FORECASTING TEA PRODUCTION IN INDIA: A TIME SERIES APPROACH

被引：0

作者：

Deka, Sakuntala ^{[1
]}

Hazarika, P. J. ^{[1
]}

Goswanill, K. ^{[1
]}

Patowary, A. N. ^{[2
]}

机构：

[1] Dibrugarh Univ, Dept Stat, Dibrugarh 786004, Assam, India

[2] Assam Agr Univ, Coll Fisheries, Raha 782103, India

来源：

INTERNATIONAL JOURNAL OF AGRICULTURAL AND STATISTICAL SCIENCES | 2022年 / 18卷 / 01期

关键词：

ARIMA; Forecasting; Tea production; Mean absolute percentage error; Time series analysis;

D O I：

暂无

中图分类号：

S [农业科学];

学科分类号：

09 ;

摘要：

Tea is one of India's most famous hot beverages and India is the second-largest producer of tea, which results in 23% of the world tea production. The tea industry plays a vital role in the Indian economy. Also, it has a substantial impact on the livelihood of many people employed directly and indirectly by the industry. This research study outlines the development of a conventional time series model, namely the Autoregressive Integrated Moving Average (ARIMA) model for the annual tea production of India. The study used R programming for the analysis. The analyzed data are secondary and obtained from the Tea Board of India, Ministry of Commerce, from 1947 to 2016 with 70 years of data. Based on different diagnostic and evaluation criteria, ARIMA (1,1,2) is the best-fitted forecasting model.

引用

页码：105 / 112

页数：8

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