Samuel Muller

Research Outputs

Research output per year 1998 2005 2011 2013 2015 2016 2017 2019 2020 2021 2022 2023 2024 2025

• 85 Article
• 6 Conference proceeding contribution
• 5 Meeting abstract
• 4 Other report
• 14 More
  • 4 Software
  • 3 Other journal contribution
  • 2 Review article
  • 1 Conference abstract
  • 1 Editorial
  • 1 Doctoral Thesis
  • 1 Master (Coursework) Thesis
  • 1 Preprint

Research output per year

Research output per year

Search results

• 2025

  Best subset solution path for linear dimension reduction models using continuous optimization

  Liquet, B., Moka, S. & Muller, S., Feb 2025, In: Biometrical Journal. 67, 1, p. 1-17 17 p., e70015.

  Research output: Contribution to journal › Article › peer-review
• 2024

  Advancing student outcome predictions through generative adversarial networks

  Farhood, H., Joudah, I., Beheshti, A. & Muller, S., Dec 2024, In: Computers and Education: Artificial Intelligence. 7, p. 1-13 13 p., 100293.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  37 Downloads (Pure)

• COMBSS: best subset selection via continuous optimization

  Moka, S., Liquet, B., Zhu, H. & Muller, S., Apr 2024, In: Statistics and Computing. 34, 2, p. 1-22 22 p., 75.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Continuous Optimization 100%
  • Subset Selection 99%
  • Linear regression 24%
  • Linear Regression 22%
  • Subset 21%
  1 Citation (Scopus)

  82 Downloads (Pure)

• CR-Lasso: Robust cellwise regularized sparse regression

  Su, P., Tarr, G., Muller, S. & Wang, S., Sept 2024, In: Computational Statistics and Data Analysis. 197, p. 1-14 14 p., 107971.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Lasso 100%
  • Minerals 85%
  • Bone 82%
  • Contamination 82%
  • Feature extraction 65%
  1 Citation (Scopus)

  47 Downloads (Pure)

• Evaluating and enhancing artificial intelligence models for predicting student learning outcomes

  Farhood, H., Joudah, I., Beheshti, A. & Muller, S., Sept 2024, In: Informatics. 11, 3, p. 1-17 17 p., 46.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  1 Citation (Scopus)

  36 Downloads (Pure)

• Likelihood-based surrogate dimension reduction

  Nghiem, L. H., Hui, F. K. C., Muller, S. & Welsh, A. H., Feb 2024, In: Statistics and Computing. 34, 1, p. 1-15 15 p., 51.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Dimension Reduction 100%
  • Surrogate 62%
  • Central Subspace 45%
  • Likelihood 44%
  • Estimator 41%
  60 Downloads (Pure)

• Robust variable selection methods with Cox model—a selective practical benchmark study

  Zhang, Y. & Muller, S., 1 Nov 2024, In: Briefings in Bioinformatics. 25, 6, p. 1-9 9 p., bbae508.

  Research output: Contribution to journal › Review article › peer-review

  Open Access

  File
  19 Downloads (Pure)

• Robust variable selection under cellwise contamination

  Su, P., Tarr, G. & Muller, S., 2024, In: Journal of Statistical Computation and Simulation. 94, 6, p. 1371-1387 17 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Variable Selection 100%
  • Outliers 74%
  • Contamination 65%
  • Outlier 53%
  • Covariance matrix 28%
  80 Downloads (Pure)

• The effect of the working correlation on fitting models to longitudinal data

  Muller, S., Wang, S. & Welsh, A. H., Jun 2024, In: Scandinavian Journal of Statistics. 51, 2, p. 891-912 22 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Longitudinal Data 100%
  • Model Fitting 77%
  • Estimator 51%
  • Generalized Estimating Equations 46%
  • Inference 35%
  41 Downloads (Pure)
• 2023

  A Multi-step precision pathway for predicting allograft survival in heterogeneous cohorts of kidney transplant recipients

  Zhang, Y., Deng, D., Muller, S., Wong, G. & Yang, J. Y. H., Sept 2023, In: Transplant International. 36, 9, p. 1-8 8 p., 11338.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Transplant Recipients 100%
  • Allografts 94%
  • Transplants 67%
  • Kidney 57%
  • Registries 42%
  1 Citation (Scopus)

  29 Downloads (Pure)

• GEE-assisted variable selection for latent variable models with multivariate binary data

