The alpha-kernel regression with compositional response data: The \(\alpha\)-kernel regression with compositional response data
Description
The \(\alpha\)-kernel regression with compositional response data.
Usage
akern.reg( xnew, y, x, a = seq(0.1, 1, by = 0.1),
h = seq(0.1, 1, length = 10), type = "gauss" )
Arguments
xnew
A matrix with the new predictor variables whose compositions are to
be predicted.
y
A matrix with the compositional response data. Zeros are allowed.
x
A matrix with the available predictor variables.
a
The value(s) of \(\alpha\). Either a single value or a vector of values.
As zero values in the compositional data are allowed, you must be careful
to choose strictly positive vcalues of \(\alpha\). However, if negative
values are passed, the positive ones are used only.
h
The bandwidth value(s) to consider.
type
The type of kernel to use, "gauss" or "laplace".
Value
A list with the estimated compositional response data for each value of
\(\alpha\) and h.
Details
The \(\alpha\)-kernel regression for compositional response variables is
applied.
References
Tsagris M., Alenazi A. and Stewart C. (2021).
Non-parametric regression models for compositional data.
https://arxiv.org/pdf/2002.05137.pdf