shrinkage

R package for adaptive correlation and covariance matrix shrinkage.

Experiments with experimental rule-based models to go along with imodels.

[AAAI 2026, oral] unshrink: post-hoc debiasing of machine learning predictions to reduce shrinkage-induced attenuation bias in downstream causal inference -- without requiring fresh ground-truth data

Code for the paper E. Raninen and E. Ollila, "Bias Adjusted Sign Covariance Matrix," in IEEE Signal Processing Letters, vol. 29, pp. 339-343, 2022, doi: 10.1109/LSP.2021.3134940.

This repository contains data and code relative to the manuscript "A large covariance matrix estimator under intermediate spikiness regimes" by Matteo Farnè and Angela Montanari (https://arxiv.org/abs/1711.08950).

Code for the paper E. Raninen, D. E. Tyler and E. Ollila, "Linear pooling of sample covariance matrices," in IEEE Transactions on Signal Processing, Vol 70, pp. 659-672, 2022, doi: 10.1109/TSP.2021.3139207.

A collaborative repository highlighting Bayesian autoregressive analysis with extensions. It is prepared by the students of Macroeconometrics at the University of Melbourne.

Horseshoe regression model fitted in PyMC.

Tool combining pngcrush and optipng to optimize input PNG

Code for the paper E. Raninen and E. Ollila, “Coupled regularized sample covariance matrix estimator for multiple classes,” in IEEE Transactions on Signal Processing, vol. 69, pp. 5681–5692, 2021, doi: 10.1109/TSP.2021.3118546.

My Master's thesis on Bayesian Classification with Regularized Gaussian Models

Nested Cross-Validation for Bayesian Optimized Linear Regularization

Introduction to Data Mining

Sliding Filter for AWGN Denoising

Deformable lattice Boltzmann method for diffusion in 1D moving domains

Word Enrichment Analysis using VEctor Representations

Privacy-preserving hierarchical Bayes for multi-tenant fleets: empirical-Bayes partial pooling, cold-start mitigation, zero-dependency TypeScript.

Jackstraw Weighted Shrinkage Methods

Example code for "Bayesian shrinkage priors for penalized synthetic control estimators in the presence of spillovers."

R package for Dirichlet adaptive shrinkage and smoothing