In HeyangGong/estcondmin: Estimation of Conditional Min

This is a vignette to explain those model details.

Model

We have the dataset with on predict variable y and $p$ predictors $x_1,...,x_p$. This package trys to find sufficient conditions in the datasets in the forms:

$$y \geq \sum_{i \in I} \beta_i x_i$$

quick start

step 1: we generate the dataset.

set.seed(1)
library(magrittr)
d <- estcondmin::gen_dat(n = 100, beta = c(1,1, 0, 0, 0))
knitr::kable(head(data.frame(y= d$y, d$X)))

step 2: We estimate the relationship

estcondmin::estcondmin(y = d$y, X = d$X, lambda = 0.3)

HeyangGong/estcondmin documentation built on May 19, 2019, 12:40 a.m.