g01fe is the AD Library version of the primal routine g01fef. Based (in the C++ interface) on overload resolution, g01fe can be used for primal, tangent and adjoint evaluation. It supports tangents and adjoints of first order.

2 Specification

Fortran Interface

Subroutine g01fe_AD_f (

ad_handle, p, a, b, tol, x, ifail)

Integer, Intent (Inout)	::	ifail
ADTYPE, Intent (In)	::	p, a, b, tol
ADTYPE, Intent (Out)	::	x
Type (c_ptr), Intent (Inout)	::	ad_handle

Corresponding to the overloaded C++ function, the Fortran interface provides five routines with names reflecting the type used for active real arguments. The actual subroutine and type names are formed by replacing AD and ADTYPE in the above as follows:

when ADTYPE is	Real(kind=nag_wp)	then AD is p0w
when ADTYPE is	Type(nagad_a1w_w_rtype)	then AD is a1w
when ADTYPE is	Type(nagad_t1w_w_rtype)	then AD is t1w

C++ Interface

#include <dco.hpp>
#include <nagad.h>
namespace nag {
namespace ad {

void g01fe (

handle_t &ad_handle, const ADTYPE &p, const ADTYPE &a, const ADTYPE &b, const ADTYPE &tol, ADTYPE &x, Integer &ifail)

}
}

The function is overloaded on ADTYPE which represents the type of active arguments. ADTYPE may be any of the following types:
double,
dco::ga1s<double>::type,
dco::gt1s<double>::type

Note: this function can be used with AD tools other than dco/c++. For details, please contact NAG.

3 Description

g01fe is the AD Library version of the primal routine g01fef.

g01fef returns the deviate associated with the given lower tail probability of the beta distribution. For further information see Section 3 in the documentation for g01fef.

4 References

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

5 Arguments

In addition to the arguments present in the interface of the primal routine, g01fe includes some arguments specific to AD.

A brief summary of the AD specific arguments is given below. For the remainder, links are provided to the corresponding argument from the primal routine. A tooltip popup for all arguments can be found by hovering over the argument name in Section 2 and in this section.

Note that the primal routine is a function whereas g01fe_a1w_f, is a subroutine, where the function value is returned in the additional output parameter, x.

1: ad_handle – nag::ad::handle_t Input/Output: On entry: a configuration object that holds information on the differentiation strategy. Details on setting the AD strategy are described in AD handle object in the NAG AD Library Introduction.
2: p – ADTYPE Input
3: a – ADTYPE Input
4: b – ADTYPE Input
5: tol – ADTYPE Input
6: x – ADTYPE Output: On exit: the deviate associated with the given lower tail probability of the beta distribution.
7: ifail – Integer Input/Output

6 Error Indicators and Warnings

g01fe preserves all error codes from g01fef and in addition can return:

$ifail = - 89$: An unexpected AD error has been triggered by this routine. Please contact NAG.
See Error Handling in the NAG AD Library Introduction for further information.

$ifail = - 199$: The routine was called using a strategy that has not yet been implemented.
See AD Strategies in the NAG AD Library Introduction for further information.

$ifail = - 444$: A C++ exception was thrown.
The error message will show the details of the C++ exception text.

$ifail = - 899$: Dynamic memory allocation failed for AD.
See Error Handling in the NAG AD Library Introduction for further information.

7 Accuracy

Not applicable.

8 Parallelism and Performance

g01fe is not threaded in any implementation.

9 Further Comments

None.

10 Example

The following examples are variants of the example for g01fef, modified to demonstrate calling the NAG AD Library.

Description of the primal example.

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