R/WalleyeWs.R

In droglenc/FSAWs: Construct and Validate Standard Weight (Ws) Equations for Fish

#' @title Length-weight regression results for computing Ws for Walleye.
#' 
#' @description Length-weight regression results from a variety of populations used for computing the standard weight (Ws) equation for Walleye (\emph{Sander vitreus}).
#' 
#' @details Each row contains the intercept (\code{log.a}) and slope (\code{b}) results from fitting the \eqn{log_{10}(W) = log_{10}(a) + b log_{10}(L)} linear regression model to a population of \code{n} fish from the given location and state. Note that \eqn{W} is weight in grams and \eqn{L} is length in mm.
#' 
#' @name WalleyeWs
#' 
#' @docType data
#' 
#' @format A data frame with 114 observations on the following 8 variables:
#'  \describe{ 
#'    \item{code}{A unique identifier for the sample.}
#'    \item{site}{Location of sample.}
#'    \item{state}{State where location is located.}
#'    \item{n}{Sample size in regression.}
#'    \item{log.a}{Intercept of regression.}
#'    \item{b}{Slope of regression.}
#'    \item{r2}{Coefficient of determination for the regression.} 
#'    \item{meanWr}{Mean relative weight for the population.}
#'  }
#'  
#' @seealso \code{\link{rlp}}.
#' 
#' @source From Table 3 in Murphy, B.R., M.L. Brown, and T.A. Springer. 1990. Evaluation of the relative weight (Wr) index, with new applications to
#' walleye. North American Journal of Fisheries Management, 10:85-97.
#' 
#' @keywords datasets
#' 
#' @examples
#' str(WalleyeWs)
#' head(WalleyeWs)
#' 
#' ## Recreate Murphy et al. (1990) results for walleye
#' wae.rlp <- rlp(WalleyeWs$log.a,WalleyeWs$b,155,1045,qtype=6)
#' coef(wae.rlp)
#' # compare to log.a=-5.453 and b=3.180
#' 
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