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Accurate Approximation of Standard Normal Distribution's CDF, Study Guides, Projects, Research of Physics

The accuracy evaluation of the cumulative distribution function (cdf) of the standard normal distribution using approximation formulas. The formulas are presented for the range of x from -1 to 1 and x from -3 to 3, with errors less than 10-5 and 10-7, respectively. The mathematica code is included for verification.

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Accurate Evaluation of the Cumulative

Distribution of the Standard Normal

Distribution.

Article · May 2018

CITATIONS

0

1 author:

Some of the authors of this publication are also working on these related projects:

NEURON MODELS View project

ANDRICA CONJECTURE View project

Alvaro H. Salas

National University of Colombia

190 PUBLICATIONS 938 CITATIONS

SEE PROFILE

All content following this page was uploaded by Alvaro H. Salas on 01 May 2018.

The user has requested enhancement of the downloaded file.

Accurate Evaluation of the

Cumulative Distribution of the

Standard Normal Distribution.

By : Alvaro H. Salas

Universidad Nacional de Colombia.

https : //

en.wikipedia.org / wiki / Normal _ distribution

Approximation Formulas

First Approximation Formula

In[100]:= Join  x, HoldForm ^1 2 π

- ∞

x ⅇ -^

t 2 (^2) t , Aproximant, Error  ,

Table  x, SetPrecision ^1 2 π

x ⅇ -^

t 2 (^2) t, 16 , SetPrecision

739 x 5 196 560 2 π

+^55 x^

4 8736

+^17 x^

3 468 2 π

+^95 x^

2 936

+ x 2 π

+^1

^55 x^

4 4368

+^95 x^

2 468

2 π

- ∞

x ⅇ -^

t 2 (^2) t - 739 x^

5 196 560 2 π

+ 55 x^

4 8736

+ 17 x^

3 468 2 π

+ 95 x^

2 936

+ x 2 π

+^1

55 x 4 4368

+ 95 x^

2 468

+ 1  // ReleaseHold, { x, 0, 1, 0.05 } // TableForm

Out[100]//TableForm=

x ∫-∞

x (^) ⅇ - t (^2 2) t 2 π Aproximant Error

  1. 0.5000000000000000 0.5000000000000000 0. 0.05 0.5199388058383725 0.5199388058383725 0. 0.1 0.5398278372770290 0.5398278372770291 - 2.22045 × 10 0.15 0.5596176923702425 0.5596176923702434 - 8.88178 × 10 0.2 0.5792597094391030 0.5792597094391225 - 1.95399 × 10 0.25 0.5987063256829237 0.5987063256831474 - 2.2371 × 10 - 0.3 0.6179114221889527 0.6179114221905960 - 1.64346 × 10 0.35 0.6368306511756191 0.6368306511844571 - 8.83804 × 10 0.4 0.6554217416103242 0.6554217416481328 - 3.78086 × 10 0.45 0.6736447797120800 0.6736447798478249 - 1.35745 × 10 0.5 0.6914624612740131 0.6914624616982843 - 4.24271 × 10 0.55 0.7088403132116536 0.7088403143965819 - 1.18493 × 10 0.6 0.7257468822499264 0.7257468852646274 - 3.0147 × 10 - 0.65 0.7421538891941353 0.7421538962844073 - 7.09027 × 10 0.7 0.7580363477769270 0.7580363633687422 - 1.55918 × 10 0.75 0.7733726476231318 0.7733726799728918 - 3.23498 × 10 0.8 0.7881446014166033 0.7881446652066814 - 6.37901 × 10 0.85 0.8023374568773076 0.8023375771413779 - 1.20264 × 10 0.9 0.8159398746532405 0.8159400925093920 - 2.17856 × 10 0.95 0.8289438736915182 0.8289442544580521 - 3.80767 × 10
  2. 0.8413447460685429 0.8413453904324962 - 6.44364 × 10

We see that 1 2 π

x ⅇ -^

t 2 (^2) t <

739 x 5 196 560 2 π

+ 55 x^

4 8736

+ 17 x^

3 468 2 π

+ 95 x^

2 936

+ x 2 π

+^1

55 x^

4 4368

+ 95 x^

2 468

Second Approximation Formula

on[-3, 3]

Φ( x ) =^ def^

2 π

x ⅇ -^ t^22 t

x^2 -

25 867 x 4398

x^2 -

10 219 x 2668

x^2 +

25 811 x 3468

x^2 +

25 453 x 3241

x^2 +

23 209 x 2875

 2 x^2 +

x^2 -

5927 x 1480

x^2 - 5151 x 2741

x^2 + 5151 x 2741

x^2 + 5927 x 1480

for  x  ≤ 3

with an error less that 10 -^7.