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Confidence Intervals for the Signal to Noise Ratio of Two-Parameter Exponential Distribution

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Econometrics for Financial Applications (ECONVN 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 760))

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Abstract

This paper investigates the performance of confidence intervals for signal to noise ratio (SNR) of two-parameter exponential distribution. The confidence intervals were constructed using generalized confidence interval (GCI) approach, large sample (LS) approach, and method of variance estimates recovery (MOVER) approach. The coverage probability and average length of the confidence intervals were evaluated by a Monte Carlo simulation. The results found that the confidence intervals based on the GCI approach provide the best coverage probabilities for all cases. The approaches are illustrated using an example.

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Author information

Authors and Affiliations

  1. University of the Thai Chamber of Commerce, Bangkok, 10400, Thailand

    Luckhana Saothayanun

  2. Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok, 10800, Thailand

    Warisa Thangjai

Authors
  1. Luckhana Saothayanun
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  2. Warisa Thangjai
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Corresponding author

Correspondence to Warisa Thangjai .

Editor information

Editors and Affiliations

  1. Banking University HCMC, Ho Chi Minh City, Vietnam

    Ly H. Anh

  2. Banking University HCMC, Ho Chi Minh City, Vietnam

    Le Si Dong

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

    Vladik Kreinovich

  4. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Ngoc Thach

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Saothayanun, L., Thangjai, W. (2018). Confidence Intervals for the Signal to Noise Ratio of Two-Parameter Exponential Distribution. In: Anh, L., Dong, L., Kreinovich, V., Thach, N. (eds) Econometrics for Financial Applications. ECONVN 2018. Studies in Computational Intelligence, vol 760. Springer, Cham. https://doi.org/10.1007/978-3-319-73150-6_20

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  • DOI: https://doi.org/10.1007/978-3-319-73150-6_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73149-0

  • Online ISBN: 978-3-319-73150-6

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