BNP.eq.predict: Prediction step for Bayesian non-parametric model for test...

View source: R/BNP.eq.R

BNP.eq.predictR Documentation

Prediction step for Bayesian non-parametric model for test equating

Description

This function implements the prediction step in the Bayesian non-parametric model for test equating

Usage

BNP.eq.predict(model, from = NULL, into = NULL, alpha = 0.05)

Arguments

model

A 'BNP.eq' object.

from

Numeric. A vector of indices indicating from which patterns equating should be performed. The covariates involved are integrated out.

into

Numeric. A vector of indices indicating into which patterns equating should be performed. The covariates involved are integrated out.

alpha

Numeric. Level of significance for credible bands.

Details

Predictions of the score probability distributions are obtained under the Bayesian nonparametric model and are used to compute the equating function.

Value

A 'BNP.eq.predict' object, which is a list containing the following items:

pdf A list of PDF's.

cdf A list of CDF's.

equ Numeric. Equated values.

grid Numeric. Grid used to evaluate pdf's and cdf's.

Author(s)

Daniel Leon dnacuna@uc.cl, Felipe Barrientos afb26@stat.duke.edu.

References

Gonzalez, J., Barrientos, A., and Quintana, F. (2015). Bayesian Nonparametric Estimation of Test Equating Functions with Covariates. Computational Statistics and Data Analysis, 89, 222-244.


SNSequate documentation built on Dec. 28, 2022, 1:35 a.m.