R Graphical Manual

Last data update: 2014.03.03

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Results 1 - 10 of 65 found.
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gpTest (Package: gptk) : Test the gradients of the gpCovGrads function and the gp models.

runs some tests on the GP code to test that it is working.

● Data Source: CranContrib
● Keywords: model
● Alias: gpTest
● 0 images

gpExtractParam (Package: gptk) : Extract a parameter vector from a GP model.

does the same as above, but also returns parameter names.

● Data Source: CranContrib
● Keywords: model
● Alias: gpExtractParam
● 0 images

kernCreate (Package: gptk) : Initialise a kernel structure.

Initialise a kernel structure.

● Data Source: CranContrib
● Keywords: model
● Alias: kernCreate
● 0 images

gpOut (Package: gptk) : Evaluate the output of an Gaussian process model.

evaluates the output of a given Gaussian process model.

● Data Source: CranContrib
● Keywords: model
● Alias: gpOut
● 0 images

modelExpandParam (Package: gptk) : Update a model structure with new parameters or update the

Update a model structure or component with new parameters, or update the posterior processes.

● Data Source: CranContrib
● Keywords: model
● Alias: cgpdisimExpandParam, cgpdisimUpdateProcesses, cgpsimExpandParam, cgpsimUpdateProcesses, cmpndKernExpandParam, disimKernExpandParam, gpdisimExpandParam, gpdisimUpdateProcesses, gpsimExpandParam, gpsimUpdateProcesses, kernExpandParam, mlpKernExpandParam, modelExpandParam, modelUpdateProcesses, multiKernExpandParam, rbfKernExpandParam, simKernExpandParam, translateKernExpandParam, whiteKernExpandParam
● 0 images

gpOptimise (Package: gptk) : Optimise the inducing variable based kernel.

optimises the Gaussian process model for a given number of iterations.

● Data Source: CranContrib
● Keywords: model
● Alias: gpOptimise
● 0 images

demRegression (Package: gptk) : Gaussian Process Regression Demo

The regression demo very much follows the format of the interpolation demo. Here the difference is that the data is sampled with noise. Fitting a model with noise means that the regression will not necessarily pass right through each data point.

● Data Source: CranContrib
● Keywords: model
● Alias: demRegression
● 0 images

gpLogLikelihood (Package: gptk) : Compute the log likelihood of a GP.

computes the log likelihood of a data set given a GP model.

● Data Source: CranContrib
● Keywords: model
● Alias: gpLogLikelihood
● 0 images

whiteKernGradX (Package: gptk) : Gradient of WHITE kernel with respect to input locations.

computes the gradident of the white noise kernel with respect to the input positions where both the row positions and column positions are provided separately.

● Data Source: CranContrib
● Keywords: model
● Alias: whiteKernGradX
● 0 images

noiseParamInit (Package: gptk) : Noise model's parameter initialisation.

initialises the noise structure with some default parameters.

● Data Source: CranContrib
● Keywords: model
● Alias: noiseParamInit
● 0 images