#' Sample labels of cluster groups
#'
#' A dataframe of alphabetical labels representing
#' the optimal solution of `traj` dataset based on `akClust`
#' function
#'
#' @format A dataframe containing one variable:
#' \itemize{
#' \item label: alphabetical label by clusters
#' }
"clustr"
#' Simulated population data.
#'
#' Sample simulated population data to be used as
#' the denominator variable against `traj` dataset. Contains
#' data for two consecutive census years
#'
#' @format A dataframe with the following variables:
#' \itemize{
#' \item location_id: Character id of sample census unit
#' at which the population is obtained.
#' \item census_2003: Population estimates at the sample
#' locations for the census year 2003.
#' \item census_2007: Population estimates at the sample
#' locations for the census year 2007.
#' }
"popl"
#' Simulated longitudinal dataset
#'
#' Contains simulated trajectories belonging to one of the
#' three pre-defined groups, namely (a) decreasing, (b) stable
#' and (c) increasing groups.
#'
#' @format A dataframe with the following variables:
#' \itemize{
#' \item X1: Values across locations at time step 1
#' \item X2: Values across locations at time step 2
#' \item X3: Values across locations at time step 3
#' \item X4: Values across locations at time step 4
#' \item X5: Values across locations at time step 5
#' \item X6: Values across locations at time step 6
#' \item X7: Values across locations at time step 7
#' \item X8: Values across locations at time step 8
#' \item X9: Values across locations at time step 9
#' \item X10: Values across locations at time step 10
#' \item X11: Values across locations at time step 11
#' \item X12: Values across locations at time step 12
#' \item X13: Values across locations at time step 13
#' \item X14: Values across locations at time step 14
#' \item X15: Values across locations at time step 15
#' \item X16: Values across locations at time step 16
#' \item X17: Values across locations at time step 17
#' \item X18: Values across locations at time step 18
#' \item X19: Values across locations at time step 19
#' \item X20: Values across locations at time step 20
#' \item X21: Values across locations at time step 21
#' }
"simulated"
#' Time-at-risk for the Adjudicated Toronto
#' Youth Data (Sample 1)
#'
#' Real-life time-at-risk per year for 378 individuals
#' from the age of 8 to 38 in the Toronto, Ontario, Canada.
#' The data is obtained through the R package `crimCV`.
#' For further information, please see: Nielsen, J. (2018)
#' crimCV: Group-Based Modelling of Longitudinal Data.
#' R package version 0.9.6.
#' URL https://CRAN.R-project.org/package=crimCV.
#'
#' @format A dataframe with the following variables:
#' \itemize{
#' \item 8: Time-at-risk per year at age 8
#' \item 9: Time-at-risk per year at age 9
#' \item 10: Time-at-risk per year at age 10
#' \item 11: Time-at-risk per year at age 11
#' \item 12: Time-at-risk per year at age 12
#' \item 13: Time-at-risk per year at age 13
#' \item 14: Time-at-risk per year at age 14
#' \item 15: Time-at-risk per year at age 15
#' \item 16: Time-at-risk per year at age 16
#' \item 17: Time-at-risk per year at age 17
#' \item 18: Time-at-risk per year at age 18
#' \item 19: Time-at-risk per year at age 19
#' \item 20: Time-at-risk per year at age 20
#' \item 21: Time-at-risk per year at age 21
#' \item 22: Time-at-risk per year at age 22
#' \item 23: Time-at-risk per year at age 23
#' \item 24: Time-at-risk per year at age 24
#' \item 25: Time-at-risk per year at age 25
#' \item 26: Time-at-risk per year at age 26
#' \item 27: Time-at-risk per year at age 27
#' \item 28: Time-at-risk per year at age 28
#' \item 29: Time-at-risk per year at age 29
#' \item 30: Time-at-risk per year at age 30
#' \item 31: Time-at-risk per year at age 31
#' \item 32: Time-at-risk per year at age 32
#' \item 33: Time-at-risk per year at age 33
#' \item 34: Time-at-risk per year at age 34
#' \item 35: Time-at-risk per year at age 35
#' \item 36: Time-at-risk per year at age 36
#' \item 37: Time-at-risk per year at age 37
#' \item 38: Time-at-risk per year at age 38
#' }
"TO1Risk"
#' Sample longitudinal dataset
#'
#' Simulated longitudinal datasets containing
#' trajectories with missing values
#' (\code{NA}, \code{Inf}, \code{null})
#'
#' @format A dataframe with the following variables:
#' \itemize{
#' \item location_ids: Character id of sample locations
#' at which values are obtained.
#' \item X2001: Values at time step 1 (i.e. year 2001)
#' \item X2002: Values at time step 2 (i.e. year 2002)
#' \item X2003: Values at time step 3 (i.e. year 2003)
#' \item X2004: Values at time step 4 (i.e. year 2004)
#' \item X2005: Values at time step 5 (i.e. year 2005)
#' \item X2006: Values at time step 6 (i.e. year 2006)
#' \item X2007: Values at time step 7 (i.e. year 2007)
#' \item X2008: Values at time step 8 (i.e. year 2008)
#' \item X2009: Values at time step 9 (i.e. year 2009)
#' }
"traj"
#' Sample longitudinal dataset containing whitespaces
#'
#' Longitudinal dataset with both trailing and leading
#' whitespaces. For example, there is a trailing whitespace
#' at cell [3, 6], while there is a leading whitespace
#' at cell [9, 4].
#'
#' @format A dataframe with the following variables:
#' \itemize{
#' \item location_ids: Character id of sample locations
#' at which values are obtained.
#' \item X2001: Values at time step 1 (i.e. year 2001)
#' \item X2002: Values at time step 2 (i.e. year 2002)
#' \item X2003: Values at time step 3 (i.e. year 2003)
#' \item X2004: Values at time step 4 (i.e. year 2004)
#' \item X2005: Values at time step 5 (i.e. year 2005)
#' \item X2006: Values at time step 6 (i.e. year 2006)
#' \item X2007: Values at time step 7 (i.e. year 2007)
#' \item X2008: Values at time step 8 (i.e. year 2008)
#' \item X2009: Values at time step 9 (i.e. year 2009)
#' }
"traj_w_spaces"
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