What is time series analysis with example?

Time series analysis is used to identify the fluctuation in economics and business . It helps in the evaluation of current achievements. Time series is used in pattern recognition, signal processing, weather forecasting and earthquake prediction.

Two of the most common models in time series are the Autoregressive (AR) models and the Moving Average (MA) models . The autoregressive model uses observations from preivous time steps as input to a regression equations to predict the value at the next step.

Time series data can be classified into two types:

These four components are:

Types of time series forecasting methods include:

Identifying Patterns in Time Series Data. Interrupted Time Series . Exponential Smoothing . Seasonal Decomposition (Census I)