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_negative_binomial() Function.
The stats_cdf_negative_binomial() function in PHP calculates any one parameter of the negative binomial distribution given values for the others.
The stats_cdf_negative_binomial() function in PHP calculates any one parameter of the negative binomial distribution given values for the others.
Syntax
Following below is the syntax to use this function -
float stats_cdf_negative_binomial ( 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 built-in PHP function returns the CDF, its inverse, or one of its parameters of the negative binomial distribution. The kind of the return value and the 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 number of failures.
- r denotes the number of success.
- p denotes the success rate for each trial.
which | Return value | par1 | par2 | par3 |
---|---|---|---|---|
1 | CDF | x | r | p |
2 | x | CDF | r | p |
3 | r | x | CDF | p |
4 | p | x | CDF | r |
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 (S, XN, PR).
- P is the cumulative from 0 to S of the negative binomial distribution. Input range: [0, 1].
- S is the upper limit of cumulation of the negative binomial distribution. There are F or fewer failures before the XN success.
- XN is the number of successes.
- PR is the probability of success in each of the binomial trial.
<?php // which = 1 : calculate P from (S, XN, PR) var_dump(round(stats_cdf_negative_binomial(2, 1, 0.4, 1), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(0.784)
Example2
In the following example below, when which = 2, calculate S from (P, XN, PR).
- P is the cumulative from 0 to S of the negative binomial distribution. Input range: [0, 1].
- S is the upper limit of cumulation of the negative binomial distribution. There are F or fewer failures before the XN success.
- XN is the number of successes.
- PR is the probability of success in each of the binomial trial.
<?php // which = 2 : calculate S from (P, XN, PR) var_dump(round(stats_cdf_negative_binomial(0.784, 1, 0.4, 2), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(2)
Example3
In the following example below, when which = 3, calculate XN from (P, S, PR).
- P is the cumulative from 0 to S of the negative binomial distribution. Input range: [0, 1].
- S is the upper limit of cumulation of the negative binomial distribution. There are F or fewer failures before the XN success.
- XN is the number of successes.
- PR is the probability of success in each of the binomial trial.
<?php // which = 3 : calculate XN from (P, S, PR) var_dump(round(stats_cdf_negative_binomial(0.784, 2, 0.4, 3), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(1)
Example4
In the following example below, when which = 4, calculate PR from (P, S, XN).
- P is the cumulative from 0 to S of the negative binomial distribution. Input range: [0, 1].
- S is the upper limit of cumulation of the negative binomial distribution. There are F or fewer failures before the XN success.
- XN is the number of successes.
- PR is the probability of success in each of the binomial trial.
<?php // which = 4 : calculate PR from (P, S, XN) var_dump(round(stats_cdf_negative_binomial(0.784, 2, 1, 4), 6)); ?>
Output
When the above code is executed, it will produce the following result -
float(0.4)
Example5
Following is an error case. In the following example below which<1, warning message is displayed in logs.
<?php var_dump(stats_cdf_negative_binomial(2, 1, 0.4, 0)); // which < 1 ?>
Output
The above code will produce the following result and a warning in logs PHP Warning: stats_cdf_negative_binomial(): The fourth parameter should to 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_negative_binomial(2, 1, 0.4, 5)); // which > 4 ?>
Output
The above code will produce the following result and a warning in logs PHP Warning: stats_cdf_negative_binomial(): The fourth parameter should to be in the 1..4 range.
bool(false)
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_noncentral_chisquare() 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.