R/smatr.R

In dfalster/smatr3: (Standardised) Major Axis Estimation and Testing Routines

#' (Standardised) Major Axis Estimation and Testing Routines
#' 
#' @description This package provides methods of fitting bivariate lines in allometry using
#' the major axis (MA) or standardised major axis (SMA), and for making
#' inferences about such lines. The available methods of inference include
#' confidence intervals and one-sample tests for slope and elevation, testing
#' for a common slope or elevation amongst several allometric lines,
#' constructing a confidence interval for a common slope or elevation, and
#' testing for no shift along a common axis, amongst several samples.
#' 
#' @details The key functions in this package are \code{\link{sma}} and
#' \code{\link{ma}}, which will fit SMA and MA respectively, and construct
#' confidence intervals or test hypotheses about slope or elevation in one or
#' several samples, depending on how the arguments are used.
#' For example:
#' 
#' \code{sma(y~x)} will fit a SMA for \code{y} vs \code{x}, and report
#' confidence intervals for the slope and elevation.
#' 
#' \code{sma(y~x, robust=T)} will fit a robust SMA for \code{y} vs \code{x}
#' using Huber's M estimation, and will report (approximate) confidence
#' intervals for the slope and elevation.
#' 
#' \code{ma(y~x*groups-1)} will fit MA lines for \code{y} vs \code{x} that are
#' forced through the origin, where a separate MA is fitted to each of several
#' samples as specified by the argument \code{groups}. It will also report
#' results from a test of the hypothesis that the true MA slope is equal across
#' all samples.
#' 
#' For more details, see the help listings for \code{\link{sma}} and
#' \code{\link{ma}}.
#' 
#' Note that the \code{\link{sma}} and \code{\link{ma}} functions replace the
#' functions given in earlier package versions as \code{\link{line.cis}},
#' \code{\link{slope.test}}, \code{\link{elev.test}}, \code{\link{slope.com}},
#' \code{\link{elev.com}} and \code{\link{shift.com}}, although all of these
#' functions and their help entries are still available.
#' 
#' All procedures have the option of correcting for measurement error, although
#' only in an approximate fashion, valid in large samples.
#' 
#' Additional features of this package are listed below.
#' 
#' \describe{ \item{meas.est}{ Estimates the average variance matrix of
#' measurement error for a set of subjects with repeated measures } }
#' 
#' \bold{Example datasets:} \describe{ \item{leaflife}{ leaf longevity and leaf
#' mass per area for plant species from different sites. Used to demonstrate
#' the functionality of the \code{sma} and \code{ma} functions.}
#' \item{leafmeas}{ leaf mass per area and photosynthetic rate for plant
#' species from different sites. Used to demonstrate the meas.est function } }
#' 
#' For more details, see the documentation for any of the individual functions
#' listed above.
#' 
#' @docType package
#' @author Warton, D. \email{David.Warton@@unsw.edu.au}, Duursma, R., Falster,
#' D. and Taskinen, S.
#' @seealso \code{\link{sma}},\code{\link{ma}}, \code{\link{meas.est}},
#' \code{\link{leaflife}}, \code{\link{leafmeas}}
#' @references Warton D. I. and Weber N. C. (2002) Common slope tests for
#' bivariate structural relationships.  \emph{Biometrical Journal} \bold{44},
#' 161--174.
#' 
#' Warton D. I., Wright I. J., Falster D. S. and Westoby M. (2006) A review of
#' bivariate line-fitting methods for allometry.  \emph{Biological Reviews}
#' \bold{81}, 259--291.
#' 
#' Taskinen S. and Warton D. I. (in press) Robust estimation and inference for
#' bivariate line-fitting in allometry.  \emph{Biometrical Journal}.
#' @keywords internal
#' @importFrom stats coef cor cor.test cov fitted model.frame na.omit pchisq pf pt qchisq qf qqline qqnorm qt uniroot var
#' @importFrom utils combn str
#' @examples
#
#' # See  ?sma and ?plot.sma for a full list of examples.

"_PACKAGE"