Nothing

```
#' Generate an index of quarters
#'
#' A function to create a quarter index variable
#'
#' @param x A vector or column of dates
#' @examples
#' # given a vector of dates
#' df <- data.frame(date = as.Date(c("2017-01-01","2017-04-01","2017-07-01","2017-08-01"),
#' format = "%Y-%m-%d"))
#' # calculate the time period variable
#' df$period <- quarterIndex(df$date)
#' df
#' @export
quarterIndex <- function(x){
firstDate <- min(x)
quarter <- ceiling(as.numeric(format(x,"%m"))/3)+
(as.numeric(format(x,"%Y"))-
as.numeric(format(firstDate,"%Y")))*4
quarter <- quarter - (quarter[which.min(x)]-1)
return(quarter)
}
#' Generate an index of years
#'
#' Function to create a year index variable
#'
#' @param x A vector or column of dates
#' @examples
#' # given a vector of dates
#' df <- data.frame(date = as.Date(c("2017-01-01","2018-04-01","2019-07-01","2019-08-01"),
#' format = "%Y-%m-%d"))
#' # calculate the time period variable
#' df$period <- yearIndex(df$date)
#' df
#' @export
yearIndex <- function(x){
firstDate <- min(x)
year <- as.numeric(format(x,"%Y"))-as.numeric(format(firstDate,"%Y"))+1
return(year)
}
#' Generate an index of weeks
#'
#' Function to create a week index variable with weeks
#' determined as defined in ISO 8601.
#' If the week (starting on Monday) containing 1 January has four
#' or more days in the new year, then it is considered week 1.
#' Otherwise, it is the 53rd week of the previous year, and the
#' next week is week 1.
#'
#' @param x A vector of dates
#' @examples
#' # given a vector of dates
#' df <- data.frame(date = as.Date(c("2016-12-20","2016-12-27","2017-01-01","2017-01-07"),
#' format = "%Y-%m-%d"))
#' # calculate the time period variable
#' df$period <- weekIndex(df$date)
#' df
#' @export
weekIndex <- function(x){
# we first need a measure of how many weeks are in each year in our sample
years <- sort(as.numeric(unique(format(x,"%Y"))))
# this gets the week number of December 31 for each of the years in
# the year vector
weeksInYears <- sapply(years,
function(y){as.numeric(format(as.Date(paste0(y,"-12-31")),"%V"))})
# If the week number is 1, then there must be 52 weeks in the year because
# it's saying that the end of the calendar year falls into week 1 of the
# following year.
weeksInYears[weeksInYears==1] <- 52
cumWeeks <- cumsum(weeksInYears)
# get the week number within the year of each date
weeks <- as.numeric(format(x,"%V"))
# get the year of each date in 'week-year' format. see ?strptime
weekYears <- as.numeric(format(x,"%G"))
# initialise a matrix for our final week index
week <- matrix(0, nrow=length(x), ncol=1)
# get the week of the first date in our sample, we'll use this to
# normalise our weekindex to start at 1
firstWeek <- as.numeric(format(min(x),"%V"))
# compute the week index as the week's number in the current year, plus the
# number of elapsed weeks in prior years, normalised to start at week 1.
for(i in seq_along(x)){
week[i,1] <- weeks[i] + cumWeeks[years==weekYears[i]] - cumWeeks[1] - (firstWeek-1)
}
return(as.vector(week))
}
#' Generate an index of months
#'
#' A function to create a month index variable
#'
#' @param x A vector or column of dates
#' @param overlapWeeks Tells monthIndex how to deal with weeks that
#' cross over two adjacent months. Options are "naive", "majority", "wholeOnly" or "fourWeek".
#' "naive" simply takes the month number of the observation, ignoring where
#' the week of that observation falls. "majority" will allocate the observation
#' to the month that owns the majority of days in that week, assuming
#' that Monday is day one of the week. "fourWeek" first calculates a week index,
#' then calculates the month index assuming that there are four weeks in each month.
#' "wholeOnly" will return NA for any dates falling inside a week that overlaps two
#' adjacent months; that is, only weeks that are wholly within a month
#' are given an index value. The default is "naive".
#' @examples
#' # given a vector of dates
#' df <- data.frame(date = as.Date(c("2017-01-01","2017-02-01","2017-03-01","2017-04-01"),
#' format = "%Y-%m-%d"))
#' # calculate the time period variable
#' df$period <- monthIndex(df$date, overlapWeeks = "naive")
#' df
#' @export
monthIndex <- function(x, overlapWeeks = "naive"){
validMethods <- c("naive","majority","wholeOnly","fourWeek")
if (!(overlapWeeks %in% validMethods)) {
stop("Not a valid option for parameter overlapWeeks. See helpfile ?monthIndex for valid options.")
}
switch (overlapWeeks,
naive = {
firstDate <- min(x)
firstYear <- as.numeric(format(firstDate,"%Y"))
adj = as.numeric(format(firstDate,"%m"))-1
month <- as.numeric(format(x,"%m"))+
(as.numeric(format(x,"%Y"))-
firstYear)*12-adj
},
majority = {
month <- monthIndex(x, overlapWeeks = "naive")
d <- as.numeric(format(x, "%d"))
wd <- as.numeric(format(x, "%u"))
m <- as.numeric(format(x, "%m"))
y <- as.numeric(format(x, "%Y"))
for (i in 1:length(month)) {
# if the week overlapped slightly into next month, push it back by 1
if (d[i] < 4 & wd[i] > 4 &
as.numeric(format(as.Date(paste0(1, "-", m[i], "-", y[i]),
format="%d-%m-%Y"),"%u")) > 4) {
month[i] <- month[i] - 1
}
# if the week overlapped slightly into previous month, push it forward by 1
else if (d[i] > 25) {
lastDay <- daysInMonth(x[i])
if (lastDay - d[i] < 3 & wd[i] < 4 &
as.numeric(format(as.Date(paste0(lastDay, "-", m[i], "-", y[i]),
format="%d-%m-%Y"),"%u")) < 4) {
month[i] <- month[i] + 1
}
}
}
},
fourWeek = {
week <- weekIndex(x)
month <- ceiling(week/4)
},
wholeOnly = {
month <- monthIndex(x, "naive")
wd <- as.numeric(format(x, "%u")) # day of the week, Monday = 1
sowMonth <- as.numeric(format(x - wd + 1, "%m"))
eowMonth <- as.numeric(format(x - wd + 7, "%m"))
month[!(sowMonth == eowMonth)] <- NA
}
)
return(month)
}
```

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