This is the formal representation of the assembly of data structures delivered by the model selection routines in the funGp package. Gaussian process models are useful statistical tools in the modeling of complex input-output relationships. 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 funGp models

  • Plotters
    plotX: diagnostic plots for a fgpm_factory optimization and the selected model
    plotEvol: plot of the evolution of the model selection algorithm in funGp



Object of class "factoryCall". User call reminder.


Object of class "fgpm". Model selected by the heuristic structural optimization algorithm.


Object of class "character". Performance measure optimized to select the model. To be set from "Q2loocv", "Q2hout".


Object of class "numeric". Value of the performance measure for the selected model.


Object of class "data.frame". Structural configuration of the selected model.


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.


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.


Object of class "numeric". Number of possible structural configurations for the optimization instance resolved.


Object of class "numeric". Number of structural configurations successfully evaluated by the algorithm.


Object of class "list". Further information about the parameters of the ant colony optimization algorithm and the evolution of the fitness along the iterations.

Useful material