Man pages for gptk
Gaussian Processes Tool-Kit

basePlotPlot a contour of the 2D Gaussian distribution with...
cmpndKernParamInitCMPND kernel parameter initialisation.
cmpndNoiseParamInitCMPND noise parameter initialisation.
demAutoOptimiseGpGaussian Process Optimisation Demo
demGpCov2DGaussian Process 2D Covariance Demo
demGpSampleGaussian Process Sampling Demo
demInterpolationGaussian Process Interpolation Demo
demOptimiseGpGaussian Process Optimisation Demo
demRegressionGaussian Process Regression Demo
expTransformConstrains a parameter.
gaussianNoiseOutCompute the output of the GAUSSIAN noise given the input mean...
gaussianNoiseParamInitGAUSSIAN noise parameter initialisation.
gaussSampSample from a Gaussian with a given covariance.
gpBlockIndicesReturn indices of given block.
gpComputeAlphaUpdate the vector 'alpha' for computing posterior mean...
gpComputeMCompute the matrix m given the model.
gpCovGradsSparse objective function gradients wrt Covariance functions...
gpCovGradsTestTest the gradients of the likelihood wrt the covariance.
gpCreateCreate a GP model with inducing variables/pseudo-inputs.
gpDataIndicesReturn indices of present data.
gpExpandParamExpand a parameter vector into a GP model.
gpExtractParamExtract a parameter vector from a GP model.
gpGradientGradient wrapper for a GP model.
gpLogLikeGradientsCompute the gradients for the parameters and X.
gpLogLikelihoodCompute the log likelihood of a GP.
gpMeanFunctionGradientCompute the log likelihood gradient wrt the scales.
gpObjectiveWrapper function for GP objective.
gpOptimiseOptimise the inducing variable based kernel.
gpOptionsReturn default options for GP model.
gpOutEvaluate the output of an Gaussian process model.
gpPlotGaussian Process Plotter
gpPosteriorMeanVarMean and variances of the posterior at points given by X.
gpPosteriorSamplePlot Samples from a GP Posterior.
gpSamplePlot Samples from a GP.
gpScaleBiasGradientCompute the log likelihood gradient wrt the scales.
gpTestTest the gradients of the gpCovGrads function and the gp...
gpUpdateADUpdate the representations of A and D associated with the...
gpUpdateKernelsUpdate the kernels that are needed.
kernComputeCompute the kernel given the parameters and X.
kernCreateInitialise a kernel structure.
kernDiagGradientCompute the gradient of the kernel's parameters for the...
kernDiagGradXCompute the gradient of the kernel wrt X.
kernGradientCompute the gradient wrt the kernel parameters.
kernParamInitKernel parameter initialisation.
kernTestRun some tests on the specified kernel.
modelDisplayDisplay a model.
modelExpandParamUpdate a model structure with new parameters or update the...
modelExtractParamExtract the parameters of a model.
modelGradientModel log-likelihood/objective error function and its...
modelGradientCheckCheck gradients of given model.
modelOutGive the output of a model for given X.
modelOutputGradCompute derivatives with respect to params of model outputs.
multiKernParamInitMULTI kernel parameter initialisation.
noiseCreateInitialise a noise structure.
noiseOutGive the output of the noise model given the mean and...
noiseParamInitNoise model's parameter initialisation.
optimiDefaultConstraintReturns function for parameter constraint.
rbfKernDiagGradXGradient of RBF kernel's diagonal with respect to X.
rbfKernGradXGradient of RBF kernel with respect to input locations.
rbfKernParamInitRBF kernel parameter initialisation.
SCGoptimOptimise the given function using (scaled) conjugate...
whiteKernDiagGradXGradient of WHITE kernel's diagonal with respect to X.
whiteKernGradXGradient of WHITE kernel with respect to input locations.
whiteKernParamInitWHITE kernel parameter initialisation.
zeroAxesA function to move the axes crossing point to the origin.
gptk documentation built on May 30, 2017, 6:41 a.m.