s22bb: FL CL CPP AD PY MB

NAG CL Interface
s22bbc (hyperg_confl_real_scaled)

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NAG Library Manual, Mark 30.1

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s22bb: FL CL CPP AD PY MB

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

▸▿ 10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

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1 Purpose

s22bbc returns a value for the confluent hypergeometric function

{}_{1}F_{1} (a; b; x)

, with real parameters

a

and

b

and real argument

x

. The solution is returned in the scaled form

{}_{1}F_{1} (a; b; x) = m_{f} \times 2^{m_{s}}

. This function is sometimes also known as Kummer's function

M (a, b, x)

2 Specification

#include <nag.h>

void	s22bbc (double ani, double adr, double bni, double bdr, double x, double frm, Integer scm, NagError *fail)

The function may be called by the names: s22bbc, nag_specfun_hyperg_confl_real_scaled or nag_specfun_1f1_real_scaled.

3 Description

s22bbc returns a value for the confluent hypergeometric function

{}_{1}F_{1} (a; b; x)

, with real parameters

a

and

b

and real argument

x

, in the scaled form

{}_{1}F_{1} (a; b; x) = m_{f} \times 2^{m_{s}}

, where

m_{f}

is the real scaled component and

m_{s}

is the integer power of two scaling. This function is unbounded or not uniquely defined for

b

equal to zero or a negative integer.

The confluent hypergeometric function is defined by the confluent series,

{}_{1}F_{1} (a; b; x) = M (a, b, x) = \sum_{s = 0}^{\infty} \frac{{(a)}_{s} x^{s}}{{(b)}_{s} s!} = 1 + \frac{a}{b} x + \frac{a (a + 1)}{b (b + 1) 2!} x^{2} + \dots

where

{(a)}_{s} = 1 (a) (a + 1) (a + 2) \dots (a + s - 1)

is the rising factorial of

a

M (a, b, x)

is a solution to the second order ODE (Kummer's Equation):

x \frac{d^{2} M}{d x^{2}} + (b - x) \frac{d M}{d x} - a M = 0 .

(1)

Given the parameters and argument

(a, b, x)

, this function determines a set of safe values

{(α_{i}, β_{i}, ζ_{i}) ∣ i \leq 2}

and selects an appropriate algorithm to accurately evaluate the functions

M_{i} (α_{i}, β_{i}, ζ_{i})

. The result is then used to construct the solution to the original problem

M (a, b, x)

using, where necessary, recurrence relations and/or continuation.

For improved precision in the final result, this function accepts

a

and

b

split into an integral and a decimal fractional component. Specifically

a = a_{i} + a_{r}

, where

| a_{r} | \leq 0.5

and

a_{i} = a - a_{r}

is integral.

b

is similarly deconstructed.

Additionally, an artificial bound,

arbnd

is placed on the magnitudes of

a_{i}

b_{i}

and

x

to minimize the occurrence of overflow in internal calculations.

arbnd = 0.0001 \times I_{\max}

, where

I_{\max} = X02BBC

. It should, however, not be assumed that this function will produce an accurate result for all values of

a_{i}

b_{i}

and

x

satisfying this criterion.

Please consult the NIST Digital Library of Mathematical Functions for a detailed discussion of the confluent hypergeometric function including special cases, transformations, relations and asymptotic approximations.

4 References

NIST Digital Library of Mathematical Functions

Pearson J (2009) Computation of hypergeometric functions MSc Dissertation, Mathematical Institute, University of Oxford

5 Arguments

1: $ani$ – double Input

On entry:

a_{i}

, the nearest integer to

a

, satisfying

a_{i} = a - a_{r}

Constraints:

$ani = ⌊ ani ⌋$ ;
$| ani | \leq arbnd$ .

2: $adr$ – double Input

On entry:

a_{r}

, the signed decimal remainder satisfying

a_{r} = a - a_{i}

and

| a_{r} | \leq 0.5

Constraint:

| adr | \leq 0.5

Note: if

| adr | < 100.0 ε

a_{r} = 0.0

will be used, where

ε

is the machine precision as returned by X02AJC.

3: $bni$ – double Input

On entry:

b_{i}

, the nearest integer to

b

, satisfying

b_{i} = b - b_{r}

Constraints:

$bni = ⌊ bni ⌋$ ;
$| bni | \leq arbnd$ ;
if $bdr = 0.0$ , $bni > 0$ .

4: $bdr$ – double Input

On entry:

b_{r}

, the signed decimal remainder satisfying

b_{r} = b - b_{i}

and

| b_{r} | \leq 0.5

Constraint:

| bdr | \leq 0.5

Note: if

| bdr - adr | < 100.0 ε

a_{r} = b_{r}

will be used, where

ε

is the machine precision as returned by X02AJC.

5: $x$ – double Input

On entry: the argument

x

of the function.

Constraint:

| x | \leq arbnd

6: $frm$ – double * Output

On exit:

m_{f}

, the scaled real component of the solution satisfying

m_{f} = M (a, b, x) \times 2^{- m_{s}}

Note: if overflow occurs upon completion, as indicated by

fail . code =

NW_OVERFLOW_WARN, the value of

m_{f}

returned may still be correct. If overflow occurs in a subcalculation, as indicated by

fail . code =

NE_OVERFLOW, this should not be assumed.

