Analysis and Forecasting of Area Under Cultivation of Rice in India: Univariate Time Series Approach.

This study uses three distinct models to analyse a univariate time series of data: Holt's exponential smoothing model, the autoregressive integrated moving average (ARIMA) model, and the neural network autoregression (NNAR) model. The effectiveness of each model is assessed using in-sample forecasts and accuracy metrics, including mean absolute percentage error, mean absolute square error, and root mean square log error. The area under cultivation in India for the following 5 years is predicted using the model whose fitted values are most like the observed values.