Posts tagged pymc3.Exponential
GLM: Robust Regression using Custom Likelihood for Outlier Classification
- 17 November 2021
- Category: intermediate
Using PyMC3 for Robust Regression with Outlier Detection using the Hogg 2010 Signal vs Noise method.
A Primer on Bayesian Methods for Multilevel Modeling
- 09 November 2021
- Category: intermediate
Hierarchical or multilevel modeling is a generalization of regression modeling. Multilevel models are regression models in which the constituent model parameters are given probability models. This implies that model parameters are allowed to vary by group. Observational units are often naturally clustered. Clustering induces dependence between observations, despite random sampling of clusters and random sampling within clusters.
Splines in PyMC3
- 08 October 2021
- Category: beginner
Often, the model we want to fit is not a perfect line between some \(x\) and \(y\). Instead, the parameters of the model are expected to vary over \(x\). There are multiple ways to handle this situation, one of which is to fit a spline. The spline is effectively multiple individual lines, each fit to a different section of \(x\), that are tied together at their boundaries, often called knots. Below is an exmaple of how to fit a spline using the Bayesian framework PyMC3.
Hierarchical Partial Pooling
- 07 October 2021
- Category: intermediate
Suppose you are tasked with estimating baseball batting skills for several players. One such performance metric is batting average. Since players play a different number of games and bat in different positions in the order, each player has a different number of at-bats. However, you want to estimate the skill of all players, including those with a relatively small number of batting opportunities.
Rolling Regression
- 15 September 2021
- Category: intermediate
Pairs trading is a famous technique in algorithmic trading that plays two stocks against each other.