7: $scm$ – Integer * Output

On exit:

m_{s}

, the scaling power of two, satisfying

m_{s} = \log_{2} (\frac{M (a, b, x)}{m_{f}})

Note: if overflow occurs upon completion, as indicated by

fail . code =

NW_OVERFLOW_WARN, then

m_{s} \geq I_{\max}

, where

I_{\max}

is the largest representable integer (see X02BBC). If overflow occurs during a subcalculation, as indicated by

fail . code =

NE_OVERFLOW,

m_{s}

may or may not be greater than

I_{\max}

. In either case,

scm = nag_max_integer

will have been returned.

8: $fail$ – NagError * Input/Output

The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

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_BAD_PARAM: On entry, argument $⟨ value ⟩$ had an illegal value.
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_OVERFLOW: Overflow occurred in a subcalculation of $M (a, b, x)$ .
The answer may be completely incorrect.
NE_REAL: On entry, $adr = ⟨ value ⟩$ .
Constraint: $| adr | \leq 0.5$ .

On entry, $bdr = ⟨ value ⟩$ .
Constraint: $| bdr | \leq 0.5$ .
NE_REAL_2: On entry, $b = bni + bdr = ⟨ value ⟩$ .
$M (a, b, x)$ is undefined when $b$ is zero or a negative integer.
NE_REAL_ARG_NON_INTEGRAL: ani is non-integral.
On entry, $ani = ⟨ value ⟩$ .
Constraint: $ani = ⌊ ani ⌋$ .

bni is non-integral.
On entry, $bni = ⟨ value ⟩$ .
Constraint: $bni = ⌊ bni ⌋$ .
NE_REAL_RANGE_CONS: On entry, $ani = ⟨ value ⟩$ .
Constraint: $| ani | \leq arbnd = ⟨ value ⟩$ .

On entry, $bni = ⟨ value ⟩$ .
Constraint: $| bni | \leq arbnd = ⟨ value ⟩$ .

On entry, $x = ⟨ value ⟩$ .
Constraint: $| x | \leq arbnd = ⟨ value ⟩$ .
NE_TOTAL_PRECISION_LOSS: All approximations have completed, and the final residual estimate indicates no accuracy can be guaranteed.
Relative residual $= ⟨ value ⟩$ .
NW_OVERFLOW_WARN: On completion, overflow occurred in the evaluation of $M (a, b, x)$ .
NW_SOME_PRECISION_LOSS: All approximations have completed, and the final residual estimate indicates some precision may have been lost.
Relative residual $= ⟨ value ⟩$ .
NW_UNDERFLOW_WARN: Underflow occurred during the evaluation of $M (a, b, x)$ .
The returned value may be inaccurate.

7 Accuracy

In general, if

fail . code =

NE_NOERROR, the value of

M

may be assumed accurate, with the possible loss of one or two decimal places. Assuming the result does not under or overflow, an error estimate

res

is made internally using equation (1). If the magnitude of

res

is sufficiently large a different fail.code will be returned. Specifically,

$fail . code =$ NE_NOERROR	$res \leq 1000 ε$
$fail . code =$ NW_SOME_PRECISION_LOSS	$1000 ε < res \leq 0.1$
$fail . code =$ NE_TOTAL_PRECISION_LOSS	$res > 0.1$

A further estimate of the residual can be constructed using equation (1), and the differential identity,

\begin{matrix} \frac{d M (a, b, x)}{d x} & = & \frac{a}{b} M (a + 1, b + 1, x), \\ \frac{d^{2} M (a, b, x)}{d x^{2}} & = & \frac{a (a + 1)}{b (b + 1)} M (a + 2, b + 2, x) . \end{matrix}

This estimate is however, dependent upon the error involved in approximating

M (a + 1, b + 1, x)

and

M (a + 2, b + 2, x)

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

s22bbc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

s22bbc makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.

Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

The values of

m_{f}

and

m_{s}

are implementation dependent. In most cases, if

{}_{1}F_{1} (a; b; x) = 0

m_{f} = 0

and

m_{s} = 0

will be returned, and if

{}_{1}F_{1} (a; b; x) = 0

is finite, the fractional component will be bound by

0.5 \leq | m_{f} | < 1

, with

m_{s}

chosen accordingly.

The values returned in frm (

m_{f}

) and scm (

m_{s}

) may be used to explicitly evaluate

M (a, b, x)

, and may also be used to evaluate products and ratios of multiple values of

M

as follows,

\begin{matrix} M (a, b, x) & = & m_{f} \times 2^{m_{s}} \\ M (a_{1}, b_{1}, x_{1}) \times M (a_{2}, b_{2}, x_{2}) & = & (m_{f 1} \times m_{f 2}) \times 2^{(m_{s 1} + m_{s 2})} \\ \frac{M (a_{1}, b_{1}, x_{1})}{M (a_{2}, b_{2}, x_{2})} & = & \frac{m_{f 1}}{m_{f 2}} \times 2^{(m_{s 1} - m_{s 2})} \\ \ln | M (a, b, x) | & = & \ln | m_{f} | + m_{s} \times \ln (2) \end{matrix} .

10 Example

This example evaluates the confluent hypergeometric function at two points in scaled form using s22bbc, and subsequently calculates their product and ratio without having to explicitly construct