# picor: Piecewise-constant regression In statip: Statistical Functions for Probability Distributions and 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```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

 ```1 2 3 4 5 6 7 8 9``` ```## 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) ```

statip documentation built on Nov. 18, 2019, 1:06 a.m.