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DESCRIPTION
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README.md

README.md

Travis-CI Build Status

This is an R package, in development, for regularized interval regression.

Installation

To install the package, use the devtools package:

devtools::install_github("anujkhare/iregnet")

Example usage:

# y can be a 2 column matrix.
X <- matrix(rnorm(50), 10, 5)
y <- matrix(rnorm(20), 10, 2)
y <- t(apply(y, 1, sort)) # intervals must be non-decreasing
fit1 <- iregnet(X, y)

# Surv objects from survival are also supported.
data("ovarian")
X <- cbind(ovarian$ecog.ps, ovarian$rx)
y <- Surv(ovarian$futime, ovarian$fustat)
fit2 <- iregnet(X, y)

# Log-Gaussian is same as Gaussian with log-transformed data
X <- matrix(rnorm(50), 10, 5)
y <- matrix(abs(rnorm(20)), 10, 2)
y <- t(apply(y, 1, sort)) # intervals must be non-decreasing
fit3 <- iregnet(X, log(y), "gaussian")
fit4 <- iregnet(X, y, "loggaussian")

# Scale parameter can be fixed by setting the estimate_scale flag.
X <- matrix(rnorm(50), 10, 5)
y <- matrix(rnorm(20), 10, 2)
y <- t(apply(y, 1, sort)) # intervals must be non-decreasing
fit5 <- iregnet(X, y, scale_init=1, estimate_scale=F)

Detailed documentation of each parameter is provided in R help for iregnet.

For more details about the package, visit the following link: https://github.com/rstats-gsoc/gsoc2016/wiki/Regularized-interval-regression