kernDiagGradX: Compute the gradient of the kernel wrt X.

In ahonkela/tigre: Transcription factor Inference through Gaussian process Reconstruction of Expression

Description

computes the gradient of the (diagonal of the) kernel matrix with respect to the elements of the design matrix given in X.

Usage

  kernDiagGradX(kern, x)
  kernGradX(kern, x, x2)

Arguments

kern	the kernel structure for which gradients are being computed.
x	if only argument: the input data in the form of a design matrix, if two arguments: row locations against which gradients are being computed.
x2	(optional) column locations against which gradients are being computed.

Value

gX	the gradients of the diagonal with respect to each element of X. The returned matrix has the same dimensions as X.
gX2	the returned gradients. The gradients are returned in a matrix which is numData x numInputs x numData. Where numData is the number of data points and numInputs is the number of input dimensions in X.

See Also

kernGradient

Examples

kern <- kernCreate(1, 'mlp')
g <- kernDiagGradX(kern, as.matrix(3:8))

ahonkela/tigre documentation built on Aug. 6, 2021, 12:08 p.m.