one variable and each row is a sample that gives the values for all the observed variables. The column names correspond to the names of the observed variables. Data must be discrete like.

plot

[a boolean value] if the autocorrelation plot has to be done. It will be performed only if all values of the correlation vector are positive.

Value

A list containing the autocorrelation decay, the effective number of samples, and the result of an exponentiality test with alpha = 0.05


miic documentation built on Feb. 2, 2018, 5:03 p.m.