Abstract
Power series expansions are old friends of all workers in the mathematical sciences [4, 5, 10]. This chapter emphasizes special techniques for handling and generating the power series encountered in computational statistics. Most expansions can be phrased in terms of recurrence relations. Logarithmic differentiation is one powerful device for developing recurrences. Our applications of logarithmic differentiation to problems such as the conversion between moments and cumulants illustrate some of the interesting possibilities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bickel PJ, Doksum KA (1977) Mathematical Statistics: Basic Ideas and Selected Topics. Holden-Day, Oakland, CA
Curnow RN, Dunnett CW (1962) The numerical evaluation of certain multivariate normal integrals. Ann Math Stat 33:571-579
Feller W (1968) An Introduction to Probability Theory and Its Applications, Volume 1, 3rd ed. Wiley, New York
Graham RL, Knuth DE, Patashnik O (1988) Concrete Mathematics: A Foundation for Computer Science. Addison-Wesley, Reading, MA
Henrici P (1974) Applied and Computational Complex Analysis, Volume 1. Wiley, New York
Lehmann EL (1991) Theory of Point Estimation. Wadsworth, Belmont, CA
Majumder KL, Bhattacharjee GP (1973) Algorithm AS 63. The incomplete beta integral. Appl Stat 22:409-411
Pourhamadi M (1984) Taylor expansion of exp(∑k =0 akzks) and some applications. Amer Math Monthly 91:303-307
Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1992) Numerical Recipes in Fortran: The Art of Scientific Computing, 2nd ed. Cambridge University Press, Cambridge
Wilf HS (1990) generatingfunctionology. Academic Press, New York
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer New York
About this chapter
Cite this chapter
Lange, K. (2010). Power Series Expansions. In: Numerical Analysis for Statisticians. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5945-4_2
Download citation
DOI: https://doi.org/10.1007/978-1-4419-5945-4_2
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-5944-7
Online ISBN: 978-1-4419-5945-4
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)