to_latent: The Function for Transforming Qualitative/Categorical...

In LVGP: Latent Variable Gaussian Process Modeling with Qualitative and Quantitative Input Variables

Description

Transforms qualitative/categorical variables into latent variables.

Usage

to_latent(X_qual, lvs_qual, n_lvs_qual, p_qual, z_vec, dim_z, k)

Arguments

X_qual	Matrix or data frame containing (only) the qualitative/categorical data.
lvs_qual	List containing levels of each qualitative variable
n_lvs_qual	Number of levels of each qualitative variable
p_qual	Number of qualitative variables
z_vec	Latent variable parameters, i.e., latent variable values for each level of qualitative/categorical variables
dim_z	Dimensionality of latent variables, usually 1 or 2
k	Number of data points, equal to nrow(X_qual)

Value

Matrix containing transformed data

Note

This function is NOT exported once the LVGP package is loaded.

References

1. "A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors", Yichi Zhang, Siyu Tao, Wei Chen, and Daniel W. Apley (arXiv)

See Also

LVGP_fit to see how a GP model can be fitted to a training dataset.
LVGP_predict to use the fitted LVGP model for prediction.
LVGP_plot to plot the features of the fitted model.

Examples

# see the examples in the documentation of the function LVGP_fit.

LVGP documentation built on May 1, 2019, 7:05 p.m.