Structural Time-Series Models for Forecasting Yield of Promising Varieties of Rice Crop in Chhattisgarh

  IJMTT-book-cover
 
International Journal of Mathematics Trends and Technology (IJMTT)
 
© 2015 by IJMTT Journal
Volume-26 Number-2
Year of Publication : 2015
Authors : Roshan Kumar Bharadwaj, S.S. Gautam, R.R. Saxena
  10.14445/22315373/IJMTT-V26P513

MLA

Roshan Kumar Bharadwaj, S.S. Gautam, R.R. Saxena "Structural Time-Series Models for Forecasting Yield of Promising Varieties of Rice Crop in Chhattisgarh", International Journal of Mathematics Trends and Technology (IJMTT). V26(2):58-62 October 2015. ISSN:2231-5373. www.ijmttjournal.org. Published by Seventh Sense Research Group.

Abstract
A univariate structural time series model based on the traditional decomposition into trend, seasonal and irregular components is measured. Purpose of present paper is to discuss Structural Time Series Model (STM) methodology utilized for modelling time-series data in the present of trend, seasonal and cyclic fluctuations. Structural time series model are formulated in such a way that their components are stochastic, i.e. they are regard as being driven by random disturbances. The study mainly confined to secondary collected for a period 2009-10 to 2014-15 data of promising varieties of Rice yield. As these techniques, it may be mentioned that models are fitted to the data and coefficient parameter value obtained on the basis of the model are compared with the actual observation for assessing the accuracy of the fitted model. To validate the forecasting ability of the fitted models, for the three years with upper and lower limit. The maximum rice yield obtained Swarna variety with forecast for the year 2017-18 obtained 50.31 q/ha with upper and lower limit 53.84 and 46.78 q/ha. The minimum yield obtained PKV-HMT (33.79 q/ha) with upper and lower limit 45.63 and 21.96 q/ha respectively.

References
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Keywords
Structural time series model, AIC, BIC, Goodness of fit