Intel® Integrated Performance Primitives (Intel® IPP) Developer Guide and Reference

ID 790148
Date 3/22/2024
Public
Document Table of Contents

CdfNormInv

Computes the inverse cumulative normal distribution function values of vector elements.

Syntax

IppStatus ippsCdfNormInv_32f_A11 (const Ipp32f* pSrc, Ipp32f* pDst, Ipp32s len);

IppStatus ippsCdfNormInv_32f_A21 (const Ipp32f* pSrc, Ipp32f* pDst, Ipp32s len);

IppStatus ippsCdfNormInv_32f_A24 (const Ipp32f* pSrc, Ipp32f* pDst, Ipp32s len);

IppStatus ippsCdfNormInv_64f_A26 (const Ipp64f* pSrc, Ipp64f* pDst, Ipp32s len);

IppStatus ippsCdfNormInv_64f_A50 (const Ipp64f* pSrc, Ipp64f* pDst, Ipp32s len);

IppStatus ippsCdfNormInv_64f_A53 (const Ipp64f* pSrc, Ipp64f* pDst, Ipp32s len);

Include Files

ippvm.h

Domain Dependencies

Headers: ippcore.h

Libraries: ippcore.lib

Parameters

pSrc

Pointer to the source vector.

pDst

Pointer to the destination vector.

len

Number of elements in the vectors.

Description

This function computes the inverse cumulative normal distribution function values of pSrc vector elements and stores the result in the corresponding element of pDst.

For single precision data:

function flavor ippsCdfNormInv_32f_A11 guarantees 11 correctly rounded bits of significand, or at least 3 exact decimal digits;

function flavor ippsCdfNormInv_32f_A21 guarantees 21 correctly rounded bits of significand, or 4 ulps, or about 6 exact decimal digits;

function flavor ippsCdfNormInv_32f_A24 guarantees 24 correctly rounded bits of significand, including the implied bit, with the maximum guaranteed error within 1 ulp.

For double precision data:

function flavor ippsCdfNormInv_64f_A26 guarantees 26 correctly rounded bits of significand, or 6.7E+7 ulps, or approximately 8 exact decimal digits;

function flavor ippsCdfNormInv_64f_A50 guarantees 50 correctly rounded bits of significand, or 4 ulps, or approximately 15 exact decimal digits;

function flavor ippsCdfNormInv_64f_A53 guarantees 53 correctly rounded bits of significand, including the implied bit, with the maximum guaranteed error within 1 ulp.

The computation is performed as follows:

pDst[n] = CdfNormInv(pSrc[n]), 0 ≤ n < len, where CdfNormInv(x) = CdfNorm-1(x), and CdfNorm(x) denotes the cumulative normal distribution function:



The example below shows how to use the function ippsCdfNormInv.

Return Values

ippStsNoErr

Indicates no error.

ippStsNullPtrErr

Indicates an error when pSrc or pDst pointer is NULL.

ippStsSizeErr

Indicates an error when len is less than or equal to 0.

ippStsDomain

Indicates a warning that the argument is out of the function domain, that is, at least one of pSrc elements is outside the function domain [0; 1].

ippStsSingularity

Indicates a warning that the argument is a singularity point, that is, at least one of the elements of pSrc is equal to 0 or 1.

Using ippsCdfNormInv Function

IppStatus ippsCdfNormInv_32f_A24_sample(void)
{
const Ipp32f x[4] = {+0.085, +0.543, +1.809, +0.953};
Ipp32f      	y[4];
 
   
	IppStatus st = ippsCdfNormInv_32f_A24( x, y, 4 );
 
   
	printf(" ippsCdfNormInv_32f_A24:\n");
	printf(" x = %+.3f %+.3f %+.3f %+.3f \n", x[0], x[1], x[2], x[3]);
	printf(" y = %+.3f %+.3f %+.3f %+.3f \n", y[0], y[1], y[2], y[3]);
	return st;
}
 
   
 
   
Output results:
 
   
 ippsCdfNormInv_32f_A24:
 x = +0.085 +0.543 +1.809 +0.953
 y = -1.372 +0.108 +0.874 +1.675