beta_cdf()

Returns the standard cumulative beta distribution function.

beta_cdf(0.2, 10.0, 50.0)

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)

Arguments

• x: A value at which to evaluate the function.
• alpha: A parameter of the distribution.
• beta: A parameter of the distribution.

Returns

• The cumulative beta distribution function.

Notes

If any argument is nonnumeric, beta_cdf() returns null value.

If x < 0 or x > 1, beta_cdf() returns NaN value.

If alpha ≤ 0 or alpha > 10000, beta_cdf() returns the NaN value.

If beta ≤ 0 or beta > 10000, beta_cdf() returns the NaN value.

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)

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

See also

• For computing the inverse of the beta cumulative probability density function, see beta-inv().
• For computing probability density function, see beta-pdf().