  Hui, F. K. C., Müller, S. & Welsh, A. H., 2023, In: Journal of the American Statistical Association. 118, 542, p. 1252-1263 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Variable Selection 100%
  • Generalized Estimating Equations 79%
  • Latent Variable Models 77%
  • Binary Data 64%
  • Multivariate Data 61%
  2 Citations (Scopus)

• NEMoE: a nutrition aware regularized mixture of experts model to identify heterogeneous diet-microbiome-host health interactions

  Xu, X., Lubomski, M., Holmes, A. J., Sue, C. M., Davis, R. L., Muller, S. & Yang, J. Y. H., Dec 2023, In: Microbiome. 11, p. 1-14 14 p., 51.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Ecotype 100%
  • Microbiota 56%
  • Diet 39%
  • Health 28%
  • Parkinson Disease 16%
  2 Citations (Scopus)

  39 Downloads (Pure)

• Screening methods for linear errors-in-variables models in high dimensions

  Nghiem, L. H., Hui, F. K. C., Müller, S. & Welsh, A. H., Jun 2023, In: Biometrics. 79, 2, p. 926-939 14 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Errors-in-variables Model 100%
  • Screening 84%
  • Microarrays 82%
  • Higher Dimensions 70%
  • Linear Model 67%
  3 Citations (Scopus)

  68 Downloads (Pure)

• simKAP: simulation framework for the kidney allocation process with decision making model

  Zhang, Y., Hu, A., Lin, Y., Cao, Y., Muller, S., Wong, G. & Yang, J. Y. H., 2023, In: Scientific Reports. 13, p. 1-9 9 p., 16367.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Clinical Decision-Making 100%
  • Decision Making 78%
  • Transplantation 72%
  • Transplants 59%
  • Kidney 50%
  77 Downloads (Pure)

• Surface area estimation using 3D point clouds and Delaunay triangulation

  Farhood, H., Muller, S. & Beheshti, A., 2023, Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23). Daimi, K. & Al Sadoon, A. (eds.). Cham: Springer, Springer Nature, p. 28-39 12 p. (Lecture Notes in Networks and Systems; vol. 721).

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  • Triangulation 100%
  • Remote sensing 15%
  • Cellular telephones 14%
  • Costs 11%
  • Cameras 10%
  1 Citation (Scopus)
• 2022

  COMBSS: Best Subset Selection via Continuous Optimization

  Moka, S., Liquet, B., Zhu, H. & Muller, S., 5 May 2022, (Submitted) arXiv.org, (arXiv).

  Research output: Working paper › Preprint

  • Linear regression 100%
  • Set theory 95%
  • Feature extraction 38%

• Cross-Platform Omics Prediction procedure: a statistical machine learning framework for wider implementation of precision medicine

  Wang, K. Y. X., Pupo, G. M., Tembe, V., Patrick, E., Strbenac, D., Schramm, S. J., Thompson, J. F., Scolyer, R. A., Muller, S., Tarr, G., Mann, G. J. & Yang, J. Y. H., Dec 2022, In: npj Digital Medicine. 5, 1, p. 1-10 10 p., 85.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Personalized medicine 100%
  • Machine Learning 78%
  • Precision Medicine 74%
  • Machine learning 50%
  • Inflammatory Bowel Diseases 32%
  3 Citations (Scopus)

  50 Downloads (Pure)

• Estimation of graphical models for skew continuous data

  Nghiem, L. H., Hui, F. K. C., Müller, S. & Welsh, A. H., Dec 2022, In: Scandinavian Journal of Statistics. 49, 4, p. 1811-1841 31 p.

  Research output: Contribution to journal › Article › peer-review

  • Graphical Models 100%
  • Skew 65%
  • Graph 45%
  • Error Bounds 35%
  • Skewed Distribution 33%
  1 Citation (Scopus)

• Nutritional intake and gut microbiome composition predict Parkinson’s disease

  Lubomski, M., Xu, X., Holmes, A. J., Muller, S., Yang, J. Y. H., Davis, R. L. & Sue, C. M., 11 May 2022, In: Frontiers in Aging Neuroscience. 14, p. 1-16 16 p., 881872.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Gastrointestinal Microbiome 100%
  • Parkinson Disease 84%
  • Forests 26%
  • Lactobacillaceae 20%
  • Bacterial DNA 14%
  12 Citations (Scopus)

  51 Downloads (Pure)

• Robust subtractive stability measures for fast and exhaustive feature importance ranking and selection in generalised linear models

  Smith, C., Guennewig, B. & Muller, S., Sept 2022, In: Australian and New Zealand Journal of Statistics. 64, 3, p. 339-355 17 p.

