blm: Fitting linear models using Basis Functions

In andreaskapou/mpgex: Methylation Profiles predict Gene Expression

Description

blm is used to fit linear models using basis functions such as Radial Basis Functions (RBFs) and Polynomial Basis Functions.

Usage

blm(x, y, basis, lambda = 0, return.all = TRUE)

Arguments

x	The observations.
y	The response.
basis	Basis function object e.g. rbf.object.
lambda	Optional parameter for performing penalized least squares.
return.all	Optional logical, indicating if all the metrics should be computed (mainly for efficiency).

Value

An object of class "blm" is a list containing the following components:

• coefficients a named vector of coefficients.

• residuals the residuals, that is response minus fitted values.

• fitted.values the fitted mean values.

• df.residuals the residual degrees of freedom.

• sigma the standard deviation of the residuals.

• vcov The covariance matrix.

• basis The basis object used.

• lambda The regularization parameter.

• call the matched call.

See Also

predict.blm, polynomial.object, rbf.object, summary.blm

andreaskapou/mpgex documentation built on May 12, 2019, 3:33 a.m.