R/tacks.R

In REBayes: Empirical Bayes Estimation and Inference

#' @name tacks
#' @title Beckett and Diaconis flipping tacks data
#' @description This data was generated by Beckett and Diaconis (1994).  
#' They describe it as follows: 
#' "The example involves repeated rolls of a common thumbtack.  A one was
#' recorded if the tack landed point up and a zero was recorded if the tack
#' landed point down.  All tacks started point down.  Each tack was flicked
#' or hit with the fingers from where it last rested.  A fixed tack was flicked
#' 9 times. The data are recorded in Table 1.  There are 320 9-tuples.  These
#' arose from 16 different tacks, 2 ``flickers,''  and 10 surfaces.  The tacks
#' vary considerably in shape and in proportion of ones.  The surfaces varied
#' from rugs through tablecloths through bathroom floors."
#' Following Liu (1996), we treat the data as though they came from 
#' 320 independent binomials.  See \code{demo(Bmix1)} for further details.
#' @usage tacks
#' @format  A data frame with 320 observations on 2 variables.
#' \itemize{
#'     \item{\code{x}}{a numeric vector giving the number of tacks landed point up.}
#'     \item{\code{k}}{a numeric vector giving the number of trials.}
#' }
#' @source  Beckett, L. and Diaconis. P. (1994). Spectral analysis 
#' for discrete longitudinal data, Adv. Math., 103: 107-128.
#' @references Liu, J.S. (1996). Nonparametric Hierarchical Bayes via 
#' Sequential Imputations.  \emph{Annals of Statistics}, 24: 911-930.
#' @keywords datasets
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