Naive Regression Growth Models for Prediction of Peppermint Yield Production

Authors

  • S. K. Yadav Department of Statistics, Babasaheb Bhimrao Ambedkar University, Lucknow, India
  • Dinesh K. Sharma University of Maryland Eastern Shore, Maryland, USA
  • Ayodele Julius Alade University of Maryland Eastern Shore, Maryland, USA
  • Alok Kumar Shukla Department of Statistics, D.A.V. College, CSJM University, Kanpur, India

DOI:

https://doi.org/10.13052/jrss0974-8024.1424

Keywords:

Main variable, regressor, regression model, residual, coefficient of determination

Abstract

In this study, three novel regression models are introduced for estimating and forecasting peppermint yield production. Several indices of the goodness of fit are used to assess the quality of the suggested models. The proposed models for yield production are compared to current regression models that are well-known. Primary data from the Banki block of the Barabanki District of Uttar Pradesh State in India was used to validate the efficiency conditions for the suggested models to outperform the competition models. The empirical results suggest that the proposed models for estimating and predicting peppermint yield production are more efficient than competing estimators.

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Author Biographies

S. K. Yadav, Department of Statistics, Babasaheb Bhimrao Ambedkar University, Lucknow, India

S. K. Yadav is an Associate Professor in the Department of Statistics at the Babasaheb Bhimrao Ambedkar University, Lucknow, UP, India. He earned his MSc and PhD in Statistics from the Lucknow University and has qualified to the National Eligibility Test. He has published 65 papers in national and international journals of repute and two books from an international publisher. He is a referee for 20 reputed international journals. He has presented papers in more than 20 national and international conferences and also delivered invited talks in several conferences.

Dinesh K. Sharma, University of Maryland Eastern Shore, Maryland, USA

Dinesh K. Sharma is a Professor of Quantitative Methods and Computer Applications in the Department of Business, Management and Accounting at the University of Maryland Eastern Shore. He earned his MS in Mathematics, MS in Computer Science, PhD in Operations Research, and a second PhD in Management. Professor Sharma has over twenty-eight years of teaching experience, served in numerous committees to supervise PhD students. Professor Sharma’s research interests include supply chain management, healthcare management, portfolio management, and stock market prediction, as well as mathematical programming, sampling, and artificial intelligence techniques. He has more than 225 peer-reviewed journal articles and conference proceedings to his credit, as well as numerous best paper awards. He is the Editor-in-Chief of the Journal of Global Information Technology and the Review of Business and Technology Research.

Ayodele Julius Alade, University of Maryland Eastern Shore, Maryland, USA

Ayodele Julius Alade, was the former Dean of the School of Business and Technology at the University of Maryland Eastern Shore. Prior to taking the deanship, he was Chair of the Department of Business, Management, and Accounting at the University of Maryland Eastern Shore as well as a Professor of Production and Operations Management and Quantitative Methods. He is currently a Professor and Director of Microsoft Center at UMES. He received his Ph.D. in Industrial Economics from the University of Utah. He has authored and co-authored numerous scholarly journal articles and abstracts that have been published in national and international journals and has been nominated and received several best paper awards. In his research, he has combined theoretic economics with financial and operations management, using linear and goal programming models. Dr. Alade has been involved in several international research activities and consulting/research engagements in international programs particularly in South Africa.

Alok Kumar Shukla, Department of Statistics, D.A.V. College, CSJM University, Kanpur, India

Alok Kumar Shukla is Assistant Professor of Statistics at D.A-V College, Kanpur, India. He received his Ph.D. degree in Statistics from Kanpur University. He is referee of many reputed national and international journals. His research interests are in sampling theory and regression analysis. He has published many research articles in international journals of repute.

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Published

2021-08-23

How to Cite

Yadav, S. K. ., Sharma, D. K. ., Alade, A. J. ., & Shukla, A. K. . (2021). Naive Regression Growth Models for Prediction of Peppermint Yield Production. Journal of Reliability and Statistical Studies, 14(02), 451–470. https://doi.org/10.13052/jrss0974-8024.1424

Issue

2021: Vol 14 Iss 2

Section

Articles