Samuel Müller

Orcid: 0000-0002-3087-8127

Affiliations:
  • University of Sydney, School of Mathematics and Statistics, Australia


According to our database1, Samuel Müller authored at least 14 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Likelihood-based surrogate dimension reduction.
Stat. Comput., February, 2024

2023
Surface Area Estimation Using 3D Point Clouds and Delaunay Triangulation.
Proceedings of the Second International Conference on Innovations in Computing Research (ICR'23), 2023

2022
Cross-Platform Omics Prediction procedure: a statistical machine learning framework for wider implementation of precision medicine.
npj Digit. Medicine, 2022

2021
MCVIS: A New Framework for Collinearity Discovery, Diagnostic, and Visualization.
J. Comput. Graph. Stat., 2021

2020
The LASSO on latent indices for regression modeling with ordinal categorical predictors.
Comput. Stat. Data Anal., 2020

LC-N2G: a local consistency approach for nutrigenomics data analysis.
BMC Bioinform., 2020

2019
bcGST - an interactive bias-correction method to identify over-represented gene-sets in boutique arrays.
Bioinform., 2019

2017
2nd special issue on robust analysis of complex data.
Comput. Stat. Data Anal., 2017

2016
On generalized degrees of freedom with application in linear mixed models selection.
Stat. Comput., 2016

Robust estimation of precision matrices under cellwise contamination.
Comput. Stat. Data Anal., 2016

2015
Inferring data-specific micro-RNA function through the joint ranking of micro-RNA and pathways from matched micro-RNA and gene expression data.
Bioinform., 2015

2014
Identification of important regressor groups, subgroups and individuals via regularization methods: application to gut microbiome data.
Bioinform., 2014

2013
Revisiting fitting monotone polynomials to data.
Comput. Stat., 2013

2011
Partially smooth tail-index estimation for small samples.
Comput. Stat., 2011


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