Identification of Statistical Distribution Type by Sample Data
Abstract
The present paper provides a full description of a software implementation of a system for statistical distributions. Such a system is almost indispensable in many simulation applications where the factors incorporated adhere to a specific non-normal distribution. The realization is developed as a software library that can be integrated in different other applications. There is also the possibility for additional theoretical distribution types to be added.
References
Balakrishnan, N., & Nevzorov, V. B. (2003). A primer on statistical distributions. Hoboken, New Jersey: A John Wiley & Sons.
Crossref
Bury, K. (1999) Statistical Distributions in engineering. Cambridge University Press.
Crossref
Cameron, A. C., & Trivedi, P. K. (2013). Regression analysis of count data (Vol. 53). Cambridge university press.
Crossref
Draper, N. R., & Smith, H. (1998). Applied regression analysis (Vol. 326). John Wiley & Sons.
Crossref
Josuttis, N. M. (2007). SOA in practice: the art of distributed system design. " O'Reilly Media, Inc.".
Google Scholar
Krishnamoorthy, K. (2006) Handbook of statistical distributions with applications. Chapman & Hall.
Crossref
Mun, J. (2006). Modeling risk: applying Monte Carlo simulation, real options analysis, forecasting, and optimization techniques (Vol. 347). John Wiley & Sons.
Google Scholar
Ricci, V. (2005). Fitting distributions with R. Contributed Documentation available on CRAN, 96.
Google Scholar
Robert, C., G. Casella (1999) Monte Carlo statistical methods. Springer-Verlag.
Crossref
Sedgewick, R. (1998) Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching, (3rd Ed.), Addison-Wesley.
Google Scholar
Vallentin, M. (2011) Probability and Statistics Cookbook. Matthias Vallentin.
Retrieved from Link
Total number of hits on abstract = 333 times
Downloads for 2025
This work is licensed under a Creative Commons Attribution 4.0 International License.
