R: Piecewise-constant regression

picor {statip}

R Documentation

Piecewise-constant regression

Description

picor looks for a piecewise-constant function as a regression function. The regression is necessarily univariate. This is essentially a wrapper for rpart (regression tree) and isoreg.

Usage

picor(formula, data, method, min_length = 0, ...)

## S3 method for class 'picor'
knots(Fn, ...)

## S3 method for class 'picor'
predict(object, newdata, ...)

## S3 method for class 'picor'
plot(x, ...)

## S3 method for class 'picor'
print(x, ...)

Arguments

`formula`	formula of the model to be fitted.
`data`	optional data frame.
`method`	character. If `method = "isotonic"`, then isotonic regression is applied with the `isoreg` from package stats. Otherwise, `rpart` is used, with the corresponding `method` argument.
`min_length`	integer. The minimal distance between two consecutive knots.
`...`	Additional arguments to be passed to `rpart`.
`object, x, Fn`	An object of class `"picor"`.
`newdata`	data.frame to be passed to the `predict` method.

Value

An object of class "picor", which is a list composed of the following elements:

formula: the formula passed as an argument;
x: the numeric vector of predictors;
y: the numeric vector of responses;
knots: a numeric vector (possibly of length 0), the knots found;
values: a numeric vector (of length length(knots)+1), the constant values taken by the regression function between the knots.

Examples

## Not run: 
s <- stats::stepfun(c(-1,0,1), c(1., 2., 4., 3.))
x <- stats::rnorm(1000)
y <- s(x)
p <- picor(y ~ x, data.frame(x = x, y = y))
print(p)
plot(p)

## End(Not run)

[Package statip version 0.2.3 Index]