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Showing results 1 to 10 of 1,109.


Function [.circular [circular v0.4-93]
keywords
array
title
Extract or Replace Parts of a Circular Object
description
Operators act on vectors and matrices to extract or replace subsets, methods for Circular Data.
Function logDataSet [micEcon v0.6-14]
keywords
array
title
Creating a Data Set with the Logarithms of the Original Variables
description
This function creates a data set with the logarithms of the original variables.
Function unscale [grt v0.2.1]
keywords
array
title
Un-scale or re-center the scaled or centered Matrix-like object
description
This function revert a Matrix-like object that is scaled or centered via scale.default to data with the original scale/center.
Function scale [grt v0.2.1]
keywords
array
title
Scale method for the class 'glc' and 'gqc'
description
Return the discriminant scores obtained by applying the general linear classifier to the fitted data.
Function is.consistent [approximator v1.2-7]
keywords
array
title
Checks observational data for consistency with a subsets object
description
Checks observational data for consistency with a subsets object: the length of the vectors should match
Function tee.fun [approximator v1.2-7]
keywords
array
title
Returns generalized distances
description
Returns generalized distances from a point to the design matrix as per equation 10
Function generate.toy.observations [approximator v1.2-7]
keywords
array
title
Er, generate toy observations
description
Generates toy observations on four levels using either internal (unknown) parameters and hyperparameters, or user-supplied versions.
Function basis.toy [approximator v1.2-7]
keywords
array
title
Toy basis functions
description
A working example of a basis function
Function mdash.fun [approximator v1.2-7]
keywords
array
title
Mean of Gaussian process
description
Returns the mean of the Gaussian process conditional on the observations and the hyperparameters
Function object [approximator v1.2-7]
keywords
array
title
Optimization of posterior likelihood of hyperparameters
description
Returns the likelihood of a set of hyperparameters given the data. Functions opt1() and opt.gt.1() find hyperparameters that maximize the relevant likelihood for level 1 and higher levels respectively. Function object() returns the expression given by equation 9 in KOH2000, which is minimized opt1() and opt.gt.1().