A simple approximation for the bivariate normal integral

2021 ◽  
pp. 1-14
Author(s):  
Wen-Jen Tsay ◽  
Peng-Hsuan Ke
Keyword(s):  
Simple Approximation ◽  
Bivariate Normal

A Simple Approximation for the Bivariate Normal Integral

1995 ◽  
Vol 9 (2) ◽  
pp. 317-321 ◽  
Author(s):  
Jinn-Tyan Lin
Keyword(s):  
Simple Approximation ◽  
Elementary Functions ◽  
Bivariate Normal

Approximations for the univariate normal integral are employed to develop a simple approximation in terms of elementary functions for the bivariate normal integral. The accuracy of the approximation is quite sufficient for many practical cases.

Simple approximation of sample size for the bivariate normal

1989 ◽  
Vol 8 (2) ◽  
pp. 201-207 ◽  
Author(s):  
Neil C. Schwertman ◽  
Margaret A. Owens
Keyword(s):  
Sample Size ◽  
Simple Approximation ◽  
Bivariate Normal

A note on the generalization of bivariate normal quadrant probabilities to bivariate elliptical distributions

2018 ◽  
Author(s):  
Oscar Lorenzo Olvera Astivia
Keyword(s):  
Normal Distribution ◽  
Bivariate Normal Distribution ◽  
Elliptical Distributions ◽  
Bivariate Normal ◽  
Geometric Argument

I present a geometric argument to show that the quadrant probability for the bivariate normal distribution can be generalized to the case of all elliptical distributions.

Simple Approximation to Diffraction-Limited MTF

1971 ◽  
Vol 10 (11) ◽  
pp. 2547_1
Author(s):  
R. E. Hufnagel
Keyword(s):  
Simple Approximation

M-groupoid as a tool for investigating mathematical models of computers

1977 ◽  
Vol 1 (1) ◽  
pp. 71-91
Author(s):  
Jerzy Tiuryn
Keyword(s):  
Mathematical Models ◽  
Simple Approximation ◽  
Simplified Model ◽  
Suitable Choice ◽  
Iterative Systems

An M-groupoid is a simplified model of computer. The classes of M-groupoids, address machines, stored program computers and iterative systems are presented as categories – by a suitable choice of homomorphisms. It is shown that the first three categories are equivalent, whereas the fourth is weaker (it is not equivalent to the previous ones and it can easily be embedded in the category of M-groupoids). This fact proves that M-groupoids form an essentially better and reasonably simple approximation of more complicated models of computers than iterative systems.

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