ARIMA (Autoregressive Integrated Moving Average) is a major tool used in time series analysis to attempt to forecast future values of a variable based on its present value. For this particular example, I use a stock price dataset of Johnson & Johnson (JNJ) from 2006-2016, and use the aforementioned model to conduct price forecasting on this time series.
PostgreSQL is a commonly used database language for creating and managing large amounts of data effectively.
Here, you will see how to:
- create a PostgreSQL database using the Linux terminal
- connect the PostgreSQL database to R using the “RpostgreSQL” library, and to Python using the “psycopg2” library
A K-Means Clustering algorithm allows us to group observations in close proximity to the mean. This allows us to create greater efficiency in categorising the data into specific segments.
In this instance, K-Means is used to analyse traffic clusters across the City of London.