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http://krishi.icar.gov.in/jspui/handle/123456789/42975
Title: | Wavelet based Multi-scale Auto-Regressive (MAR) Model: An Application for Prediction of Coconut Price in Kerala |
Other Titles: | Not Available |
Authors: | S Sarkar R.K. Paul A.K. Paul L.M. Bhar |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Indian Agricultural Statistics Research Institute |
Published/ Complete Date: | 2019-01-01 |
Project Code: | Not Available |
Keywords: | ARFIMA Long Range Dependence (LRD) Multi-scale Auto-Regressive (MAR) model Wavelet transformation |
Publisher: | Not Available |
Citation: | Sarkar, Sandipan, Paul, Ranjit Kumar, Paul, A.K. and Bhar, L.M. (2019). Wavelet based Multi-scale Auto-Regressive (MAR) Model: An Application for Prediction of Coconut Price in Kerala, Journal of the Indian Society of Agricultural Statistics ,73(1), 1–10. |
Series/Report no.: | Not Available; |
Abstract/Description: | In recent times, forecasting of agricultural commodity price becomes a major issue. But in the context of forecasting of time series data exhibiting Long-Range Dependence (LRD) becomes more complex with the fractional differencing value. In general, Autoregressive Fractionally Integrated Moving Average (AFRIMA) model is widely used for time-series forecasting having long range dependency. It has been observed that in many cases forecasting performance with ARFIMA model is not satisfactory. Therefore, Multi-scale Autoregressive (MAR) model based on wavelets decomposition can be used as an alternative for time-series forecasting. In the present investigation, MAR model is estimated using wavelet decomposition at level 6. Here, an attempt has been made to improve the forecasting performance of MAR model by inclusion of some extra regressors (modified MAR model). Daily wholesale price data on coconut of Kerala market has been used for the illustration purpose. A comparative study has been made for ARFIMA, MAR and modified MAR model in terms of Mean Squared Error (MSE) and Root Mean Squared Error (RMSE). The empirical study reveals that forecasting ability of modified MAR model outperforms the other two methodologies in terms of lower MSE and RMSE values. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Journal of The Indian Society of Agricultural Statistics |
NAAS Rating: | 5.51 |
Volume No.: | 73 (1) |
Page Number: | 1-10 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | Not Available |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/42975 |
Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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1-Sandipan.pdf | 901.08 kB | Adobe PDF | View/Open |
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