Open AccessFORECASTING THE CROP YIELD OF A COCONUT ESTATE
Author(s) -
T.S.G. Peiris
Publication year - 1989
Publication title -
cord. coconut research and development/cord
Language(s) - English
Resource type - Journals
eISSN - 2721-8856
pISSN - 0215-1162
DOI - 10.37833/cord.v5i02.226
Subject(s) - autoregressive integrated moving average , autoregressive model , yield (engineering) , mathematics , variance (accounting) , econometrics , statistics , series (stratigraphy) , estate , set (abstract data type) , time series , agricultural engineering , environmental science , computer science , economics , engineering , materials science , accounting , metallurgy , biology , finance , programming language , paleontology
Seasonal Autoregressive Integrated Moving Average (ARIMA) process of (0,1,2) x (0,1,1) x 6 that best fits a set of crop‑wise coconut yield data, in Bandirippuwa, Lunuwila is identified without using variance stabilization transformation. In this process the present value of the series may be described as a linear function of the past observation of the series and past disturbances. The physical factors such as rainfall, temperature, day length etc. are not required for this method, however the past crop figures in the estate is needed. While such model is useful for short term forecasting, it also gives the upper and lower limits of the forecasts at a given probability. These intervals would provide the quantified information on the degree of duration of the forecasts.