Nothing
#' aemet data
#'
#' @description Series of daily summaries of 73 spanish weather stations selected for the
#' period 1980-2009. The dataset contains geographic information of each
#' station and the average for the period 1980-2009 of daily temperature, daily
#' precipitation and daily wind speed.
#' @details Meteorological State Agency of Spain (AEMET), \url{https://www.aemet.es/es/portada}. Government of Spain.\cr
#' It marks 36 UTF-8 string of names of stations and 3 UTF-8 string names of provinces through the function \code{\link{iconv}}.\cr
#'
#' @name aemet
#' @docType data
#' @format Elements of aemet:\cr \code{..$df:} Data frame with information of
#' each wheather station:
#' \itemize{
#' \item \code{ind:} Indicated weather station.
#' \item \code{name:} Station Name. 36 marked UTF-8 strings.
#' \item \code{province:}Province (region) of Spain. 36 marked UTF-8 strings
#' \item \code{altitude:} Altitude of the station (in meters).
#' \item \code{year.ini:} Start year.
#' \item \code{year.end:} End year.
#' \item \code{longitude:} x geographic coordinate of the station (in decimal degrees).
#' \item \code{latitude:} y geographic coordinate of the station (in decimal degrees).
#' }
#' The functional variables:
#' \itemize{
#' \item \code{...$temp}: mean curve of the average daily temperature
#' for the period 1980-2009 (in degrees Celsius, marked with UTF-8 string).
#' In leap years temperatures for February 28 and 29 were averaged.
#' \item \code{...$wind.speed}: mean curve of the average daily wind speed for the
#' period 1980-2009 (in m/s).
#' \item \code{...$logprec}: mean curve of the log precipitation for
#' the period 1980-2009 (in log mm). Negligible precipitation
#' (less than 1 tenth of mm) is replaced by \code{0.05} and no precipitation
#' (0.0 mm) is replaced by \code{0.01}. Then the logarithm is applied.
#' }
#' @author Manuel Febrero Bande, Manuel Oviedo de la Fuente
#' \email{manuel.oviedo@@udc.es}
#' @source The data were obtained from the FTP of AEMET in 2009.
#' @keywords datasets
#' @examples
#' \dontrun{
#' data(aemet)
#' names(aemet)
#' names(aemet$df)
#' class(aemet)<-c("ldata","list") # ldata object
#' lat <- ifelse(aemet$df$latitude<31,"red","blue")
#' plot(aemet,col=lat)
#' }
NULL
#' tecator data
#'
#' Water, Fat and Protein content of meat samples
#'
#' \code{absorp.fdata} absorbance data for 215 samples. The first 129 were
#' originally used as a training set endpoints the percentages of Fat, Water
#' and Protein.\cr for more details see tecator package
#'
#' @name tecator
#' @docType data
#' @format The format is: \cr \code{..$absorp.fdata}: absorbance data.
#' \code{fdata} class object with: \cr \itemize{ \item \code{"data"}: Matrix of
#' class \code{fdata} with 215 curves (rows) discretized in 100 points or
#' argvals (columns).\cr \item \code{"argvals"}: 100 discretization points from
#' 850 to 1050mm \cr \item \code{"rangeval"}=(850,1050):
#' range(\code{"argvals"}) \item \code{"names"} list with: \code{main} an
#' overall title "Tecator data set", \code{xlab} title for \code{x} axis
#' "Wavelength (mm)" and \code{ylab} title for \code{y} axis "Absorbances". }
#' \code{..$y}: the percentages of Fat, Water and Protein. The three contents
#' are determined by analytic chemistry.\cr
#' @author Manuel Febrero-Bande and Manuel Oviedo de la Fuente \email{manuel.oviedo@@udc.es}
#' @keywords datasets
#' @examples
#' data(tecator)
#' names(tecator)
#' names(tecator$absorp.fdata)
#' names(tecator$y)
#' names(tecator$y)
#' class(tecator$absorp.fdata)
#' class(tecator$y)
#' dim(tecator$absorp.fdata)
#' dim(tecator$y)
#'
NULL
#' poblenou data
#'
#' NOx levels measured every hour by a control station in Poblenou in Barcelona
#' (Spain).
