R/data_help_files.R

In poweRlaw: Analysis of Heavy Tailed Distributions

#' @name moby
#' @aliases moby_sample
#' @title Moby Dick word count
#' @description The frequency of occurrence of unique words in the novel Moby Dick
#' by Herman Melville.
#'
#' The data set moby_sample is 2000 values
#' sampled from the moby data set.
#' @docType data
#' @format A vector
#' @source M. E. J. Newman, "Power laws, Pareto distributions and Zipf's law."
#' Contemporary Physics 46, 323 (2005).
#' See http://tuvalu.santafe.edu/~aaronc/powerlaws/data.htm for further details.
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#' @name bootstrap_moby
#' @aliases bootstrap_moby bootstrap_p_moby
#' @title Example bootstrap results for the full Moby Dick data set
#' @description To explore the uncertainity in the model fit, this package provides a
#' \code{bootstrap} function.
#' \describe{
#' \item{bootstrap_moby}{The output from running 5000 bootstraps on the full
#' Moby Dick data set (for a discrete power law)
#' using the \code{bootstrap} function. }
#' \item{bootstrap_p_moby}{The output from running 5000 bootstraps on the full
#' Moby Dick data set (for a discrete power law)
#' using the \code{bootstrap_p} function.}}
#' The \code{bootstrap_moby} values correspond to the first row of
#' table 6.1 in the Clauset et al paper:
#' \describe{
#' \item{\code{bootstrap_moby$gof}}{the K-S statistic}
#' \item{\code{bootstrap_moby$bootstraps}}{a data frame for the optimal
#' values from the bootstrapping procedure.
#' Column 1: K-S, Column 2: xmin, Column 3: alpha.
#' So standard deviation of column 2 and 3 is 2.2 and 0.033 (the paper gives 2
#' and 0.02 respectively).}
#' }
#'
#' The \code{bootstrap_p_moby} gives the p-value for the hypothesis
#' test of whether the data follows a power-law. For this simulation study,
#' we get a value of 0.43 (the paper gives 0.49).
#' @docType data
#' @seealso \code{moby}, \code{bootstrap}, \code{bootstrap_p}
#' @format A list
#' @source M. E. J. Newman, "Power laws, Pareto distributions and Zipf's law."
#' Contemporary Physics 46, 323 (2005).
#' See http://tuvalu.santafe.edu/~aaronc/powerlaws/data.htm for further details.
#' @examples
#' ## Generate the bootstrap_moby data set
#' \dontrun{
#' data(moby)
#' m = displ$new(moby)
#' bs = bootstrap(m, no_of_sims=5000, threads=4, seed=1)
#' }
#'
#' #' ## Generate the bootstrap_p_moby data set
#' \dontrun{
#' bs_p = bootstrap_p(m, no_of_sims=5000, threads=4, seed=1)
#' }
#'
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#' @name native_american
#' @aliases NativeAmerican USAmerican us_american
#' @title Casualties in the American Indian Wars (1776 and 1890)
#' @description These data files contain the observed casualties in the American Indian Wars.
#' The data sets \code{native_american} and \code{us_american} contain the
#' casualties on the Native American and US American
#' sides respectively. Each data set is a data frame, with two columns:
#' the number of casualties and the conflict date.
#'
#' @docType data
#' @format Data frame
#' @source Friedman, Jeffrey A. "Using Power Laws to Estimate Conflict Size."
#' The Journal of conflict resolution (2014).
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#' @name population
#' @aliases Population
#' @title City boundaries and the universality of scaling laws
#' @description This data set contains the population size of cities and towns in England.
#' For further details on the algorithm used to determine city boundries, see the referenced paper.
#'
#' @docType data
#' @format vector
#' @source Arcaute, Elsa, et al. "City boundaries and the universality of scaling laws."
#' arXiv preprint arXiv:1301.1674 (2013).
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#' @name swiss_prot
#' @aliases Swiss_prot
#' @title Word frequency in the Swiss-Prot database
#' @description This dataset contains all the words extracted from the
#' Swiss-Prot version 9 data (with the resulting frequency for each word).
#' Other datasets for other database versions can be obtained by contacting
#' Michael Bell
#' (http://homepages.cs.ncl.ac.uk/m.j.bell1/annotationQualityPaper.php)
#'
#' Full details in http://arxiv.org/abs/arXiv:1208.2175v1
#' @docType data
#' @format data frame
#' @source Bell, MJ, Gillespie, CS, Swan, D, Lord, P.
#' An approach to describing and analysing bulk biological annotation
#' quality: A case study using UniProtKB.
#' Bioinformatics 2012, 28, i562-i568.
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