s_soda_model: S-SODA model estimation.

In sodavis: SODA: Main and Interaction Effects Selection for Logistic Regression, Quadratic Discriminant and General Index Models

Description

S-SODA assumes within each slice the X vector follow multivariate normal distribution. This function estimates the mean vector and covariance matrix of X for each slice.

Usage

s_soda_model(x, y, H = 10)

Arguments

x	The design matrix, of dimensions n * p, without an intercept. Each row is an observation vector.
y	The response vector of dimension n * 1.
H	The number of slices.

Value

int_h	Slice index.
int_p	Proportion of samples in each slice.
int_l	Length of each slice (max - min response).
int_m	Mean vector of covariates in each slice.
int_v	Covariance matrix of covariates in each slice.

sodavis documentation built on May 2, 2019, 12:38 p.m.