  Research output: Contribution to journal › Article › peer-review

  • Ranking and Selection 100%
  • Generalized Linear Model 92%
  • Robust Regression 89%
  • Robust Stability 78%
  • Lack of Fit 67%
  1 Citation (Scopus)

• Sparse sliced inverse regression via Cholesky matrix penalization

  Nghiem, L. H., Hui, F. K. C., Müller, S. & Welsh, A. H., 2022, In: Statistica Sinica. 32, p. 2431-2453 23 p.

  Research output: Contribution to journal › Article › peer-review

  • Sliced Inverse Regression 100%
  • Cholesky 94%
  • Penalization 81%
  • Central Subspace 72%
  • Matrix 62%
  1 Citation (Scopus)

• SurvBenchmark: comprehensive benchmarking study of survival analysis methods using both omics data and clinical data

  Zhang, Y., Wong, G., Mann, G., Muller, S. & Yang, J. Y. H., 2022, In: GigaScience. 11, p. 1-13 13 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Benchmarking 100%
  • Survival Analysis 89%
  • Datasets 73%
  • Machine Learning 34%
  • Statistical Models 34%
  11 Citations (Scopus)

  61 Downloads (Pure)

• The gut microbiome in Parkinson’s disease: A longitudinal study of the impacts on disease progression and the use of device-assisted therapies

  Lubomski, M., Xu, X., Holmes, A. J., Muller, S., Yang, J. Y. H., Davis, R. L. & Sue, C. M., 17 May 2022, In: Frontiers in Aging Neuroscience. 14, p. 1-24 24 p., 875261.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Gastrointestinal Microbiome 100%
  • Parkinson Disease 84%
  • Longitudinal Studies 84%
  • Disease Progression 80%
  • Equipment and Supplies 60%
  26 Citations (Scopus)

  62 Downloads (Pure)
• 2021

  Gut microbiota and nutritional profiles of Parkinson's disease patients

  Lubomski, M., Xu, X., Holmes, A., Muller, S., Yang, J., Sue, C. M. & Davis, R. L., Aug 2021, In: BMJ Neurology Open. 3, Suppl 1, p. A6-A7 2 p., 015.

  Research output: Contribution to journal › Meeting abstract

  Open Access

• mcvis: a new framework for collinearity discovery, diagnostic, and visualization

  Lin, C., Wang, K. & Muller, S., 2021, In: Journal of Computational and Graphical Statistics. 30, 1, p. 125-132 8 p.

  Research output: Contribution to journal › Article › peer-review

  • Collinearity 100%
  • Visualization 75%
  • Diagnostics 69%
  • Framework 39%
  • Resampling 17%
  6 Citations (Scopus)

• Prediction modeling-part 2: using machine learning strategies to improve transplantation outcomes

  Coorey, C. P., Sharma, A., Muller, S. & Yang, J. Y. H., Apr 2021, In: Kidney International. 99, 4, p. 817-823 7 p.

  Research output: Contribution to journal › Review article › peer-review

  • Machine Learning 100%
  • Transplantation 67%
  • Transplant Recipients 54%
  • Unsupervised Machine Learning 53%
  • Supervised Machine Learning 47%
  7 Citations (Scopus)

• Random effects misspecification can have severe consequences for random effects inference in linear mixed models

  Hui, F. K. C., Müller, S. & Welsh, A. H., Apr 2021, In: International Statistical Review. 89, 1, p. 186-206 21 p.

  Research output: Contribution to journal › Article › peer-review

  • Linear Mixed Model 100%
  • Mixed Model 99%
  • Misspecification 93%
  • Random Effects 83%
  • Inference 65%
  8 Citations (Scopus)

• svReg: structural varying-coefficient regression to differentiate how regional brain atrophy affects motor impairment for Huntington disease severity groups

  Kim, R., Müller, S. & Garcia, T. P., Aug 2021, In: Biometrical Journal. 63, 6, p. 1254-1271 18 p.

  Research output: Contribution to journal › Article › peer-review

  • Differentiate 100%
  • Varying Coefficients 98%
  • Regression Coefficient 96%
  • Brain 87%
  • Impairment 83%
  2 Citations (Scopus)

• The gut microbiome in Parkinson's disease: longitudinal insights into disease progression and the use of device-assisted therapies

  Lubomski, M., Xu, X., Holmes, A. J., Muller, S., Yang, J., Sue, C. M. & Davis, R. L., Aug 2021, In: BMJ Neurology Open. 3, Suppl 1, p. A14 1 p., 037.

