R: Estimation of an increasing and convex function

cvxreg {Sshaped}

R Documentation

Estimation of an increasing and convex function

This function computes the least squares increasing and convex regression estimator by a sequential mixed primal-dual bases algorithm.

cvxreg(x,y)

`x`	a numeric vector that contains all the design points. NB. for the current version, we require all values to be distinct (but not necessarily in ascending order).
`y`	a numeric vector that contains the values of the response with respect to the design points.

For more details, see Sshaped.

An object of class sshaped, which contains the following fields:

`x`	covariates copied from input
`y`	response copied from input
`fitted`	the fitted values of the regression function with respect to the design points.
`rss`	the value of the minimised residual sum of squares of the fit
`inflection`	the location of the inflection point, which equals `max(x)` here
`shape`	the shape enforced in the fit, here equals "`convex`"

x<-seq(0,5,0.01)
y<-x^2 + rnorm(length(x))
output<-cvxreg(x,y)
plot(output)
xnew=rexp(5); predict(output,xnew)

[Package Sshaped version 1.1 Index]