statip (version 0.2.3)

picor: 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 picor
knots(Fn, ...)
# S3 method for picor
predict(object, newdata, ...)
# S3 method for picor
plot(x, ...)
# S3 method for 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)
# }
# NOT RUN {
# }