Abstract
Textbooks and courses on numerical algorithms contain numerous examples which lead students to believe that the algorithm of choice for computing the zeros of a function f1994 is Newton's algorithm. In many of these courses little or no time is spent in providing students with "real world" experiences where Newton's method fails. The work presented in this paper describes a slow convergence problem encountered while trying to use Newton to estimate values for the 2 distributions. The problem occurred while the authors were trying to implement a well-known machine learning algorithm from the field of artificial intelligence. The function being evaluated and the convergence problem with Newton's method is described. Numerical results are given that indicate that a hybrid algorithm consisting of Newton and the nonderivative bisection algorithm not only provides good results but quickly and consistently converges. © 1994, ACM. All rights reserved.
Recommended Citation
J. F. Dooley et al., "Computing Χ² Values," ACM SIGCSE Bulletin, vol. 26, no. 1, pp. 218 - 222, Association for Computing Machinery, Dec 1994.
The definitive version is available at https://doi.org/10.1145/191033.191124
Department(s)
Mathematics and Statistics
Second Department
Computer Science
International Standard Serial Number (ISSN)
0097-8418
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Association for Computing Machinery, All rights reserved.
Publication Date
03 Dec 1994
