aboutsummaryrefslogtreecommitdiff
path: root/man/ilr.Rd
diff options
context:
space:
mode:
authorJohannes Ranke <jranke@uni-bremen.de>2014-05-07 14:47:28 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2014-05-07 14:47:28 +0200
commite959fde98f95f3595e01490b67892678bbcd1b27 (patch)
tree992c56223a31c6937091dd5f9eeef63c2dd9e579 /man/ilr.Rd
parentd846ac7691ab648afbb5a98bbca91911396a95bf (diff)
Fork the gmkin GUI from mkin. See ChangeLog for details
Diffstat (limited to 'man/ilr.Rd')
-rw-r--r--man/ilr.Rd56
1 files changed, 0 insertions, 56 deletions
diff --git a/man/ilr.Rd b/man/ilr.Rd
deleted file mode 100644
index cedb49c..0000000
--- a/man/ilr.Rd
+++ /dev/null
@@ -1,56 +0,0 @@
-\name{ilr}
-\alias{ilr}
-\alias{invilr}
-\title{
- Function to perform isotropic log-ratio transformation
-}
-\description{
- This implementation is a special case of the class of isotropic log-ratio transformations.
-}
-\usage{
- ilr(x)
- invilr(x)
-}
-\arguments{
- \item{x}{
- A numeric vector. Naturally, the forward transformation is only sensible for
- vectors with all elements being greater than zero.
- }
-}
-\value{
- The result of the forward or backward transformation. The returned components always
- sum to 1 for the case of the inverse log-ratio transformation.
-}
-\references{
- Peter Filzmoser, Karel Hron (2008) Outlier Detection for Compositional Data Using Robust Methods. Math Geosci 40 233-248
-}
-\author{
- René Lehmann and Johannes Ranke
-}
-\seealso{
- Other implementations are in R packages \code{compositions} and \code{robCompositions}.
-}
-\examples{
-# Order matters
-ilr(c(0.1, 1, 10))
-ilr(c(10, 1, 0.1))
-# Equal entries give ilr transformations with zeros as elements
-ilr(c(3, 3, 3))
-# Almost equal entries give small numbers
-ilr(c(0.3, 0.4, 0.3))
-# Only the ratio between the numbers counts, not their sum
-invilr(ilr(c(0.7, 0.29, 0.01)))
-invilr(ilr(2.1 * c(0.7, 0.29, 0.01)))
-# Inverse transformation of larger numbers gives unequal elements
-invilr(-10)
-invilr(c(-10, 0))
-# The sum of the elements of the inverse ilr is 1
-sum(invilr(c(-10, 0)))
-# This is why we do not need all elements of the inverse transformation to go back:
-a <- c(0.1, 0.3, 0.5)
-b <- invilr(a)
-length(b) # Four elements
-ilr(c(b[1:3], 1 - sum(b[1:3]))) # Gives c(0.1, 0.3, 0.5)
-}
-
-\keyword{ manip }

Contact - Imprint