beta_cdf()
Learn how to use the beta_cdf() function to return a standard beta cumulative distribution function.
Returns the standard cumulative beta distribution function.
If probability = beta_cdf(x,…), then beta_inv(probability,…) = x.
The beta distribution is commonly used to study variation in the percentage of something across samples, such as the fraction of the day people spend watching television.
Syntax
beta_cdf(x, alpha, beta)
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
| x | int, long, or real | ✔️ | A value at which to evaluate the function. |
| alpha | int, long, or real | ✔️ | A parameter of the distribution. |
| beta | int, long, or real | ✔️ | A parameter of the distribution. |
Returns
The cumulative beta distribution function.
Examples
datatable(x:double, alpha:double, beta:double, comment:string)
[
0.9, 10.0, 20.0, "Valid input",
1.5, 10.0, 20.0, "x > 1, yields NaN",
double(-10), 10.0, 20.0, "x < 0, yields NaN",
0.1, double(-1.0), 20.0, "alpha is < 0, yields NaN"
]
| extend b = beta_cdf(x, alpha, beta)
Output
| x | alpha | beta | comment | b |
|---|---|---|---|---|
| 0.9 | 10 | 20 | Valid input | 0.999999999999959 |
| 1.5 | 10 | 20 | x > 1, yields NaN | NaN |
| -10 | 10 | 20 | x < 0, yields NaN | NaN |
| 0.1 | -1 | 20 | alpha is < 0, yields NaN | NaN |
Related content
- For computing the inverse of the beta cumulative probability density function, see beta-inv().
- For computing probability density function, see beta-pdf().
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