Structural time series model for forecasting potato production

The principal root and tuber crops of the tropics are potato (Solanum spp.) and grown almost in all states of India. Major potato growing states are Himachal Pradesh, Punjab, Uttar Pradesh, Madhya Pradesh, Gujarat, Maharashtra, Karnataka, West Bengal, Bihar and Assam. UP, West Bengal, Bihar and Punjab together account for about 86% of India's production. A univariate structural time series model based on the traditional decomposition into trend, seasonal and irregular components is defined. Purpose of present paper is to discuss 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. A number of methods of computing maximum Likelihood estimators are then considered. These include direct maximization of various times domain likelihood function. Once a model is estimated, its suitability can be assessed using goodness fit statistics and model used to forecast for five leading years. In our study the model developed for potato production, from the forecasting available.