Tuber Crop Growth Model, Performance Rate, and Some Characterization Theorems

  • Ratan DasguptaEmail author
Conference paper


Geometric and exponential distributions may be used for modeling number of tubers and yield of crop. Geometric distribution is discrete version of appropriate exponential distribution and both the distributions have memoryless property. We model a real dataset on number of potato tubers arising from a growth experiment conducted in Giridih farmland and study the properties of these and related distributions in terms of performance rate (Dasgupta 2018) and hazard rate. Some characterization theorems are proved for discrete and continuous random variables.


Exponential growth model Tuber crop Performance rate Hazard rate 

MS Subject Classification:

Primary 62E10 Secondary 62P10 


  1. Block, H., Savits, T., & Singh, H. (1998). The reversed hazard rate function. Probability in the Engineering and Informational Sciences, 12, 69–90.MathSciNetCrossRefGoogle Scholar
  2. Crawford, G. B. (1966). Characterization of geometric and exponential distributions. The Annals of Mathematical Statistics, 37, 1790–1795.MathSciNetCrossRefGoogle Scholar
  3. Dasgupta, R. (1993). Cauchy equation on discrete domain and some characterization theorems. Theory of Probability and Its Applications, 38(3), 520–524.MathSciNetCrossRefGoogle Scholar
  4. Dasgupta, R. (2011). Discrete distributions with application to lifestyle data. In: International conference on productivity, quality, reliability, optimization and modeling proceedings (Vol. 1, pp. 502–520). New Delhi: Allied Publishers.Google Scholar
  5. Dasgupta, R. (2013). Tuber crop growth and pareto model. In advances in growth curve models: topics from the Indian statistical institute. Springer proceedings in mathematics & statistics (Vol. 46, pp. 185–198) Chapter 10.Google Scholar
  6. Dasgupta R. (2015). Growth model of some vernacular word usage during political transition. In Growth curve and structural equation modeling: Topics from the Indian Statistical Institute (pp. 171–193) Chapter 10. Springer.CrossRefGoogle Scholar
  7. Dasgupta, R. (2017). Model selection and validation in agricultural context: Extended uniform distribution and some characterization theorems. In Growth curve models and applications (pp. 183–198) Chapter 9. Springer.CrossRefGoogle Scholar
  8. Dasgupta, R. (2018). Characterization of extended uniform distribution and its applications, advances in growth curve and structural equation modeling: Proceedings 2017 Springer (USA), Appearing in this volume as chapter 3.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Theoretical Statistics and Mathematics UnitIndian Statistical InstituteKolkataIndia

Personalised recommendations