Xfgpm-class: S4 class for funGp model selection data structures
In funGp: Gaussian Process Models for Scalar and Functional Inputs

Xfgpm-class

R Documentation

S4 class for funGp model selection data structures

Description

This is the formal representation of the assembly of data structures delivered by the model selection routines in the funGp package. An Xfgpm object contains the trace of an optimization process, conducted to build Gaussian process models of outstanding performance.

Main methods
fgpm_factory: structural optimization of fgpm models, creator of the "Xfgpm" class.
Plotters
plot,Xfgpm-method: plot of the evolution of the algorithm with which = "evolution" or of the absolute and relative quality of the optimized model with which = "diag".

Slots

factoryCall: Object of class "factoryCall". User call reminder.
model: Object of class "fgpm". Model selected by the heuristic structural optimization algorithm.
stat: Object of class "character". Performance measure optimized to select the model. To be set from "Q2loocv", "Q2hout".
fitness: Object of class "numeric". Value of the performance measure for the selected model.
structure: Object of class "data.frame". Structural configuration of the selected model.
log.success: Object of class "antsLog". Record of models successfully evaluated during the structural optimization. It contains the structural configuration both in data.frame and "modelCall" format, along with the fitness of each model. The models are sorted by fitness, starting with the best model in the first position.
log.crashes: Object of class "antsLog". Record of models crashed during the structural optimization. It contains the structural configuration of each model, both in data.frame and "modelCall" format.
n.solspace: Object of class "numeric". Number of possible structural configurations for the optimization instance resolved.
n.explored: Object of class "numeric". Number of structural configurations successfully evaluated by the algorithm.
details: Object of class "list". Further information about the parameters of the ant colony optimization algorithm and the evolution of the fitness along the iterations.
sIn: An object of class "matrix" containing a copy of the provided scalar inputs.
fIn: An object of class "list" containing a copy of the provided functional inputs.
sOut: An object of class "matrix" containing a copy of the provided outputs.

Useful material

Manual funGp: An R Package for Gaussian Process Regression with Scalar and Functional Inputs (\Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.18637/jss.v109.i05")})