Hello folks! welcome back to a new edition of our tutorial on PHP. In this tutorial guide, we are going to be studying about the PHP stats_cdf_beta() Function.
The built-in PHP stats_cdf_beta() function calculates any one parameter of the beta distribution given values for the others.
The built-in PHP stats_cdf_beta() function calculates any one parameter of the beta distribution given values for the others.
Syntax
Following below is the syntax to use this function -
float stats_cdf_beta( float $par1, float $par2, float $par3, int $which)
Parameter Details
| Sr.No | Parameter | Description |
|---|---|---|
| 1 | par1 | The first parameter |
| 2 | par2 | The second parameter |
| 3 | par3 | The third parameter |
| 4 | which | The flag to determine what to be calculated |
Return Value
This PHP function returns the cumulative distribution function, its inverse, or one of its parameters, of the beta distribution. The kind of return values and parameters (par1, par2, and par3) are determined by which.
The following table list the return value and parameters by which.
The following table list the return value and parameters by which.
- CDF denotes cumulative distribution function.
- x denotes the value of the random variable.
- alpha and beta denotes shape parameters of the beta distribution.
| which | Return value | par1 | par2 | par3 |
|---|---|---|---|---|
| 1 | CDF | x | alpha | beta |
| 2 | x | CDF | alpha | beta |
| 3 | alpha | x | CDF | beta |
| 4 | beta | x | CDF | alpha |
Dependencies
This built-in function was first introduced in statistics extension (PHP version 4.0.0 and PEAR v1.4.0). In this tutorial guide, we used the latest release of stats-2.0.3 (PHP v7.0.0 or newer and PEAR version 1.4.0 or newer).
Example1
In the following example below, when which = 1, calculate P from (X, A, B).
- P is the integral from 0 to X of the chi-square distribution. Input range: [0, 1].
- X is the upper limit of integration of beta density. Input range: [0, 1].
- A is the first parameter of the beta density. Input range: (0, +infinity).
- B is the second parameter of the beta density. Input range: (0, +infinity).
<?php // which = 1 : calculate P from (X, A, B) var_dump(round(stats_cdf_beta(0.5, 2, 4, 1), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(0.8125)
Example2
In the following example below, when which = 2, calculate X from (P, A, B).
- P is the integral from 0 to X of the chi-square distribution. Input range: [0, 1].
- X is the upper limit of integration of beta density. Input range: [0, 1].
- A is the first parameter of the beta density. Input range: (0, +infinity).
- B is the second parameter of the beta density. Input range: (0, +infinity).
<?php // which = 2 : calculate X from (P, A, B) var_dump(round(stats_cdf_beta(0.8125, 2, 4, 2), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(0.5)
Example3
In the following example below, when which = 3, calculate A from (P, X, B).
- P is the integral from 0 to X of the chi-square distribution. Input range: [0, 1].
- X is the upper limit of integration of beta density. Input range: [0, 1].
- A is the first parameter of the beta density. Input range: (0, +infinity).
- B is the second parameter of the beta density. Input range: (0, +infinity).
<?php // which = 3 : calculate A from (P, X, B) var_dump(round(stats_cdf_beta(0.8125, 0.5, 4, 3), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(2)
Example4
In the following example below, when which = 4, calculate B from (P, X, A).
- P is the integral from 0 to X of the chi-square distribution. Input range: [0, 1].
- X is the upper limit of integration of beta density. Input range: [0, 1].
- A is the first parameter of the beta density. Input range: (0, +infinity).
- B is the second parameter of the beta density. Input range: (0, +infinity).
<?php // which = 4 : calculate B from (P, X, A) var_dump(round(stats_cdf_beta(0.8125, 0.5, 2, 4), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(4)
Example5
Following is an error case. In the following example below which<1, warning message is displayed in logs.
<?php var_dump(stats_cdf_beta(0.5, 2, 4, 0)); // which < 1 ?>
Output
The above code will produce the following result and a warning in logs PHP Warning: stats_cdf_beta(): Fourth parameter should be in the 1..4 range.
bool(false)
Example6
Following is an error case. In the following example below which>4, warning message is displayed in logs.
<?php var_dump(stats_cdf_beta(0.5, 2, 4, 5)); // which > 4 ?>
Output
The above code will produce the following result and a warning in logs PHP Warning: stats_cdf_beta(): Fourth parameter should be in the 1..4 range.
bool(false)
READ: PHP | Statistics Module
Alright guys! This is where we are going to be rounding up for this tutorial post. In our next tutorial, we are going to be discussing about the stats_cdf_binomial() Function in PHP.
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Feel free to ask your questions where necessary and we will attend to them as soon as possible. If this tutorial was helpful to you, you can use the share button to share this tutorial.
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Thanks for reading and bye for now.