  Research output: Contribution to journal › Meeting abstract

  Open Access
• 2020

  A personalised prediction model for allograft survival after kidney transplantation

  Zhang, Y., Yang, J., Wong, G. & Muller, S., Sept 2020, In: Transplantation. 104, S3, p. S41 1 p.

  Research output: Contribution to journal › Meeting abstract

• Identification of driven risk factors for HLA-DR in kidney transplantation

  Zhang, Y., Yang, J., Muller, S. & Wong, G., Sept 2020, In: Transplantation. 104, S3, p. S420 1 p., P-11.136.

  Research output: Contribution to journal › Meeting abstract

• LC-N2G: a local consistency approach for nutrigenomics data analysis

  Xu, X., Solon-Biet, S. M., Senior, A., Raubenheimer, D., Simpson, S. J., Fontana, L., Mueller, S. & Yang, J. Y. H., 2020, In: BMC Bioinformatics. 21, p. 1-14 14 p., 530.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Nutrigenomics 100%
  • Gene Expression 86%
  • Nutrients 85%
  • Gene expression 75%
  • Nutrient 73%
  2 Citations (Scopus)

  46 Downloads (Pure)

• mcvis: multi-collinearity visualization

  Wang, K., Lin, C. & Mueller, S., 2020

  Research output: Non-traditional research output › Software

  Open Access

• mcvis: multi-collinearity visualisation

  Wang, K. & Muller, S., 2020, In: Biometric Bulletin. 37, 3, p. 12-14 3 p.

  Research output: Contribution to journal › Article

• The LASSO on latent indices for regression modeling with ordinal categorical predictors

  Hui, F. K. C., Müller, S. & Welsh, A. H., Sept 2020, In: Computational Statistics and Data Analysis. 149, p. 1-13 13 p., 106951.

  Research output: Contribution to journal › Article › peer-review

  • Categorical 100%
  • Predictors 98%
  • Regression 81%
  • Modeling 69%
  • Health 38%
  2 Citations (Scopus)
• 2019

  A radiographic analysis of the abnormal hallux interphalangeus angle range: considerations for surgeons performing Akin osteotomies

  Nguyen, J. K., Sullivan, M., Alpuerto, B. B., Mueller, S. & Sly, N., 1 May 2019, In: Journal of Orthopaedic Surgery. 27, 2, p. 1-5 5 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Hallux 100%
  • Osteotomy 79%
  • Hallux Valgus 63%
  • Surgeons 55%
  • Bone and Bones 27%
  4 Citations (Scopus)

  166 Downloads (Pure)

• bcGST: an interactive bias-correction method to identify over-represented gene-sets in boutique arrays

  Wang, K. Y. X., Menzies, A. M., Silva, I. P., Wilmott, J. S., Yan, Y., Wongchenko, M., Kefford, R. F., Scolyer, R. A., Long, G. V., Tarr, G., Mueller, S. & Yang, J. Y. H., 15 Apr 2019, In: Bioinformatics. 35, 8, p. 1350-1357 8 p.

  Research output: Contribution to journal › Article › peer-review

  • Bias Correction 100%
  • Gene 76%
  • Genes 74%
  • Filtration 67%
  • Test Set 46%
  1 Citation (Scopus)

• Fast and approximate exhaustive variable selection for generalised linear models with APES

  Wang, K. Y. X., Tarr, G., Yang, J. Y. H. & Mueller, S., Dec 2019, In: Australian and New Zealand Journal of Statistics. 61, 4, p. 445-465 21 p.

  Research output: Contribution to journal › Article › peer-review

  • Variable Selection 100%
  • Exhaustive Search 73%
  • Generalized Linear Model 72%
  • Linear regression 15%
  • Linear Regression 14%
  4 Citations (Scopus)

• Melanoma Explorer: a web application to allow easy reanalysis of publicly available and clinically annotated melanoma omics data sets

  Strbenac, D., Wang, K., Wang, X., Dong, J., Mann, G. J., Mueller, S. & Yang, J. Y. H., Jun 2019, In: Melanoma Research. 29, 3, p. 342-344 3 p.

  Research output: Contribution to journal › Article › peer-review

  • Melanoma 100%
  • Datasets 95%
  • Biomarkers 39%
  • Muramidase 34%
  • Gene Expression 18%
  5 Citations (Scopus)

• Semiparametric regression using variational approximations

  Hui, F. K. C., You, C., Shang, H. L. & Müller, S., 2 Oct 2019, In: Journal of the American Statistical Association. 114, 528, p. 1765-1777 13 p.

