An overview on R packages for seasonal analysis of time series

Time series analysis consists of approaches for analysing time series data so thatimportant information and other features can be isolated from the data. Time series forecasting is the use of a model to predict perspective values on the basis of previouly observed values by a model. Statisticians generally use R project or R language, a free and popular programming language and computer software environment for statistical computing and graphics, for developing statistical computer software and data analysis. Plenty of time series display cyclic variation significant as seasonality, periodic variation, or periodic fluctuations in statistics. This study introducesabundant functions in the R packages TSA, marls, depersonalize and season for analyzing seasonal processes of time series, are introduced in this study. Note that R packages marls, depersonalize and season are included in the comprehensive R archive network task view TimeSeries.