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21: 7.7 Integral Representations
§7.7(i) Error Functions and Dawson’s Integral
7.7.1 erfc z = 2 π e z 2 0 e z 2 t 2 t 2 + 1 d t , | ph z | 1 4 π ,
7.7.5 0 1 e a t 2 t 2 + 1 d t = π 4 e a ( 1 ( erf a ) 2 ) , a > 0 .
7.7.7 x e a 2 t 2 ( b 2 / t 2 ) d t = π 4 a ( e 2 a b erfc ( a x + ( b / x ) ) + e 2 a b erfc ( a x ( b / x ) ) ) , x > 0 , | ph a | < 1 4 π .
7.7.9 0 x erf t d t = x erf x + 1 π ( e x 2 1 ) .
22: 7.20 Mathematical Applications
§7.20(i) Asymptotics
For applications of the complementary error function in uniform asymptotic approximations of integrals—saddle point coalescing with a pole or saddle point coalescing with an endpoint—see Wong (1989, Chapter 7), Olver (1997b, Chapter 9), and van der Waerden (1951). The complementary error function also plays a ubiquitous role in constructing exponentially-improved asymptotic expansions and providing a smooth interpretation of the Stokes phenomenon; see §§2.11(iii) and 2.11(iv). …
§7.20(iii) Statistics
For applications in statistics and probability theory, also for the role of the normal distribution functions (the error functions and probability integrals) in the asymptotics of arbitrary probability density functions, see Johnson et al. (1994, Chapter 13) and Patel and Read (1982, Chapters 2 and 3).
23: 7 Error Functions, Dawson’s and Fresnel Integrals
Chapter 7 Error Functions, Dawson’s and Fresnel Integrals
24: 12.7 Relations to Other Functions
§12.7(ii) Error Functions, Dawson’s Integral, and Probability Function
12.7.6 U ( n + 1 2 , z ) = D n 1 ( z ) = π 2 ( 1 ) n n ! e 1 4 z 2 d n ( e 1 2 z 2 erfc ( z / 2 ) ) d z n , n = 0 , 1 , 2 , ,
12.7.7 U ( n + 1 2 , z ) = e 1 4 z 2 𝐻ℎ n ( z ) = π  2 1 2 ( n 1 ) e 1 4 z 2 i n erfc ( z / 2 ) , n = 1 , 0 , 1 , .
25: 8.4 Special Values
For erf ( z ) , erfc ( z ) , and F ( z ) , see §§7.2(i), 7.2(ii). …
8.4.1 γ ( 1 2 , z 2 ) = 2 0 z e t 2 d t = π erf ( z ) ,
8.4.6 Γ ( 1 2 , z 2 ) = 2 z e t 2 d t = π erfc ( z ) .
26: 7.8 Inequalities
§7.8 Inequalities
7.8.8 erf x < 1 e 4 x 2 / π , x > 0 .
27: 12.13 Sums
12.13.6 n ! U ( n + 1 2 , z ) = i n e 1 2 z 2 erfc ( z / 2 ) U ( n 1 2 , i z ) + m = 1 1 2 n + 1 2 U ( 2 m n 1 2 , z ) , n = 0 , 1 , 2 , .
For erfc see §7.2(i). …
28: 8.12 Uniform Asymptotic Expansions for Large Parameter
8.12.3 P ( a , z ) = 1 2 erfc ( η a / 2 ) S ( a , η ) ,
8.12.4 Q ( a , z ) = 1 2 erfc ( η a / 2 ) + S ( a , η ) ,
d ( ± χ ) = 1 2 π e χ 2 / 2 erfc ( ± χ / 2 ) ,
For other uniform asymptotic approximations of the incomplete gamma functions in terms of the function erfc see Paris (2002b) and Dunster (1996a). … These expansions involve the inverse error function inverfc ( x ) 7.17), and are uniform with respect to q [ 0 , 1 ] . …
29: Software Index
30: 13.18 Relations to Other Functions
§13.18(ii) Incomplete Gamma Functions
Special cases are the error functions
13.18.7 W 1 4 , ± 1 4 ( z 2 ) = e 1 2 z 2 π z erfc ( z ) .