My Master's thesis on Bayesian Classification with Regularized Gaussian Models
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Updated
Dec 27, 2015 - R
My Master's thesis on Bayesian Classification with Regularized Gaussian Models
Jackstraw Weighted Shrinkage Methods
Word Enrichment Analysis using VEctor Representations
R package for Dirichlet adaptive shrinkage and smoothing
R package for adaptive correlation and covariance matrix shrinkage.
Introduction to Data Mining
Nested Cross-Validation for Bayesian Optimized Linear Regularization
Base saturation percentage determination using shrinkage method. Due to the multicollinearity issue, we chose shrinkage/penalized/regularized regression. Since, we have small number of samples, we had no luxury of having separate test set of data, so we did iterated k-Fold cross validation.
Final Project from the course - Computational Statistics (Summer Term, 2020), University of Bonn
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.
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.
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.
Accelerated matrix Factorization via Infinite Latent Elements with structured shrinkage
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).
Sliding Filter for AWGN Denoising
A collaborative repository highlighting Bayesian autoregressive analysis with extensions. It is prepared by the students of Macroeconometrics at the University of Melbourne.
Deformable lattice Boltzmann method for diffusion in 1D moving domains
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