Writing
Generalized Linear Models
A Generalized Linear Model, if viewed without knowledge of their motivation, can be a confusing tool. It's easier to understand if seen as a two knob generalization of linear regression.
The Fisher Information
The Fisher Information quantifies the information an observation carries for a parameter. The quantification becomes intuitive once we see it measuring a certain geometric quality.
The Copula and 2008
The copula provides a clever means for mixing and matching a set of marginal distributions with the joint-only mechanism of a joint distribution. However, its elegance and utility have been a dangerous lure.
The Matrix Inversion Lemma
The Matrix Inversion Lemma looks intimidating, but it is easy to know when it applies. Doing so offers considerable computational speed ups.
Bayesian Optimization
When optimizing a slow-to-evaluate and non-differentiable function, one may think random sampling is the only option--a naive approach likely to disappoint. However, Bayesian optimization, a clever exploit of the function assumed smoothness, disconfirms these intuitions.
The Fundamental Law of Active Management
The Fundamental Law of Active Management decomposes a well known summarizing metric of an investment strategy. The decomposition yields two dimensions along which all strategies may be judged and suggests avenues for improvement.
The Exponential Family
The exponential family is a generalization of distributions, inclusive of many familiar ones plus a universe of others. The general form brings elegant properties, illuminating all distributions within. In this post, we discuss what it is, how it applies and some of its properties.
Motivating the Gini Impurity Metric
We reveal the gini impurity metric as the destination of a few natural steps.
The Trace as a Measure of Complexity
For a class of models, the trace provides a measure of model complexity that's useful for managing the bias variance trade-off.