Log Complementary Error Function
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that occurs in probability, statistics, and partial differential equations describing diffusion. It is defined as:[1][2] erf ( x ) = 1 π ∫ − x x e − t 2 d t = 2 π ∫ 0 x e − t 2 d t . {\displaystyle {\begin − erfc calculator 6\operatorname − 5 (x)&={\frac − 4{\sqrt {\pi }}}\int _{-x}^ − 3e^{-t^ − 2}\,\mathrm − 1 t\\&={\frac − error function table 0{\sqrt {\pi }}}\int _ 9^ 8e^{-t^ 7}\,\mathrm 6 t.\end 5}} The complementary error function, denoted erfc, is defined as erfc inverse error function ( x ) = 1 − erf ( x ) = 2 π ∫ x ∞ e − t 2 d t = e − x 2 erfcx ( x ) , {\displaystyle {\begin 2\operatorname 1 error function matlab (x)&=1-\operatorname 0 (x)\\&={\frac Φ 9{\sqrt {\pi }}}\int _ Φ 8^{\infty }e^{-t^ Φ 7}\,\mathrm Φ 6 t\\&=e^{-x^ Φ 5}\operatorname Φ 4 (x),\end Φ 3}} which also defines erfcx, the scaled complementary error function[3] (which can be used instead of erfc to avoid arithmetic underflow[3][4]). Another form of erfc ( x ) {\displaystyle \operatorname 2 (x)} for non-negative x {\displaystyle x} is known as Craig's formula:[5] erfc ( x | x ≥ 0 ) = 2 π ∫ 0 π /
Erf(inf)
2 exp ( − x 2 sin 2 θ ) d θ . {\displaystyle \operatorname 0 (x|x\geq 0)={\frac Φ 9{\pi }}\int _ Φ 8^{\pi /2}\exp \left(-{\frac Φ 7}{\sin ^ Φ 6\theta }}\right)d\theta \,.} The imaginary error function, denoted erfi, is defined as erfi ( x ) = − i erf ( i x ) = 2 π ∫ 0 x e t 2 d t = 2 π e x 2 D ( x ) , {\displaystyle {\begin Φ 0\operatorname − 9 (x)&=-i\operatorname − 8 (ix)\\&={\frac − 7{\sqrt {\pi }}}\int _ − 6^ − 5e^ − 4}\,\mathrm − 3 t\\&={\frac − 2{\sqrt {\pi }}}e^ − 1}D(x),\end − 0}} where D(x) is the Dawson function (which can be used instead of erfi to avoid arithmetic overflow[3]). Despite the name "imaginary error function", erfi ( x ) {\displaystyle \operatorname 8 (x)} is real when x is real. When the error function is evaluated for arbitrary complex arguments z, the resulting complex error function is usually discussed in scaled form as the Faddeeva function: w ( z ) = e − z 2 erfc ( − i z ) = erfcx ( − i z ) . {\displaystyle w(z)=e^{-z^ 6}\operatorname 5 (-iz)=\operatorname 4 (-iz).} Contents 1 The name "error function" 2 Properties 2.1 Taylor series 2.2 Derivative and integral 2.3 Bürmann series 2.4 Inverse functions 2.5 Asymptotic expansion 2.6 Continued fraction expansion 2.7 Integral of error function with Gaussian
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Updates Documentation Home MATLAB Examples Functions Release Notes PDF Documentation Mathematics error function excel Elementary Math Special Functions MATLAB Functions erfc On this page Syntax Description Examples Find Complementary Error q function Function Find Bit Error Rate of Binary Phase-Shift Keying Avoid Roundoff Errors Using Complementary Error Function Input Arguments x More About Complementary Error Function Tall Array https://en.wikipedia.org/wiki/Error_function Support Tips See Also This is machine translation Translated by Mouse over text to see original. Click the button below to return to the English verison of the page. Back to English × Translate This Page Select Language Bulgarian Catalan Chinese Simplified Chinese Traditional Czech Danish Dutch English Estonian Finnish French German https://www.mathworks.com/help/matlab/ref/erfc.html Greek Haitian Creole Hindi Hmong Daw Hungarian Indonesian Italian Japanese Korean Latvian Lithuanian Malay Maltese Norwegian Polish Portuguese Romanian Russian Slovak Slovenian Spanish Swedish Thai Turkish Ukrainian Vietnamese Welsh MathWorks Machine Translation The automated translation of this page is provided by a general purpose third party translator tool. MathWorks does not warrant, and disclaims all liability for, the accuracy, suitability, or fitness for purpose of the translation. Translate erfcComplementary error functioncollapse all in page Syntaxerfc(x) exampleDescriptionexampleerfc(x
) returns the Complementary Error Function evaluated for each element of x. Use the erfc function to replace 1 - erf(x) for greater accuracy when erf(x) is close to 1.Examplescollapse allFind Complementary Error FunctionOpen ScriptFind the complementary error function of a value.erfc(0.35) ans = 0.6206 Find the complementary error function of the elements of a vector.V = [-0.5 0 1 0.72]; erfc(V) ans = 1.5205 1.0000 0.1573 0.3086 Find the complementary error function of the elements of a matri
article Abstract 1.Introduction 2.The closed-form approximation of error functions 3.Examples of applications http://onlinelibrary.wiley.com/doi/10.1002/asl.154/full in atmospheric science 4.Conclusion References Related Content Citing Literature Atmospheric Science Letters Explore this journal > Explore this journal > Previous article in issue: On the critical Richardson number in stably stratified turbulence Previous article in issue: On the critical Richardson number in stably stratified turbulence Next article in issue: Estimating error function the top-of-atmosphere longwave radiative forcing due to Saharan dust from satellite observations over a west African surface site Next article in issue: Estimating the top-of-atmosphere longwave radiative forcing due to Saharan dust from satellite observations over a west African surface site View issue TOC Volume 8, Issue 3 July/September 2007 Pages 70–73 log complementary error Open AccessResearch ArticleClosed-form approximations to the error and complementary error functions and their applications in atmospheric scienceAuthorsC. Ren,Corresponding authorE-mail address: c.ren@lancaster.ac.ukDepartment of Environmental Sciences, Lancaster University, Lancaster LA1 4YQ, UKDepartment of Environmental Sciences, Lancaster University, Lancaster LA1 4YQ, UK.Search for more papers by this authorA. R. MacKenzieDepartment of Environmental Sciences, Lancaster University, Lancaster LA1 4YQ, UKSearch for more papers by this authorFirst published: July 2007Full publication historyDOI: 10.1002/asl.154View/save citationCited by: 5 articles Citation tools Set citation alert Check for new citations Citing literature AbstractThe error function, as well as related functions, occurs in theoretical aspects of many parts of atmospheric science. This note presents a closed-form approximation for the error, complementary error, and scaled complementary error functions, with maximum relative errors within 0.8%. Unlike other approximate solutions, this single equation gives answers within the stated accuracy for real variable x ∈ [0∞). The approximation is very useful in solving atmospheric science