Identification of patterns and choice of model in time series data is critical to facilitate forecasting. Two patterns that may be presented are trend and seasonality and the two competing models are the additive and multiplicative models. This paper uses the Buys Ballot table: (1) to provide an overview of recent developments in the identification and measure of trend and seasonality and choice of models in classical time series data analysis, and (2) to provide new insights into the development of new methodologies for effective identification of patterns and choice of models in classical time series data analysis when the trend is monotonous and the seasonal pattern is stable.

trend, seasonality, pattern identification, choice of models, additive and multiplicative models.