Topic: robust-statistics Goto Github
Some thing interesting about robust-statistics
Some thing interesting about robust-statistics
robust-statistics,Robust Sure Independence Screening using the Minimum Density Power Divergence Estimators
User: abhianik
robust-statistics,Robust statistics in Python
User: alcampopiano
Home Page: https://alcampopiano.github.io/hypothesize/
robust-statistics,FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
User: andrewwango
robust-statistics,This repository provides a unified framework to perform Optimization experiments across Stochastic, Mini-Batch, Decentralized and Federated Setting.
User: anishacharya
robust-statistics,Solve many kinds of least-squares and matrix-recovery problems
User: baggepinnen
robust-statistics,Neural Networks package for R with a fast C++ back-end and special support for unsupervised anomaly detection using autoencoders
User: bflammers
robust-statistics,:deciduous_tree: :dart: Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation
User: blind-contours
robust-statistics,This is an open source library that can be used to autofocus telescopes. It uses a novel algorithm based on robust statistics. For a preprint, see https://arxiv.org/abs/2201.12466 .The library is currently used in Astro Photography tool (APT) https://www.astrophotography.app/
User: bschulz81
robust-statistics,a c++ library with statistical machine learning algorithms for linear and non-linear robust regression that can be used with python.
User: bschulz81
robust-statistics,CRAN Task View: Robust Statistical Methods
Organization: cran-task-views
Home Page: https://CRAN.R-project.org/view=Robust
robust-statistics,R Package implementing the Penalized Elastic Net S- and MM-Estimator for Linear Regression
User: dakep
Home Page: https://dakep.github.io/pense-rpkg
robust-statistics,Code of the paper The Robust Randomized Quasi Monte Carlo method, applications to integrating singular functions by E. Gobet M. Lerasle and D. Métivier
User: dmetivie
robust-statistics,Implement some Robust Mean Estimators
User: dmetivie
robust-statistics,:bar_chart: Computation and processing of models' parameters
Organization: easystats
Home Page: https://easystats.github.io/parameters/
robust-statistics,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.
User: eliasraninen
robust-statistics,Feature transformation is a technique in machine learning that changes the way features are represented in order to improve the performance of machine learning algorithms. This can be done by transforming the features to a different scale, removing outliers, or creating new features from existing
User: emamulhossen
Home Page: https://github.com/EmamulHossen/FeatureTransformation
robust-statistics,Robust freeform surface modeling from user 2d sketches.
User: enigma-li
Home Page: http://haopan.github.io/sketchCNN.html
robust-statistics,Robustats is a Python library for high-performance computation of robust statistical estimators.
User: filippobovo
robust-statistics,A research compendium for an article published in JAS:Reports (2020), "Modern methods for old data: An overview of some robust methods for outliers detection with applications in osteology".
User: frederic-santos
Home Page: https://doi.org/10.1016/j.jasrep.2020.102423
robust-statistics,A small collection of lesser-known statistical measures
User: glevv
robust-statistics,This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.
Organization: google
robust-statistics,An Econometric Analysis of North Carolina Crime Data from 1987
User: gregtozzi
robust-statistics,FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
User: houdouinpierre
robust-statistics,Tidy data frames and expressions with statistical summaries 📜
User: indrajeetpatil
Home Page: https://indrajeetpatil.github.io/statsExpressions/
robust-statistics,Direct and robust methods for outlier detection in linear regression
User: jbytecode
robust-statistics,This is an R package I developed to estimate the causal effect of an exposure on an outcome when there's invalid instruments and large proportions of contamination.
User: jfosea
robust-statistics,Trimmed L-moments and L-comoments for robust statistics.
User: jorenham
Home Page: https://jorenham.github.io/Lmo/
robust-statistics,Official implementation of the paper: "REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions", IEEE WACV, 2022
User: lokender
Home Page: https://lokender.github.io/REGroup.html
robust-statistics,Robust Offline Reinforcement Learning with Heavy-Tailed Rewards
User: mamba413
robust-statistics,robust optimization
User: microprediction
robust-statistics,A robust deterministic affine-equivariant algorithm for multivariate location and scatter
User: mpokojovy
robust-statistics,Python PyTorch (GPU) and NumPy (CPU)-based port of Févotte and Dobigeon's robust-NMF algorithm appearing in "Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization."
User: neel-dey
robust-statistics,:package: :game_die: R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling
User: nhejazi
Home Page: https://codex.nimahejazi.org/txshift
robust-statistics,Robust Chauvenet Outlier Rejection: RCR is advanced, but easy to use, outlier rejection.
User: nickk124
Home Page: https://rcr.readthedocs.io
robust-statistics,Doubly-Robust and Efficient Estimators for Survival and Ordinal Outcomes in RCTs Without Proportional Hazards or Odds Assumptions :pill:
User: nt-williams
robust-statistics,:package: Non-parametric Causal Effects Based on Modified Treatment Policies :crystal_ball:
User: nt-williams
robust-statistics,Delicatessen: the Python one-stop sandwich (variance) shop
User: pzivich
Home Page: https://deli.readthedocs.io/en/latest/index.html
robust-statistics,Robust particle filter based on dynamic averaging of multiple noise models
User: robinlau1981
robust-statistics,This project contains the code for the paper accepted at NeurIPS 2020 - Robust Meta-learning for Mixed Linear Regression with Small Batches.
Organization: sewoonglab
robust-statistics,Defending Against Backdoor Attacks Using Robust Covariance Estimation
Organization: sewoonglab
robust-statistics,MATLAB pipeline for easy-to-program automated pre-processing of electroencephalogram (EEG) data using independent component analysis and statistically-robust detection of artifacts.
User: sjburwell
robust-statistics,Various numerical routines in C and C++
User: slugrustle
robust-statistics,Simple multiverse analysis simulations, visualizations and inference techniques.
User: stefherregods
robust-statistics,Robust Gaussian Process with Iterative Trimming
User: syrte
robust-statistics,Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
Organization: tlverse
Home Page: https://tlverse.org/causalglm/
robust-statistics,Robust estimations from distribution structures: Central moments.
User: tubanlee
Home Page: https://doi.org/10.5281/zenodo.8127703
robust-statistics,Robust estimations from distribution structures: Invariant moments.
User: tubanlee
Home Page: https://doi.org/10.5281/zenodo.8127703
robust-statistics,Robust estimations from distribution structures: Mean.
User: tubanlee
Home Page: https://doi.org/10.5281/zenodo.6629988
robust-statistics,Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.
User: uniprjrc
Home Page: https://uniprjrc.github.io/FSDA/
robust-statistics,Robust locally weighted multiple regression in Python
User: yaniv-shulman
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