LVGP (version 2.1.5)

to_latent: The Function for Transforming Qualitative/Categorical Variables into Latent Variables in LVGP Package

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

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

# NOT RUN {
# see the examples in the documentation of the function LVGP_fit.
# }