time series

Time-series analysis aims to analyse and learn the temporal behaviour of datasets over a period. Examples include the investigation of long-term records of temperature , sea-level fluctuations, the effect of the El Niño/Southern Oscillation on tropical rainfall, and surface current influences on distribution of temperature and rainfall. Th e temporal pattern of a sequence of events in a time series data can be either random, clustered, cyclic, or chaotic.

Forecast time series introduction Time series analysis comprises methods for predicting the future based on the historical in order to extract meaningful statistics and other characteristics of the data. In other words, time series forecasting is the use of a model to predict future values based on previously observed values. Time series are widely used for non-stationary data, like economic, weather, stock price, and retail sales in this post.