Abstract
This paper presents a construction of confidence intervals for the common variance of normal distributions based on generalized confidence intervals, and then compares the results with a large sample approach. A Monte Carlo simulation was used to evaluate the coverage probability and average length of confidence intervals. Simulation studies showed that the generalized confidence interval approach provided much better confidence interval estimates than the large sample approach. Two real data examples are exhibited to illustrate our approaches.
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Acknowledgments
The first author gratefully acknowledges the financial support from Faculty of Applied Science and Graduate College of King Mongkuts University of Technology North Bangkok of Thailand.
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Smithpreecha, N., Niwitpong, SA., Niwitpong, S. (2016). Confidence Intervals for Common Variance of Normal Distributions. In: Huynh, VN., Inuiguchi, M., Le, B., Le, B., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2016. Lecture Notes in Computer Science(), vol 9978. Springer, Cham. https://doi.org/10.1007/978-3-319-49046-5_48
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DOI: https://doi.org/10.1007/978-3-319-49046-5_48
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