Exploring crime in Philadelphia This is a large and intersting dataset and has data points stretching back over 10 years. Several explorations have pointed out that crime seems to be seasonal and I wanted to explore this with a time series. Assuming that seasonal trends might repeat themselves, I am exploring this using the forecast package and using linear regression to predict trends. suppressPackageStartupMessages({ library(data.table) library(forecast) library(knitr) }) Data size and structure.

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Revenue forecasting with linear methods. This post highlights linear regression techniques on time series data. We have some weekly sales data from a small business that is expected to have seasonal trends. A bike rental business in a major tourist city. Let’s dive into the data. Load up the required packages. suppressPackageStartupMessages({ library(forecast) }) Load the data, we have two columns with weekly revenue numbers from two different sources. Online and Phone; these correspond to sales online and via phone call to the business.

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