Apply a confidence interval to values in a dataframe based on the beta distribution.

Apply a confidence interval to values in a dataframe based on the beta distribution.

Usage

beta_interval(.data, alpha, beta, conf = 0.95)

Arguments

.data

Data frame; a confidence interval will be applied to each row in the data frame.

alpha

First shape parameter of the beta distribution, must be greater than 0

beta

Second shape parameter of the beta distribution, must be greater than 0

conf

Confidence interval, must be between [0, 1]. Defaults to 0.95.

See also

Other interval verbs: normal_interval()

Examples

# create example df
alpha <- rnorm(10, 100, 20)
beta <- rnorm(10, 80, 10)
example <- dplyr::bind_cols(alpha, beta)
#> New names:
#> • `` -> `...1`
#> • `` -> `...2`
colnames(example) <- c("alpha", "beta")

# apply the default confidence interval of 0.95
beta_interval(example, alpha, beta)
#> # A tibble: 10 × 4
#>    alpha  beta ci_lower ci_upper
#>    <dbl> <dbl>    <dbl>    <dbl>
#>  1  92.7  90.5    0.434    0.578
#>  2 117.   87.3    0.504    0.640
#>  3 123.   78.6    0.543    0.677
#>  4  75.8  62.5    0.465    0.630
#>  5 108.   53.6    0.594    0.739
#>  6 111.   69.6    0.543    0.684
#>  7  79.3  69.1    0.454    0.614
#>  8  99.4  77.5    0.488    0.634
#>  9 116.   80.2    0.523    0.660
#> 10  73.8  82.6    0.394    0.550

# apply a custom confidence interval
beta_interval(example, alpha, beta, conf = 0.99)
#> # A tibble: 10 × 4
#>    alpha  beta ci_lower ci_upper
#>    <dbl> <dbl>    <dbl>    <dbl>
#>  1  92.7  90.5    0.412    0.600
#>  2 117.   87.3    0.483    0.660
#>  3 123.   78.6    0.521    0.696
#>  4  75.8  62.5    0.439    0.655
#>  5 108.   53.6    0.570    0.759
#>  6 111.   69.6    0.520    0.705
#>  7  79.3  69.1    0.429    0.638
#>  8  99.4  77.5    0.465    0.656
#>  9 116.   80.2    0.501    0.680
#> 10  73.8  82.6    0.371    0.574