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pGPx
View on CRAN: Click
here
Download and install pGPx package within the R console
Install from CRAN:
install.packages("pGPx")
Install from Github:
library("remotes")
install_github("cran/pGPx")
Install by package version:
library("remotes")
install_version("pGPx", "0.1.4")
Attach the package and use:
library("pGPx")
Maintained by
Dario Azzimonti
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-08-17
Latest Update: 2023-08-23
Description:
Computes pseudo-realizations from the posterior distribution of a Gaussian Process (GP) with the method described in Azzimonti et al. (2016) . The realizations are obtained from simulations of the field at few well chosen points that minimize the expected distance in measure between the true excursion set of the field and the approximate one. Also implements a R interface for (the main function of) Distance Transform of sampled Functions ().
How to cite:
Dario Azzimonti (2018). pGPx: Pseudo-Realizations for Gaussian Process Excursions. R package version 0.1.4, https://cran.r-project.org/web/packages/pGPx. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Complete documentation for pGPx
Functions, R codes and Examples using
the pGPx R package
Some associated functions: DTV . computeVolumes . compute_contourLength . dtt_fast . edm_crit . edm_crit2 . expDistMeasure . grad_kweights . integrand_edm_crit . krig_weight_GPsimu . max_distance_measure . max_integrand_edm . optim_dist_measure . pGPx-package . simulate_and_interpolate .
Some associated R codes: DTvar.R . RcppExports.R . computeVolumes.R . compute_contourLength.R . edm_crit.R . edm_crit2.R . expDistMeasure.R . grad_weight_GPsimu.R . integrand_edm_crit.R . krig_weight_GPsimu.R . max_distance_measure.R . max_integrand_edm.R . optim_distMeas.R . pGPx-package.R . simulate_and_interpolate.R . Full pGPx package functions and examples
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