bernoulli_kernel

This function is used to calculate the kernel matrix for the
RKHS regression that iteratively updates the temporal loading function.

TEMPoral TEnsor Decomposition (TEMPTED), is a dimension reduction method for multivariate longitudinal data with varying temporal sampling. It formats the data into a temporal tensor and decomposes it into a summation of low-dimensional components, each consisting of a subject loading vector, a feature loading vector, and a continuous temporal loading function. These loadings provide a low-dimensional representation of subjects or samples and can be used to identify features associated with clusters of subjects or samples. TEMPTED provides the flexibility of allowing subjects to have different temporal sampling, so time points do not need to be binned, and missing time points do not need to be imputed.

Pixu Shi

tempted

Temporal Tensor Decomposition, a Dimensionality Reduction Tool
for Longitudinal Multivariate Data

bernoulli_kernel function

<dl><dt>x, y</dt>
<dd>Two values between which the Bernoulli kernel is calculated.</dd></dl>

Arguments

Caculate the Bernoulli kernel — bernoulli_kernel

<dl>

<dt>x, y</dt>
<dd>Two values between which the Bernoulli kernel is calculated.</dd>

</dl>

bernoulli_kernel: Caculate the Bernoulli kernel

Description

Usage

Value

Arguments

References