transform: Transform by R matrix.

In nlr: Nonlinear Regression Modelling using Robust Methods

Description

Transform R \times value and its gradient and hessian.

Usage

transform(value,rm)

Arguments

value	A vector to be transformed by R-matrix. It must have gradient and hessian as attributes.
rm	The R-matrix, from QR decomposition.

Details

It is used to transfomr a nonlinear regression model by R matrix from QR decomposition of variance covariance matrix.

Value

Is a transformed vector R \times V, and hessian and gradient as its attributes. Gradient is equal:

gradient= rm \times g

and hessian equal the three dimentional product:

hessian= h \%3d*m\% rm

.

Note

It is used in generalized model. In both heteroscedastic and autocorrelated model will be applied.

This function call by nlr, it might not be called directly by user.

Author(s)

Hossein Riazoshams, May 2014. Email: [e-mail] URL http://www.riazoshams.com/nlr/

References

Robust Nonlinear Regression, Theories and Methods with Practical Guides for R Packages. Riazoshams et al.

See Also

nlmest.NLM, nlmest.NLMf, nlmest.WF

Examples

## The function is currently defined as
"transform"

nlr documentation built on July 31, 2019, 5:09 p.m.