Journal ArticleDOI
Least-squares estimation of distribution functions in johnson's translation system
Reads0
Chats0
TLDR
Compared to traditional methods of distribution fitting based on moment matching, percentile matching, L 1 estimation, and L ⌆ estimation, the least-squares technique is seen to yield fits of similar accuracy and to converge more rapidly and reliably to a set of acceptable parametre estimates.Abstract:
To summarize a set of data by a distribution function in Johnson's translation system, we use a least-squares approach to parameter estimation wherein we seek to minimize the distance between the vector of "uniformized" oeder statistics and the corresponding vector of expected values. We use the software package FITTRI to apply this technique to three problems arising respectively in medicine, applied statistics, and civil engineering. Compared to traditional methods of distribution fitting based on moment matching, percentile matchingL 1 estimation, and L ⌆ estimation, the least-squares technique is seen to yield fits of similar accuracy and to converge more rapidly and reliably to a set of acceptable parametre estimates.read more
Citations
More filters
Journal ArticleDOI
Generalized exponential distribution: different method of estimations
Rameshwar D. Gupta,Debasis Kundu +1 more
TL;DR: In this article, the authors considered the maximum likelihood estimation of the different parameters of a generalized exponential distribution and discussed some of the testing of hypothesis problems, and compared their performances through numerical simulations.
Journal ArticleDOI
Generalized Rayleigh distribution
Debasis Kundu,Mohammad Z. Raqab +1 more
TL;DR: Different estimation procedures have been used to estimate the unknown parameter(s) and their performances are compared using Monte Carlo simulations, and it is observed that this particular skewed distribution can be used quite effectively in analyzing lifetime data.
Journal ArticleDOI
Generalized exponential distribution: Bayesian estimations
Debasis Kundu,Rameshwar D. Gupta +1 more
TL;DR: The approximate Bayes estimators obtained under the assumptions of non-informative priors, are compared with the maximum likelihood estimators using Monte Carlo simulations.
Journal ArticleDOI
Sensitivity of computer simulation experiments to errors in input data
TL;DR: In this paper, the authors compare two methods of assessing variability in simulation output: the classical statistical differential analysis (SDA) and the parametric form of bootstrap sampling (PBS).
Journal ArticleDOI
Fitting beta distributions based on sample data
TL;DR: A computer program founded upon several fast, robust numerical procedures based on a number of statistical-estimation methods is presented, and it is found that the least-square minimi- zation method provided better quality fits in general, compared to the other two approaches.
References
More filters
Book
Linear regression analysis
TL;DR: In this paper, the authors take into serious consideration the further development of regression computer programs that are efficient, accurate, and considered an important part of statistical research, and provide up-to-date accounts of computational methods and algorithms currently in use without getting entrenched in minor computing details.