Time-Based Rolling Binomial Probability

Produces a a rolling time-window based vector of binomial probability and confidence intervals.

Usage

tbr_binom(.tbl, x, tcolumn, unit = "years", n, alpha = 0.05)

Arguments

.tbl

dataframe with two variables.

x

indicates the variable column containing "success" and "failure" observations coded as 1 or 0.

tcolumn

indicates the variable column containing Date or Date-Time values.

unit

character, one of "years", "months", "weeks", "days", "hours", "minutes", "seconds"

n

numeric, describing the length of the time window in the selected units.

alpha

numeric, probability of a type 1 error, so confidence coefficient = 1-alpha

Value

tibble with binomial point estimate and confidence intervals.

See also

binom_ci

Examples

## Generate Sample Data
df <- tibble::tibble(
date = sample(seq(as.Date('2000-01-01'), as.Date('2015/12/30'), by = "day"), 100),
value = rbinom(100, 1, 0.25)
)

## Run Function
tbr_binom(df, x = value,
tcolumn = date, unit = "years", n = 5,
alpha = 0.1)
#> # A tibble: 100 × 5
#>    date       value PointEst  Lower Upper
#>    <date>     <int>    <dbl>  <dbl> <dbl>
#>  1 2000-01-13     0    0     0      0.895
#>  2 2000-05-09     1    0.5   0.0527 0.947
#>  3 2000-07-15     1    0.667 0.254  0.965
#>  4 2001-04-29     0    0.5   0.182  0.818
#>  5 2001-05-16     1    0.6   0.272  0.857
#>  6 2001-08-11     0    0.5   0.221  0.779
#>  7 2001-10-04     1    0.571 0.289  0.814
#>  8 2002-01-15     0    0.5   0.249  0.751
#>  9 2002-01-21     1    0.556 0.303  0.782
#> 10 2002-01-22     0    0.5   0.269  0.731
#> # ℹ 90 more rows