timeplyr (version 1.1.0)

get_time_delay: Get summary statistics of time delay

Description

The output is a list containing summary statistics of time delay between two date/datetime vectors. This can be especially useful in estimating reporting delay for example.

• data - A data frame containing the origin, end and calculated time delay.

• unit - The chosen time unit.

• num - The number of time units.

• summary - tibble with summary statistics.

• delay - tibble containing the empirical cumulative distribution function values by time delay.

• plot - A ggplot of the time delay distribution.

Usage

get_time_delay(
  data,
  origin,
  end,
  timespan = 1L,
  min_delay = -Inf,
  max_delay = Inf,
  probs = c(0.25, 0.5, 0.75, 0.95),
  .by = NULL,
  include_plot = TRUE,
  x_scales = "fixed",
  bw = "sj",
  ...
)

Value

A list containing summary data, summary statistics and an optional ggplot.

Arguments

data

A data frame.

origin

Origin date variable.

end

End date variable.

timespan

timespan.

min_delay

The minimum acceptable delay, all delays less than this are removed before calculation. Default is min_delay = -Inf.

max_delay

The maximum acceptable delay, all delays greater than this are removed before calculation. Default is max_delay = Inf.

probs

Probabilities used in the quantile summary. Default is probs = c(0.25, 0.5, 0.75, 0.95).

.by

(Optional). A selection of columns to group by for this operation. Columns are specified using tidy-select.

include_plot

Should a ggplot graph of delay distributions be included in the output?

x_scales

Option to control how the x-axis is displayed for multiple facets. Choices are "fixed" or "free_x".

bw

The smoothing bandwidth selector for the Kernel Density estimator. If numeric, the standard deviation of the smoothing kernel. If character, a rule to choose the bandwidth. See ?stats::bw.nrd for more details. The default has been set to "SJ" which implements the Sheather & Jones (1991) method, as recommended by the R team ?stats::density. This differs from the default implemented by stats::density() which uses Silverman's rule-of-thumb.

...

Further arguments to be passed on to ggplot2::geom_density().

Examples

library(timeplyr)
library(outbreaks)
library(dplyr)
# \dontshow{
.n_dt_threads <- data.table::getDTthreads()
.n_collapse_threads <- collapse::get_collapse()$nthreads
data.table::setDTthreads(threads = 1L)
collapse::set_collapse(nthreads = 1L)
# }
ebola_linelist <- ebola_sim_clean$linelist

# Incubation period distribution

# 95% of individuals experienced an incubation period of <= 26 days
inc_distr_days <- ebola_linelist %>%
  get_time_delay(date_of_infection,
                 date_of_onset,
                 time = "days")
head(inc_distr_days$data)
inc_distr_days$unit
inc_distr_days$num
inc_distr_days$summary
head(inc_distr_days$delay) # ECDF and freq by delay
inc_distr_days$plot

# Can change bandwidth selector
inc_distr_days <- ebola_linelist %>%
  get_time_delay(date_of_infection,
                 date_of_onset,
                 time = "day",
                 bw = "nrd")
inc_distr_days$plot

# Can choose any time units
inc_distr_weeks <- ebola_linelist %>%
  get_time_delay(date_of_infection,
                 date_of_onset,
                 time = "weeks",
                 bw = "nrd")
inc_distr_weeks$plot
# \dontshow{
data.table::setDTthreads(threads = .n_dt_threads)
collapse::set_collapse(nthreads = .n_collapse_threads)
# }