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Confidence Intervals for the Mean of Delta-Lognormal Distribution

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Structural Changes and their Econometric Modeling (TES 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 808))

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Abstract

Focusing on delta-lognormal distribution, confidence intervals for the mean are proposed in this research. This will be achieved using a method of variance estimates recovery (MOVER) and generalized confidence interval (GCI) based on weighted beta distribution by Hannig, and MOVER based on variance stabilized transformation (VST). These are then compared with GCI based on VST. The coverage probabilities and average lengths are performances from the presented methods, computed via Monte Carlo simulation. Our results showed that MOVER based on VST is the recommended method under situations of slight probability of being zero and large coefficient of variation in small to moderate sample sizes. Ultimately, rainfall data in Chiang Mai was used to illustrate all of the presented methods.

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Authors and Affiliations

  1. Faculty of Applied Science, Department of Applied Statistics, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

    Patcharee Maneerat, Sa-Aat Niwitpong & Suparat Niwitpong

Authors
  1. Patcharee Maneerat
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  2. Sa-Aat Niwitpong
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  3. Suparat Niwitpong
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Corresponding author

Correspondence to Patcharee Maneerat .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  2. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

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Maneerat, P., Niwitpong, SA., Niwitpong, S. (2019). Confidence Intervals for the Mean of Delta-Lognormal Distribution. In: Kreinovich, V., Sriboonchitta, S. (eds) Structural Changes and their Econometric Modeling. TES 2019. Studies in Computational Intelligence, vol 808. Springer, Cham. https://doi.org/10.1007/978-3-030-04263-9_20

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