duke

<p>This data set details microarray experiment for 44 breast cancer patients. The binary variable <code>Status</code> is used to classify the patients into estrogen receptor-positive (<code>Status = 0</code>) and estrogen receptor-negative (<code>Status = 1</code>). The other variables  contain the expression level of the considered genes.</p>

datasets

Differential geometric least angle regression method for fitting sparse generalized linear models. In this version of the package, the user can fit models specifying Gaussian, Poisson, Binomial, Gamma and Inverse Gaussian family. Furthermore, several link functions can be used to model the relationship between the conditional expected value of the response variable and the linear predictor. The solution curve can be computed using an efficient predictor-corrector or a cyclic coordinate descent algorithm, as described in the paper linked to via the URL below.

Luigi Augugliaro

dglars

Differential Geometric Least Angle Regression

Angelo Mineo

Ernst Wit

Hassan Pazira

Michael Wichura

John Burkardt

duke function

Duke breast cancer microarray experiment — duke

Duke breast cancer microarray experiment

duke: Duke breast cancer microarray experiment

Description

Usage

Arguments

References