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http://krishi.icar.gov.in/jspui/handle/123456789/73143
Title: | Trends in marine fish production in Tamil Nadu using regression and autoregressive integrated moving average (ARIMA) model. |
Other Titles: | Not Available |
Authors: | Anuja A, Yadav VK*, Bharti VS, Kumar NR |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR: Central Institute of Fisheries Education |
Published/ Complete Date: | 2017-04-10 |
Project Code: | Not Available |
Keywords: | ARIMA, BIC, Marine Production, Sustainable fishing, Trend line regression, Tamil Nadu |
Publisher: | Research Gate |
Citation: | Not Available |
Series/Report no.: | Not Available; |
Abstract/Description: | Tamil Nadu is situated in the south eastern coast of the Indian peninsula with a coastal line of 1076 km (13% of the country’s coast line), 0.19 million sq.km of EEZ (9.4 % of total national EEZ) and a continental shelf of about 41,412 sq. km. This is one of the country’s leading state in marine fish production and ranks third in marine fish production. In Tamil Nadu, Ramanathapuram district is a leading maritime district followed by Nagapattinam and Thoothukudi. The objective of this study was to investigate the trends in marine fish production in Tamil Nadu. Year-ly fish production data for the period of 1988-1989 to 2012-2013 were analyzed using time-series method called Autoregressive Integrated Moving Average (ARIMA) model and Regression analysis (curve estimation). In our study, the developed best ARIMA model for Tamil Nadu marine fish production was found to be ARIMA (1, 1, 1) which have the minimum BIC (Bayesian Information Criterion). ARIMA model had got a slightly higher forecasting accuracy rate for forecasting marine fish production of Tamil Nadu than Regression trend analysis. The independent sample test showed there was no significant difference between the two models. The limitations of ARIMA model include its requirement of a long time series data for better forecast. It is basically linear model assuming that data are stationary and have a limited ability to capture non-stationarities and nonlinearities in series data. Both the mod-els indicated that Tamil Nadu marine fish production has plateaued and fishermen should be encouraged to adopt sustainable fishing practices. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Journal of Applied and Natural Science |
Journal Type: | International |
NAAS Rating: | 5.1 |
Volume No.: | 9 (2) |
Page Number: | 653-657 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | Not Available |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/73143 |
Appears in Collections: | FS-CIFE-Publication |
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