Accurate RMM-based approximations for the CDF of the normal distribution

Communications in Statistics - Theory and Methods

Volumn 34, Issue 3, 2005, Pages 507-513

  Shore, Haim ^a  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

Author keywords

Distributional approximation; Normal distribution; Response modeling methodology (RMM)

Indexed keywords

FUNCTIONS; MATHEMATICAL MODELS; OPTIMIZATION; POISSON DISTRIBUTION; POLYNOMIAL APPROXIMATION; RANDOM PROCESSES;

DISTRIBUTIONAL APPROXIMATION; EXPONENTIAL DISTRIBUTION; NORMAL DISTRIBUTIONS; RESPONSE MODELING METHODOLOGY (RDM);

STATISTICAL METHODS;

EID: 17044398621     PISSN: 03610926     EISSN: None     Source Type: Journal    
DOI: 10.1081/STA-200052102     Document Type: Article

References (8)

1. Abramowitz, M., Stegun, I. A. (1970). Handbook of Mathematical Functions. National Bureau of Standards. New York: Dover Publications.
2. Bagby, R. J. (1995). Calculating normal probabilities. Amer. Math. Monthly. 102:46-49.
3. Caq, J. H., Chen, K. (1986). Introduction to Reliability Mathematics. Beijing: Academic Publishers.
4. Johnson, N. L., Kotz, S., Balakrishnan, N. (1994). Continuous Univariate Distributions -Volume 1. 2nd ed. New York: John Wiley & Sons.
5. Shore, H. (2000). General control charts for variables. Inter. J. Prod. Res. 38(8):1875-1897.
6. Shore, H. (2002). Response modeling methodology (RMM) - exploring the implied error distribution. Commun. Statist. Theo. Meth. 31(12):2225-2249.
7. Shore, H. (2004a). Response modeling Methodology (RMM) - current statistical distributions, transformations and approximations as special cases of RMM. Commun. Statist. Theory Meth. 33(7):1491-1510.
8. Shore, H. (2004b). Response modeling methodology (RMM) - On the relationship between the RMM model and the assumption of normal (or lognormal) errors. Under review.