Introduction A peculiar example Minimizing our error What minimizes the squared error? - a simulation Extensions and implications Introduction Everyone knows what the average is. To find the average of the bunch of numbers, simply add them all up and then divide the total by the number of … Continue reading →

Introduction Problem formulation Portfolio weights Portfolio expectation and variance The math behind diversification Two uncorrelated assets Two correlated assets Starting with two assets Efficient Portfolios Minimum variance portfolio Risk-free assets One “risky” asset and one … Continue reading →

Introduction I am using waterfall charts drawn in ggplot2 to visualize GLM coefficients, for regression and classification. Source Rmd file can be found here. Waterfall chart: inspired by their commonplace use in finance1, a simple visualization to illustrate the constituent components … Continue reading →

This is a worked example on how to set up SQL Server, SQL Server Management Studio, and a ODBC connection with R. Step 1: Install SQL Server from https://www.microsoft.com/en-us/sql-server/sql-server-downloads. The SQL Server 2017 Express was good enough for me to run some analysis and modelling … Continue reading →

This is a worked example on how to set up SQL Server, SQL Server Management Studio, and a ODBC connection with R. Step 1: Install SQL Server from https://www.microsoft.com/en-us/sql-server/sql-server-downloads. The SQL Server 2017 Express was good enough for me to run some analysis and modelling … Continue reading →

Introduction As the name suggests, random forest models basically contain an ensemble of decision tree models, with each decision tree predicting the same response variable. The response may be categorical, in which case being a classification problem, or continuous / numerical, being a … Continue reading →