  Research output: Contribution to journal › Article › peer-review

  • Semiparametric Regression 100%
  • Variational Approximation 95%
  • Approximation 55%
  • Generalized Additive Models 38%
  • Framework 38%
  11 Citations (Scopus)

• Testing random effects in linear mixed models: another look at the F-test (with discussion)

  Hui, F. K. C., Müller, S. & Welsh, A. H., Mar 2019, In: Australian and New Zealand Journal of Statistics. 61, 1, p. 61-84 24 p.

  Research output: Contribution to journal › Article › peer-review

  • Linear Mixed Model 100%
  • Mixed Model 99%
  • F Test 97%
  • Random Effects 83%
  • Testing 66%
  9 Citations (Scopus)
• 2018

  mplot: graphical model stability and variable selection procedures

  Tarr, G., Mueller, S. & Welsh, A. H., 2018

  Research output: Non-traditional research output › Software

  Open Access

• mplot: an R package for graphical model stability and variable selection procedures

  Tarr, G., Müller, S. & Welsh, A. H., Feb 2018, In: Journal of Statistical Software. 83, 9, p. 1-28 28 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Variable Selection 100%
  • Graphical Models 76%
  • Selection Procedures 61%
  • Graphical User Interface 30%
  • Bootstrap 26%
  9 Citations (Scopus)

  48 Downloads (Pure)

• Sparse pairwise likelihood estimation for multivariate longitudinal mixed models

  Hui, F. K. C., Müller, S. & Welsh, A. H., 2018, In: Journal of the American Statistical Association. 113, 524, p. 1759-1769 11 p.

  Research output: Contribution to journal › Article › peer-review

  • Pairwise Likelihood 100%
  • Likelihood Estimation 95%
  • Mixed Model 81%
  • Multivariate Models 44%
  • Shrinkage Estimator 39%
  9 Citations (Scopus)
• 2017

  2nd special issue on robust analysis of complex data

  Mueller, S., Boente, G., Croux, C., Romo, J. & Van Aelst, S., Sept 2017, In: Computational Statistics and Data Analysis. 113, p. 395-397 3 p.

  Research output: Contribution to journal › Editorial › peer-review

• A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types

  Patrick, E., Schramm, S-J., Ormerod, J. T., Scolyer, R. A., Mann, G. J., Mueller, S. & Yang, J. Y. H., 2017, In: Oncotarget. 8, 2, p. 2807-2815 9 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Biomarkers 100%
  • Neoplasms 49%
  • Survival 18%
  • Genetic Variation 16%
  • Colonic Neoplasms 15%
  9 Citations (Scopus)

  32 Downloads (Pure)

• A variational bayes approach to variable selection

  Ormerod, J. T., You, C. & Müller, S., 2017, In: Electronic Journal of Statistics. 11, 2, p. 3549-3594 46 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Variable Selection 100%
  • Variational Bayes 83%
  • Regression Coefficient 37%
  • Force Method 27%
  • Parameter Tuning 22%
  34 Citations (Scopus)

  43 Downloads (Pure)

• Hierarchical selection of fixed and random effects in generalized linear mixed models

  Hui, F. K. C., Müller, S. & Welsh, A. H., Apr 2017, In: Statistica Sinica. 27, 2, p. 501-518 18 p.

  Research output: Contribution to journal › Article › peer-review

  • Generalized Linear Mixed Model 100%
  • Fixed Effects 76%
  • Random Effects 68%
  • Composite 40%
  • Mixed Model 34%
  22 Citations (Scopus)

• Joint selection in mixed models using regularized PQL

  Hui, F. K. C., Müller, S. & Welsh, A. H., 2017, In: Journal of the American Statistical Association. 112, 519, p. 1323-1333 11 p.

  Research output: Contribution to journal › Article › peer-review

  • Penalized Quasi-likelihood 100%
  • Quasi-likelihood 95%
  • Mixed Model 81%
  • Random Effects 65%
  • Number of Clusters 32%
  42 Citations (Scopus)
• 2016

  Cox regression with exclusion frequency-based weights to identify neuroimaging markers relevant to huntington's disease onset

  Garcia, T. P. & Müller, S., Dec 2016, In: Annals of Applied Statistics. 10, 4, p. 2130-2156 27 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Neuroimaging 100%
  • Cox Regression 95%
  • Predictors 74%
  • Exclusion 71%
  • Genomics 36%
  3 Citations (Scopus)