An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and Pakistan
Background. A country’s agriculture reflects a backbone and performs a vital part in the betterment of the economy and individuals. Facts and figures of the agriculture sector offer a solid foundation and factual pathway intended for upcoming decisions in favor of a country. Accordingly, the probabi...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2023/8713812 |
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| author | Muhammad Zeshan Arshad Muhammad Zafar Iqbal Festus Were Ramy Aldallal Fathy H. Riad M. E. Bakr Yusra A. Tashkandy Eslam Hussam Ahmed M. Gemeay |
| author_facet | Muhammad Zeshan Arshad Muhammad Zafar Iqbal Festus Were Ramy Aldallal Fathy H. Riad M. E. Bakr Yusra A. Tashkandy Eslam Hussam Ahmed M. Gemeay |
| author_sort | Muhammad Zeshan Arshad |
| collection | DOAJ |
| description | Background. A country’s agriculture reflects a backbone and performs a vital part in the betterment of the economy and individuals. Facts and figures of the agriculture sector offer a solid foundation and factual pathway intended for upcoming decisions in favor of a country. Accordingly, the probability models have a more significant influence not only in reliability engineering, hydrology, ecology, and medicine but also in agriculture sciences. Objective. The primary objective of this study is to propose a reliable and efficient model for pearl millet yield analysis, thereby empowering decision-makers to make informed decisions about their farming practices. With the successful implementation of this model, farmers can potentially increase their pearl millet yield, leading to higher incomes and improved livelihoods for the rural population of Pakistan. Model. This study proposes a novel probability model, namely, the alpha transformed odd exponential power function (ATOE-PF) distribution, for analyzing pearl millet yield in Punjab, Pakistan. Data. For data collection, two secondary data sets are explored that are electronically available on the site of the Directorate of Agriculture (Economics and Marketing) Punjab, Lahore, Pakistan. Results. The maximum likelihood estimation technique is used for estimating the model parameters. For the selection of a better fit model, we follow some accredited goodness of fit tests. The efficiency and applicability of the ATOE-PF distribution are discussed over the province of Punjab (with RMSE = 4.9176) and Pakistan (with RMSE = 4.5849). Better estimates and closest fit to data among the well-established neighboring models offer robust evidence in support of ATOE-PF distribution as well. |
| format | Article |
| id | doaj-art-a2d0f9a422a4456a97582774c98f77f7 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-a2d0f9a422a4456a97582774c98f77f72025-02-03T01:30:23ZengWileyComplexity1099-05262023-01-01202310.1155/2023/8713812An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and PakistanMuhammad Zeshan Arshad0Muhammad Zafar Iqbal1Festus Were2Ramy Aldallal3Fathy H. Riad4M. E. Bakr5Yusra A. Tashkandy6Eslam Hussam7Ahmed M. Gemeay8Department of Mathematics and StatisticsDepartment of Mathematics and StatisticsJomo Kenyatta University of Agriculture and TechnologyDepartment of AccountingMathematics Department College of ScienceDepartment of Statistics and Operations ResearchDepartment of Statistics and Operations ResearchHelwan UniversityDepartment of MathematicsBackground. A country’s agriculture reflects a backbone and performs a vital part in the betterment of the economy and individuals. Facts and figures of the agriculture sector offer a solid foundation and factual pathway intended for upcoming decisions in favor of a country. Accordingly, the probability models have a more significant influence not only in reliability engineering, hydrology, ecology, and medicine but also in agriculture sciences. Objective. The primary objective of this study is to propose a reliable and efficient model for pearl millet yield analysis, thereby empowering decision-makers to make informed decisions about their farming practices. With the successful implementation of this model, farmers can potentially increase their pearl millet yield, leading to higher incomes and improved livelihoods for the rural population of Pakistan. Model. This study proposes a novel probability model, namely, the alpha transformed odd exponential power function (ATOE-PF) distribution, for analyzing pearl millet yield in Punjab, Pakistan. Data. For data collection, two secondary data sets are explored that are electronically available on the site of the Directorate of Agriculture (Economics and Marketing) Punjab, Lahore, Pakistan. Results. The maximum likelihood estimation technique is used for estimating the model parameters. For the selection of a better fit model, we follow some accredited goodness of fit tests. The efficiency and applicability of the ATOE-PF distribution are discussed over the province of Punjab (with RMSE = 4.9176) and Pakistan (with RMSE = 4.5849). Better estimates and closest fit to data among the well-established neighboring models offer robust evidence in support of ATOE-PF distribution as well.http://dx.doi.org/10.1155/2023/8713812 |
| spellingShingle | Muhammad Zeshan Arshad Muhammad Zafar Iqbal Festus Were Ramy Aldallal Fathy H. Riad M. E. Bakr Yusra A. Tashkandy Eslam Hussam Ahmed M. Gemeay An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and Pakistan Complexity |
| title | An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and Pakistan |
| title_full | An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and Pakistan |
| title_fullStr | An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and Pakistan |
| title_full_unstemmed | An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and Pakistan |
| title_short | An Alternative Statistical Model to Analysis Pearl Millet (Bajra) Yield in Province Punjab and Pakistan |
| title_sort | alternative statistical model to analysis pearl millet bajra yield in province punjab and pakistan |
| url | http://dx.doi.org/10.1155/2023/8713812 |
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