P. Mishra, Arti, B. Mondal, Rajnee Sharma, Binita Kumari, Tufleuddin Biswas, Soumik Ray
{"title":"用时间序列模型预测印度槟榔产量","authors":"P. Mishra, Arti, B. Mondal, Rajnee Sharma, Binita Kumari, Tufleuddin Biswas, Soumik Ray","doi":"10.18805/ag.d-5764","DOIUrl":null,"url":null,"abstract":"Background: Arecanut is popularly known as supari and is grown in many parts of the country. India maintained its first place in production among all the countries. In total world’s area and production, India contributes about 49 per cent and 59 per cent respectively. The area has expanded to various states such as Tamil Nadu, West Bengal, Maharashtra, Andhra Pradesh, Goa, Meghalaya and Tripura etc. Methods: The data from 1960-61 to 2015-16 is used to build the model, whereas data from 2016-17 to 2019-20 is used to validate the model. Appropriate statistical steps were adopted for model building and model validation. Holt’s linear and Holt’s exponential and ARIMA models is used in the study to forecast area, production and productivity for next five years from 2021 to 2025. Result: The results from the study revealed that Holt’s winter Exponential was the best model for predicating area and production whereas ARIMA (0, 1, 1) model was found best suited for predicating productivity.","PeriodicalId":7599,"journal":{"name":"Agricultural Science Digest – A Research Journal","volume":"53 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting of Arecanut in India using Time Series Model\",\"authors\":\"P. Mishra, Arti, B. Mondal, Rajnee Sharma, Binita Kumari, Tufleuddin Biswas, Soumik Ray\",\"doi\":\"10.18805/ag.d-5764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Arecanut is popularly known as supari and is grown in many parts of the country. India maintained its first place in production among all the countries. In total world’s area and production, India contributes about 49 per cent and 59 per cent respectively. The area has expanded to various states such as Tamil Nadu, West Bengal, Maharashtra, Andhra Pradesh, Goa, Meghalaya and Tripura etc. Methods: The data from 1960-61 to 2015-16 is used to build the model, whereas data from 2016-17 to 2019-20 is used to validate the model. Appropriate statistical steps were adopted for model building and model validation. Holt’s linear and Holt’s exponential and ARIMA models is used in the study to forecast area, production and productivity for next five years from 2021 to 2025. Result: The results from the study revealed that Holt’s winter Exponential was the best model for predicating area and production whereas ARIMA (0, 1, 1) model was found best suited for predicating productivity.\",\"PeriodicalId\":7599,\"journal\":{\"name\":\"Agricultural Science Digest – A Research Journal\",\"volume\":\"53 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural Science Digest – A Research Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18805/ag.d-5764\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Science Digest – A Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18805/ag.d-5764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting of Arecanut in India using Time Series Model
Background: Arecanut is popularly known as supari and is grown in many parts of the country. India maintained its first place in production among all the countries. In total world’s area and production, India contributes about 49 per cent and 59 per cent respectively. The area has expanded to various states such as Tamil Nadu, West Bengal, Maharashtra, Andhra Pradesh, Goa, Meghalaya and Tripura etc. Methods: The data from 1960-61 to 2015-16 is used to build the model, whereas data from 2016-17 to 2019-20 is used to validate the model. Appropriate statistical steps were adopted for model building and model validation. Holt’s linear and Holt’s exponential and ARIMA models is used in the study to forecast area, production and productivity for next five years from 2021 to 2025. Result: The results from the study revealed that Holt’s winter Exponential was the best model for predicating area and production whereas ARIMA (0, 1, 1) model was found best suited for predicating productivity.