# Man pages for RobinHankin/calibratorBayesian Calibration of Complex Computer Codes

 beta1hat.fun beta1 estimator beta2hat.fun estimator for beta2 betahat.fun.koh Expectation of beta, given theta, phi and d blockdiag Assembles matrices blockwise into a block diagonal matrix C1 Matrix of distances from D1 to D2 calibrator-package Bayesian Calibration of Complex Computer Codes cov.p5.supp Covariance function for posterior distribution of z create.new.toy.datasets Create new toy datasets D1.fun Function to join x.star to t.vec to give matrix D1 D2.fun Augments observation points with parameters dists.2frames Distance between two points EK.eqn10.supp Posterior mean of K etahat Expectation of computer output E.theta.toy Expectation and variance with respect to theta extractor.toy Extracts lat/long matrix and theta matrix from D2. Ez.eqn7.supp Expectation of z given y, beta2, phi Ez.eqn9.supp Expectation as per equation 10 of KOH2001 h1 Basis functions H1.toy Basis functions for D1 and D2 hbar.fun.toy Toy example of hbar (section 4.2) H.fun H function is.positive.definite Is a matrix positive definite? MH Very basic implementation of the Metropolis-Hastings... p.eqn4.supp Apostiori probability of psi1 p.eqn8.supp A postiori probability of hyperparameters phi.fun.toy Functions to create or change hyperparameters p.page4 A postiori probability of hyperparameters prob.psi1 A priori probability of psi1, psi2, and theta reality Reality stage1 Stage 1,2 and 3 optimization on toy dataset symmetrize Symmetrize an upper triangular matrix tee Auxiliary functions for equation 9 of the supplement toys Toy datasets tt.fun Integrals needed in KOH2001 V1 Distance matrix V2 distance between observation points Vd Variance matrix for d V.fun Variance matrix for observations W covariance matrix for beta W1 Variance matrix for beta1hat W2 variance matrix for beta2
RobinHankin/calibrator documentation built on May 8, 2019, 8:06 a.m.