blr: Fitting linear models using Basis Functions

In andreaskapou/BPRMeth-devel: Model higher-order methylation profiles

Description

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

Usage

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

Arguments

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

Value

An object of class "basis_lm" 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.

Author(s)

C.A.Kapourani [e-mail]

See Also

predict.blr, create_fourier_object, create_rbf_object, summary.blr

andreaskapou/BPRMeth-devel documentation built on May 12, 2019, 3:32 a.m.