Piecewise-constant regression
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, ...)
formula |
formula of the model to be fitted. |
data |
optional data frame. |
method |
character. If |
min_length |
integer. The minimal distance between two consecutive knots. |
... |
Additional arguments to be passed to |
object, x, Fn |
An object of class |
newdata |
data.frame to be passed to the |
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.
## 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)
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