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Truncated Family of Distributions with Applications to Time and Cost to Start a Business

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Abstract

The time and cost to start a business are highly related to the degree of transparency of business information, which strongly impacts the loss due to illicit financial flows. In order to study the distributional characteristics of time and cost to start a business, we introduce right-truncated and left-truncated T-X families of distributions. These families are used to construct new generalized families of continuous distributions. Relationships between the families are investigated. Real data sets including time and cost to start a business are analyzed and the results show that the truncated families perform very well for fitting highly skewed data.

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Acknowledgments

The authors are grateful to the referees and the Associate Editor. Their comments and suggestions have greatly improved the paper. The author Felix Famoye gratefully acknowledges the financial support received from the US Department of State, Bureau of Education and Cultural Affairs Fulbright Grant# PS00230565.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, American University of Sharjah, Sharjah, UAE

    Ayman Alzaatreh

  2. Department of Mathematics, Tafila Technical University, Tafila, Jordan

    Mohammad A. Aljarrah

  3. Department of Psychology, The Australian National University, Canberra, Australia

    Michael Smithson

  4. Department of Statistics, King Abdulaziz University, Jeddah, Saudi Arabia

    Saman Hanif Shahbaz & Muhammad Qaiser Shahbaz

  5. Department of Statistics, Actuarial and Data Sciences, Central Michigan University, Mount Pleasant, MI, USA

    Felix Famoye & Carl Lee

Authors
  1. Ayman Alzaatreh
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  2. Mohammad A. Aljarrah
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  3. Michael Smithson
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  4. Saman Hanif Shahbaz
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  5. Muhammad Qaiser Shahbaz
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  6. Felix Famoye
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  7. Carl Lee
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Correspondence to Carl Lee.

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Alzaatreh, A., Aljarrah, M.A., Smithson, M. et al. Truncated Family of Distributions with Applications to Time and Cost to Start a Business. Methodol Comput Appl Probab 23, 5–27 (2021). https://doi.org/10.1007/s11009-020-09801-1

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  • DOI: https://doi.org/10.1007/s11009-020-09801-1

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