#'
#' The dataset starts on 23 February and ends on 26 June, in 2005. We split the
#' whole sample of hourly measures in a dataset of functional trajectories of
#' 24 h observations (each curve represents the evolution of the levels in 1
#' day).\cr Twelve curves that contained missing data were eliminated.
#'
#' @name poblenou
#' @docType data
#' @format The format is:\cr \code{..$nox}: \code{fdata} class object with: \cr
#' i.- \code{"data"}: Matrix with 115 curves (rows) discretized in 24 points or
#' argvals (columns).\cr ii.- \code{"argvals": 0:23}\cr iii.-
#' \code{"rangeval"=(0,23)}: range(\code{"argvals"}), \cr iv.- \code{"names"}
#' list with: \code{main} an overall title "NOx data set", \code{xlab} title
#' for \code{x} axis "Hours" and \code{ylab} title for \code{y} axis "NOx
#' (mglm^3)".\cr \cr \code{..$df}: Data Frame with (115x3) dimension. \cr
#' "date" in the first column.\cr Second column ("day.week"). Factor levels:
#' "Monday" 1, "Tuesday" 2, "Wednesday" 3, "Thursday" 4, "Friday" 5, "Saturday"
#' 6 and "Sunday" 7.\cr Third column "day.festive". Factor levels: "non
#' festive day" 0 and "festive day" 1.\cr
#' @author Febrero-Bande, M and Oviedo de la Fuente, Manuel
#' @references Febrero-Bande, M., Galeano, P., and Gonzalez-Manteiga, W.
#' (2008). \emph{Outlier detection in functional data by depth measures with
#' application to identify abnormal NOx levels}. Environmetrics 19, 4, 331-345.
#' @source \url{https://mediambient.gencat.cat/ca/inici}
#' @keywords datasets
#' @examples
#'
#' data(poblenou)
#' names(poblenou)
#' names(poblenou$nox)
#' nox<-poblenou$nox
#' class(nox)
#' ind.weekend<-as.integer(poblenou$df[,"day.week"])>5
#' plot(nox,col=ind.weekend+1)
#'
NULL
#' phoneme data
#'
#' Phoneme curves
#'
#' The following instructions have been used file: \cr
#' \url{https://www.math.univ-toulouse.fr/~ferraty/SOFTWARES/NPFDA/npfda-phondiscRS.txt}\cr
#' of \code{Phoneme dataset} file.
#'
#' @name phoneme
#' @docType data
#' @format Elements of phoneme:\cr \code{..$learn}: learning sample of curves.
#' \code{fdata} class object with: i.- \code{"data"}: Matrix of class
#' \code{fdata} with 250 curves (rows) discretized in 150 points or argvals
#' (columns).\cr, ii.- \code{"argvals"}, iii.- \code{"rangeval"}:
#' range(\code{"argvals"}), iv.- \code{"names"} list with: \code{main} an
#' overall title "Phoneme learn", \code{xlab} title for \code{x} axis
#' "frequencies" and \code{ylab} title for \code{y} axis "log-periodograms".\cr
#' \cr \code{..$test}: testing sample of curves. \code{fdata} class object
#' with: i.- \code{"data"}: Matrix of class \code{fdata} with 250 curves (rows)
#' discretized in 150 points or argvals (columns).\cr, ii.- \code{"argvals"},
#' iii.- \code{"rangeval"}: range(\code{"argvals"}), iv.- \code{"names"} list
#' with: \code{main} an overall title "Phoneme learn", \code{xlab} title for
#' \code{x} axis "frequencies" and \code{ylab} title for \code{y} axis
#' "log-periodograms".\cr \cr \code{..$classlearn}:learning class numbers (as
#' factor). Factor levels: "sh" 1, "iy" 2, "dcl" 3, "aa" 4 and "ao" 5.\cr \cr
#' \code{..$classtest}: testing class numbers (as factor). Factor levels: "sh"
#' 1, "iy" 2, "dcl" 3, "aa" 4 and "ao" 5.\cr
