R/depthproc.R

In DepthProc: Statistical Depth Functions for Multivariate Analysis

#' US Labour dataset
#' @docType data
#' @keywords datasets
#' @name USLABOUR
#' @usage data(USLABOUR)
#' @format A data frame with 654 rows and 4 variables
#' @source U.S.Department of Labor --- Bureau of Labour Statistics FRED
#'
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#' Children under 5 months mortality rate per 1,000 live births
#' @docType data
#' @keywords datasets
#' @name under5.mort
#' @usage data(under5.mort)
#' @format A data frame with 654 rows and 4 variables
#' @source http://mdgs.un.org/unsd/mdg/Data.aspx
#'
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#' Infant mortality rate (0--1 year) per 1,000 live births
#' @docType data
#' @keywords datasets
#' @name inf.mort
#' @usage data(inf.mort)
#' @format A data frame with 654 rows and 4 variables
#' @source http://mdgs.un.org/unsd/mdg/Data.aspx
#'
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#' Children 1 year old immunized against measles, percentage
#' @docType data
#' @keywords datasets
#' @name maesles.imm
#' @usage data(maesles.imm)
#' @format A data frame with 654 rows and 4 variables
#' @source http://mdgs.un.org/unsd/mdg/Data.aspx
#'
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#' Internet view data
#' @docType data
#' @keywords datasets
#' @name internet.users
#' @usage data(internet.users)
#' @format data frame containing 17518 rows and 6 columns --- 17518 working days of the
#' Internet service considered with respect to variables:
#' service, month, day, hour, unique users and page views.
#' @references Kosiorowski, Rydlewski, Snarska (2016), Detecting a Structural Change in Functional Time Series Using Local Wilcoxon Statistic, arXiv: 1604.03776v2
#'
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#' Relation between minimum wage (MW) and unemployment rate (UR) in France.
#'
#' @docType data
#' @keywords datasets
#' @name france
#' @usage data(france)
#' @format data frame containing 17 rows and two column. MW is a minimum wage, and UR is an unemployment rate.
#'
#'
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#' Air pollution in Katowice city by hour.
#'
#' @docType data
#' @keywords datasets
#' @name katowice.airpollution
#' @usage data("katowice.airpollution")
#' @format data frame containing 181 rows (days) and 24 columns. Each column is an air pollination for given hour.
#'
#'
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#' Air pollution with PM10 in Cracow within day and night in December 2016
#'
#' @docType data
#' @keywords datasets
#' @name cracow.airpollution
#' @usage data("cracow.airpollution")
#' @format data frame containing 744 rows.
#'
#' @references
#'
#' 1. Kosiorowski D, Rydlewski J P, Zawadzki Z (2017). 'Functional Outliers Detection By The Example Of Air Quality Monitoring.' submitted.
#'
#' 2. Kosiorowski D, Szlachtowska E (2017). 'K- local Median Algorithm for Functional Data in Empirical Analysis of Air Pollution Data.' Proceedings from the 11th Professor A. Zelias International Conference, pp. 153-162. Cracow University of Economics.
#'
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