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Add a rolling average

Source: R/add_rolling_average.R
add_rolling_average.Rd

add_rolling_average() adds a rolling average to an <incidence2> object. If multiple groupings or count variables are present then the average will be calculated for each.

Usage

add_rolling_average(
  x,
  n = 3L,
  complete_dates = TRUE,
  align = c("right", "center"),
  colname = "rolling_average",
  ...
)

Arguments

x

[incidence2] object

n

[integer]

How many date groupings to consider in each window?

double vectors will be converted via as.integer(n).

complete_dates

[bool]

Should incidence2::complete_dates() be called on the data prior to adding the rolling average.

Defaults to TRUE.

align

character, define if rolling window covers preceding rows ("right"), following rows ("left") or centered ("center"). Defaults to "right".

colname

[character]

The name of the column to contain the rolling average.

...

Other arguments passed to incidence2::complete_dates()

Value

The input object with an additional column for the rolling average.

Examples


if (requireNamespace("outbreaks", quietly = TRUE)) {
withAutoprint({

  data(ebola_sim_clean, package = "outbreaks")
  dat <- ebola_sim_clean$linelist
  dat <- subset(dat, date_of_onset <= as.Date("2014-10-05"))

  inci <- incidence2::incidence(
      dat,
      date_index = "date_of_onset",
      groups = "gender",
      interval = "isoweek"
  )

  add_rolling_average(inci, n = 3L)
  inci2 <- incidence2::regroup(inci)
  add_rolling_average(inci2, n = 7L)
})
}
#> > data(ebola_sim_clean, package = "outbreaks")
#> > dat <- ebola_sim_clean$linelist
#> > dat <- subset(dat, date_of_onset <= as.Date("2014-10-05"))
#> > inci <- incidence2::incidence(dat, date_index = "date_of_onset", groups = "gender", 
#> +     interval = "isoweek")
#> > add_rolling_average(inci, n = 3L)
#> # incidence:  52 x 5
#> # count vars: date_of_onset
#> # groups:     gender
#>    date_index gender count_variable count rolling_average
#>  * <isowk>    <fct>  <chr>          <int>           <dbl>
#>  1 2014-W15   f      date_of_onset      1          NA    
#>  2 2014-W15   m      date_of_onset      0          NA    
#>  3 2014-W16   f      date_of_onset      0          NA    
#>  4 2014-W16   m      date_of_onset      1          NA    
#>  5 2014-W17   f      date_of_onset      4           1.67 
#>  6 2014-W17   m      date_of_onset      1           0.667
#>  7 2014-W18   f      date_of_onset      4           2.67 
#>  8 2014-W18   m      date_of_onset      0           0.667
#>  9 2014-W19   f      date_of_onset      9           5.67 
#> 10 2014-W19   m      date_of_onset      3           1.33 
#> # … with 42 more rows
#> > inci2 <- incidence2::regroup(inci)
#> > add_rolling_average(inci2, n = 7L)
#> # incidence:  26 x 4
#> # count vars: date_of_onset
#>    date_index count_variable count rolling_average
#>  * <isowk>    <chr>          <int>           <dbl>
#>  1 2014-W15   date_of_onset      1           NA   
#>  2 2014-W16   date_of_onset      1           NA   
#>  3 2014-W17   date_of_onset      5           NA   
#>  4 2014-W18   date_of_onset      4           NA   
#>  5 2014-W19   date_of_onset     12           NA   
#>  6 2014-W20   date_of_onset     17           NA   
#>  7 2014-W21   date_of_onset     15            7.86
#>  8 2014-W22   date_of_onset     19           10.4 
#>  9 2014-W23   date_of_onset     23           13.6 
#> 10 2014-W24   date_of_onset     21           15.9 
#> # … with 16 more rows