Revision 9ae1e67cb5e13c5bbc731a5fc56a0053182f16b0 authored by Matthias Templ on 11 February 2020, 16:20:02 UTC, committed by cran-robot on 11 February 2020, 16:20:02 UTC
1 parent 775c7e1
impRZalr.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/impRZalr.R
\name{impRZalr}
\alias{impRZalr}
\title{alr EM-based imputation of rounded zeros}
\usage{
impRZalr(
x,
pos = ncol(x),
dl = rep(0.05, ncol(x) - 1),
eps = 1e-04,
maxit = 50,
bruteforce = FALSE,
method = "lm",
step = FALSE,
nComp = "boot",
R = 10,
verbose = FALSE
)
}
\arguments{
\item{x}{compositional data}
\item{pos}{position of the rationing variable for alr transformation}
\item{dl}{detection limit for each part}
\item{eps}{convergence criteria}
\item{maxit}{maximum number of iterations}
\item{bruteforce}{if TRUE, imputations over dl are set to dl. If FALSE,
truncated (Tobit) regression is applied.}
\item{method}{either \dQuote{lm} (default) or \dQuote{MM}}
\item{step}{if TRUE, a stepwise (AIC) procedure is applied when fitting
models}
\item{nComp}{if determined, it fixes the number of pls components. If
\dQuote{boot}, the number of pls components are estimated using a
bootstraped cross validation approach.}
\item{R}{number of bootstrap samples for the determination of pls
components. Only important for method \dQuote{pls}.}
\item{verbose}{additional print output during calculations.}
}
\value{
\item{xOrig }{Original data frame or matrix} \item{xImp }{Imputed
data} \item{wind }{Index of the missing values in the data} \item{iter
}{Number of iterations} \item{eps }{eps}
}
\description{
A modified EM alr-algorithm for replacing rounded zeros in compositional
data sets.
}
\details{
Statistical analysis of compositional data including zeros runs into
problems, because log-ratios cannot be applied. Usually, rounded zeros are
considerer as missing not at random missing values. The algorithm first
applies an additive log-ratio transformation to the compositions. Then the
rounded zeros are imputed using a modified EM algorithm.
}
\examples{
data(arcticLake)
x <- arcticLake
## generate rounded zeros artificially:
x[x[,1] < 5, 1] <- 0
x[x[,2] < 47, 2] <- 0
xia <- impRZalr(x, pos=3, dl=c(5,47), eps=0.05)
xia$xImp
}
\references{
Palarea-Albaladejo, J., Martin-Fernandez, J.A. Gomez-Garcia, J. (2007)
A parametric approach for dealing with compositional rounded zeros.
\emph{Mathematical Geology}, 39(7), 625-645.
}
\seealso{
\code{\link{impRZilr}}
}
\author{
Matthias Templ and Karel Hron
}
\keyword{manip}
\keyword{multivariate}
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