#' @author Manuel Febrero-Bande and Manuel Oviedo de la Fuente
#' <manuel.oviedo@@udc.es>
#' @references Ferraty, F. and Vieu, P. (2006). \emph{NPFDA in practice}. Free
#' access on line at \url{https://www.math.univ-toulouse.fr/~ferraty/SOFTWARES/NPFDA/}
#' @source
#' \url{https://www.math.univ-toulouse.fr/~ferraty/SOFTWARES/NPFDA/npfda-datasets.html}
#' @keywords datasets
#' @examples
#'
#' data(phoneme)
#' names(phoneme)
#' names(phoneme$learn)
#' class(phoneme$learn)
#' dim(phoneme$learn)
#' table(phoneme$classlearn)
#'
NULL
#' Mithochondiral calcium overload (MCO) data set
#'
#' The mithochondiral calcium overload (MCO) was measured in two groups
#' (control and treatment) every 10 seconds during an hour in isolated mouse
#' cardiac cells. In fact, due to technical reasons, the original experiment
#' [see Ruiz-Meana et al. (2000)] was performed twice, using both the "intact",
#' original cells and "permeabilized" cells (a condition related to the
#' mitochondrial membrane).
#'
#'
#' @name MCO
#' @docType data
#' @format Elements of MCO:\cr \code{..$intact}: \code{fdata} class object with
#' ``intact cells''curves,\cr \itemize{ \item \code{"data"}: Matrix of class
#' \code{fdata} with 89 intact cells curves (rows) measured every 10 seconds
#' during an hour in isolated mouse cardiac cell. \item \code{"argvals"}, 360
#' discretization points from seond 0 to 3590. \item \code{"rangeval"}:
#' range(\code{"argvals"}). \item \code{"names"} list with: \code{main} an
#' overall title "Control Intact Treatment", \code{xlab} title for \code{x}
#' axis "seconds" and \code{ylab} title for \code{y} axis "Ca". }
#' \code{..$classintact}: Factor levels of ``intact cells'' curves: "1" control
#' group and "2" treatment group.\cr
#'
#' \code{..$permea}: \code{fdata} class object with ``permeabilized cells''
#' curves (whose membrane has been removed), \itemize{ \item \code{"data"}:
#' Matrix of class \code{fdata} with 90 permeabilizzed cells curves (rows)
#' measured every 10 seconds during an hour in isolated mouse cardiac cell.
#' \item \code{"argvals"}, 360 discretization points from seond 0 to 3590.
#' \item \code{"rangeval"}: range(\code{"argvals"}). \item \code{"names"} list
#' with: \code{main} an overall title "Control Intact Treatment", \code{xlab}
#' title for \code{x} axis "seconds" and \code{ylab} title for \code{y} axis
#' "Ca". } \code{..$classpermea}: Factor levels of ``permeabilized cells''
#' curves: "1" control group and "2" treatment group.\cr
#' @note The structure of the curves during the initial period (first 180
#' seconds) of the experiment shows a erratic behavior (not very relevant in
#' the experiment context) during this period.
#' @references
#'
#' Ruiz--Meana M, Garcia-Dorado D, Pina P, Inserte J, Agullo L, Soler--Soler J.
#' Cariporide preserves mitochondrial proton gradient and delays ATP depletion
#' in cardiomyocytes during ischemic conditions. \emph{American Journal
#' Physiology Heart Circulatori Physiology}. 2003 Sep;285(3):H999--1006.
#' @keywords datasets
#' @examples
#'
#' data(MCO)
#' names(MCO)
#' par(mfrow=c(1,2))
#' plot(MCO$intact,col=MCO$classintact)
#' plot(MCO$permea,col=MCO$classpermea)
#'
NULL
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.