biviso {Iso}R Documentation

Bivariate isotonic regression.

Description

Bivariate isotonic regression with respect to simple (increasing) linear ordering on both variables.

Usage

biviso(y, w = NULL, eps = 1e-04, ncycle = 1000)

Arguments

y The matrix of observations to be isotonized. It must of course have at least two rows and at least two columns.
w A matrix of weights, greater than or equal to zero, of the same dimension as y. If left NULL then w is created as a matrix all of whose entries are equal to 1.
eps Convergence criterion. The algorithm is deemed to have converged if each entry of the output matrix, after the completion of the current iteration, does not differ by more than eps from the corresponding entry of the matrix after the completion of the previous iteration.
ncycle The maximum number of cycles of the iteration procedure. If the procedure has not converged after ncycle iterations then an error is given.

Details

See the paper by Bril et al., (References) and the references cited therein for details.

Value

A matrix of the same dimensions as y containing the corresponding isotonic values. It has an attribute icycle equal to the number of cycles required to achieve convergence of the algorithm.

Error Messages

The subroutine comprising Algorithm AS 206 produces an error code ifault with values from 1 to 6 The meaning of these codes is as follows:

If ifault==4 a warning is given. All of the other non-zero values of ifault result in an error being given.

Author(s)

Rolf Turner r.turner@auckland.ac.nz http://www.math.unb.ca

References

Bril, Gordon; Dykstra, Richard; Pillers Carolyn, and Robertson, Tim ; Isotonic regression in two independent variables; Algorithm AS 206; JRSSC (Applied Statistics), vol. 33, no. 3, pp. 352-357, 1984.

See Also

pava() pava.sa() ufit()

Examples

x <- 1:20
y <- 1:10
xy <- outer(x,y,function(a,b){a+b+0.5*a*b})
ixy <- biviso(xy)

u <- matrix(runif(400),20,20)
v <- biviso(u)

[Package Iso version 0.0-8 Index]