71 Papers
1.8K Citations
Lee J. Bain is an academic researcher from Missouri University of Science and Technology. The author has contributed to research in topics: Weibull distribution & Gamma distribution. The author has an hindex of 29, co-authored 71 publications.
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Papers
•Book
Introduction to Probability and Mathematical Statistics
Lee J. Bain,Max Engelhardt +1 more
- 01 Jan 1987
TL;DR: Probability Random Variables and their Distributions Special Probability Distributions Joint Distributions Properties of random Variables Functions of random variables Limiting Distributions Statistics and Sampling Distributions Point Estimation Sufficiency and Completeness Interval Estimation Test of Hypotheses Contingency Tables and Goodness-of-Fit Nonparametric Methods Regression and Linear Models Reliability and Survival Distributions Answers to Selected Exercises as mentioned in this paper.
653
Introduction to Probability and Mathematical Statistics.
Lee J. Bain,Max Engelhardt +1 more
TL;DR: Probability Random Variables and their Distributions Special Probability Distributions Joint Distributions Properties of random Variables Functions of random variables Limiting Distributions Statistics and Sampling Distributions Point Estimation Sufficiency and Completeness Interval Estimation Test of Hypotheses Contingency Tables and Goodness-of-Fit Nonparametric Methods Regression and Linear Models Reliability and Survival Distributions Answers to Selected Exercises as mentioned in this paper.
420
Inferences on the Parameters of the Birnbaum-Saunders Fatigue Life Distribution Based on Maximum Likelihood Estimation
TL;DR: In this paper, the authors provide tests of hypotheses and confidence intervals for the scale and shape parameters of the Birnbaum-Saunders fatigue life model, each with an unknown nuisance parameter.
143
Maximum Likelihood Estimation, Exact Confidence Intervals for Reliability, and Tolerance Limits in the Weibull Distribution
TL;DR: In this paper, the authors present the results of a study of the maximum likelihood estimator, (t), of the reliability, R(t), when the two-parameter Weibull distribution is assumed.
116
Estimation and Hypothesis Testing for the Parameters of a Bivariate Exponential Distribution
TL;DR: In this paper, the authors investigated statistical properties of the bivariate exponential distribution and compared them with the estimates given by Arnold, showing that the method of moments type estimates are easy to compute and highly efficient, whereas the maximum likelihood estimates are computationally inconvenient.
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