NAG CL Interfaceg01fec (inv_​cdf_​beta)

1Purpose

g01fec returns the deviate associated with the given lower tail probability of the beta distribution.

2Specification

 #include
 double g01fec (double p, double a, double b, double tol, NagError *fail)
The function may be called by the names: g01fec, nag_stat_inv_cdf_beta or nag_deviates_beta.

3Description

The deviate, ${\beta }_{p}$, associated with the lower tail probability, $p$, of the beta distribution with parameters $a$ and $b$ is defined as the solution to
 $PB≤βp:a,b=p=Γa+b ΓaΓb ∫0βpBa-11-Bb-1dB, 0≤βp≤1;a,b>0.$
The algorithm is a modified version of the Newton–Raphson method, following closely that of Cran et al. (1977).
An initial approximation, ${\beta }_{0}$, to ${\beta }_{p}$ is found (see Cran et al. (1977)), and the Newton–Raphson iteration
 $βi=βi-1-fβi-1 f′βi-1 ,$
where $f\left(\beta \right)=P\left(B\le \beta :a,b\right)-p$ is used, with modifications to ensure that $\beta$ remains in the range $\left(0,1\right)$.

4References

Cran G W, Martin K J and Thomas G E (1977) Algorithm AS 109. Inverse of the incomplete beta function ratio Appl. Statist. 26 111–114
Hastings N A J and Peacock J B (1975) Statistical Distributions Butterworth

5Arguments

1: $\mathbf{p}$double Input
On entry: $p$, the lower tail probability from the required beta distribution.
Constraint: $0.0\le {\mathbf{p}}\le 1.0$.
2: $\mathbf{a}$double Input
On entry: $a$, the first parameter of the required beta distribution.
Constraint: $0.0<{\mathbf{a}}\le {10}^{6}$.
3: $\mathbf{b}$double Input
On entry: $b$, the second parameter of the required beta distribution.
Constraint: $0.0<{\mathbf{b}}\le {10}^{6}$.
4: $\mathbf{tol}$double Input
On entry: the relative accuracy required by you in the result. If g01fec is entered with tol greater than or equal to $1.0$ or less than (see X02AJC), the value of is used instead.
5: $\mathbf{fail}$NagError * Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6Error Indicators and Warnings

On any of the error conditions listed below except ${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_RES_NOT_ACC or NE_SOL_NOT_CONV g01fec returns $0.0$.
NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
NE_REAL_ARG_GT
On entry, ${\mathbf{a}}=〈\mathit{\text{value}}〉$ and ${\mathbf{b}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{a}}\le {10}^{6}$.
On entry, ${\mathbf{a}}=〈\mathit{\text{value}}〉$ and ${\mathbf{b}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{b}}\le {10}^{6}$.
On entry, ${\mathbf{p}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{p}}\le 1.0$.
NE_REAL_ARG_LE
On entry, ${\mathbf{a}}=〈\mathit{\text{value}}〉$ and ${\mathbf{b}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{a}}>0.0$.
On entry, ${\mathbf{a}}=〈\mathit{\text{value}}〉$ and ${\mathbf{b}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{b}}>0.0$.
NE_REAL_ARG_LT
On entry, ${\mathbf{p}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{p}}\ge 0.0$.
NE_RES_NOT_ACC
The requested accuracy has not been achieved. Use a larger value of tol. There is doubt concerning the accuracy of the computed result. $100$ iterations of the Newton–Raphson method have been performed without satisfying the accuracy criterion (see Section 9). The result should be a reasonable approximation of the solution.
NE_SOL_NOT_CONV
The solution has failed to converge. However, the result should be a reasonable approximation. Requested accuracy not achieved when calculating beta probability. You should try setting tol larger.

7Accuracy

The required precision, given by tol, should be achieved in most circumstances.

8Parallelism and Performance

g01fec is not threaded in any implementation.

The typical timing will be several times that of g01eec and will be very dependent on the input argument values. See g01eec for further comments on timings.

10Example

This example reads lower tail probabilities for several beta distributions and calculates and prints the corresponding deviates until the end of data is reached.

10.1Program Text

Program Text (g01fece.c)

10.2Program Data

Program Data (g01fece.d)

10.3Program Results

Program Results (g01fece.r)