neg_log_l {LVGP} | R Documentation |
The Negative Log-Likelehood Function in LVGP
Package
Description
Calculates the negative log-likelihood (excluding all the constant terms) as described in reference 1
.
Usage
neg_log_l(hyperparam, p_quant, p_qual, lvs_qual, n_lvs_qual, dim_z,
X_quant, X_qual, Y, min_eig, k, M)
Arguments
hyperparam |
Hyperparameters of the LVGP model |
p_quant |
Number of quantative variables |
p_qual |
Number of qualitative variables |
lvs_qual |
Levels of each qualitative variable |
n_lvs_qual |
Number of levels of each qualitative variable |
dim_z |
Dimensionality of latent variables, usually 1 or 2 |
X_quant |
Input data of quantative variables |
X_qual |
Input data of qualitative variables |
Y |
Vector containing the outputs of data points |
min_eig |
The smallest eigen value that the correlation matrix is allowed to have, which determines the nugget added to the correlation matrix. |
k |
Number of data points, |
M |
Vector of ones with length |
Details
LVGP_fit
calls this function as its optimization objective function.
Value
The negative log-likelihood (excluding all the constant terms) value.
Note
This function is NOT exported once the package is loaded.
References
"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.