Time series modeling technique is used to model a series of sales data in which seasonality causes distinct spike peaks. The analysis of actual sales data shows that the seasonality in the data can be ...

Bayesian approaches to the study of politics are increasingly popular. But Bayesian approaches to modeling multiple time series have not been critically evaluated. This is in spite of the potential ...

Time series analysis involves identifying attributes of your time series data, such as trend and seasonality, by measuring statistical properties. From stock market analysis to economic forecasting, ...

Artificial intelligence (AI) technologies are currently revolutionizing industries and enabling automation on a scale we've never seen before. Of course, none of this is possible without data. These ...

1. Difference Equations -- 2. Lag Operators -- 3. Stationary ARMA Processes -- 4. Forecasting -- 5. Maximum Likelihood Estimation -- 6. Spectral Analysis -- 7 ...