Publication Search Results
Exact matches for:
- Author = Muller S [web profile page]
1.
Su P, Tarr G, Muller S
Peng Su, Garth Tarr, Samuel Muller:
Robust variable selection under cellwise contamination,
Journal of Statistical Computation and Simulation,
94
(2024),
no. 6,
1371–1387.
2.
Zhang Y, Muller S
Yunwei Zhang and Samuel Muller:
Robust variable selection methods with Cox model—a selective practical benchmark study,
Briefings in Bioinformatics,
25
(2024),
no. 6,
bbae508 (9 pages).
3.
Su P, Tarr G, Muller S, Wang S
Peng Su, Garth Tarr, Samuel Muller, Suojin Wang:
CR-Lasso: Robust cellwise regularized sparse regression,
Computational Statistics and Data Analysis,
197
(2024),
Article no. 107971 (14 pages).
4.
Moka S, Liquet B, Zhu H, Muller S
Sarat Moka, Benoit Liquet, Houying Zhu, Samuel Muller:
COMBSS: best subset selection via continuous optimization,
Statistics and Computing,
34
(2024),
no. 2,
34–75.
5.
Nghiem LH, Hui FKC, Muller S, Welsh AH
Linh H Nghiem, Francis K C Hui, Samuel Muller, A H Welsh:
Likelihood-based surrogate dimension reduction,
Statistics and Computing,
34
(2024),
no. 1,
Article number 51 (15 pages).
6.
Zhang Y, Hu A, Lin Y, Cao Y, Muller S, Wong G, Yang YH
Yunwei Zhang, Anne Hu, Yingxin Lin, Yue Cao, Samuel Muller, Germaine Wong & Jean Yee Hwa Yang:
simKAP: simulation framework for the kidney allocation process with decision making model,
Scientific Reports,
13
(2023),
Article number 16367.
7.
Farhood H, Muller S, Beheshti A
Helia Farhood, Samuel Muller and Amin Beheshti:
Surface Area Estimation Using 3D Point Clouds and Delaunay Triangulation,
Lecture Notes in Networks and Systems,
721
(2023),
28–39.
8.
Hui FKC, Muller S, Welsh AH
Francis K C Hui, Samuel Muller, A H Welsh:
GEE-Assisted Variable Selection for Latent Variable Models with Multivariate Binary Data,
Journal of the American Statistical Association,
118
(2023),
no. 542,
1252–1263.
9.
Nghiem LH, Hui FKC, Muller S, Welsh AH
Linh H Nghiem, FKC Hui, Samuel Müller, AH Welsh:
creening methods for linear errors-in-variables models in high dimensions,
Biometrics,
00
(2022),
1–14.
10.
Nghiem LH, Hui FKC, Muller S, Welsh AH
Linh H Nghiem, FKC Hui, Samuel Müller, AH Welsh:
Estimation of graphical models for skew continuous data.,
Scandinavian Journal of Statistics. Theory and Applications,
49
(2022),
no. 4,
1811– 1841.
11.
Nghiem LH, Hui FKC, Muller S, Welsh AH
Linh H Nghiem, Francis K. C. Hui, Samuel Muller and A H Welsh:
Sparse sliced inverse regression via Cholesky matrix penalization,
Statistica Sinica,
32
(2022),
no. Special Online Issue,
2431–2453.
12.
Wang KYX, Pupo GM, Tembe V, Patrick E, Strbenac D, Schramm SJ, Thompson JF, Scolyer RA, Muller S, Tarr G, Mann GJ, Yang YH
Kevin Y X Wang, Gulietta M Pupo, Varsha Tembe, Ellis Patrick, Dario Strbenac, Sarah-Jane Schramm, John F Thompson, Richard A Scolyer, Samuel Muller, Garth Tarr, Graham J Mann and Jean Y H Yang:
Cross-Platform Omics Prediction procedure: a statistical machine learning framework for wider implementation of precision medicine,
npj Digital Medicine,
5 (open Access)
(2022),
no. 1,
Article 85.
13.
Lin C, Wang KYX, Muller S
Chen Lin, Kevin Wang and Samuel Mueller:
MCVIS: A New Framework for Collinearity Discovery, Diagnostic, and Visualization,
Journal of Computational and Graphical Statistics,
30
(2021),
no. 1,
125–132.
14.
Xu X, Solon‑Biet SM, Senior AM, Raubenheimer D, Simpson SJ, Fontana L, Muller S, Yang YH
Xiangnan Xu, Samantha M Solon‑Biet, Alistair Senior, David Raubenheimer, Stephen J Simpson, Luigi Fontana, Samuel Mueller and Jean Y H Yang:
LC-N2G: a local consistency approach for nutrigenomics data analysis,
BMC Bioinformatics,
21
(2020),
no. Open Access,
Article 530.
15.
Hui FKC, Muller S, Welsh AH
FKC Hui, S Mueller, AH Welsh:
The LASSO on latent indices for regression modeling with ordinal categorical predictors,
Computational Statistics and Data Analysis,
149
(2020),
1–13.
16.
Hui FKC, You C, Shang HL, Muller S
FKC Hui, C You, HL Shang, S Mueller:
Semiparametric Regression Using Variational Approximations,
Journal of the American Statistical Association,
114
(2019),
no. 528,
1765–1777.
MR4047298
17.
Wang KYX, Tarr G, Yang YH, Muller S
Kevin YX Wang, Garth Tarr, Jean YH Yang and Samuel Mueller:
Fast and approximate exhaustive variable selection for generalised linear models with APES,
Australian and New Zealand Journal of Statistics,
61
(2019),
no. 4,
445–465.
MR4052183
18.
Wang KYX, Menzies AM, Silva IP, Wilmott JS, Yan Y, Wongchenko M, Kefford RF, Scolyer RA, Long GV, Tarr G, Muller S, Yang YH
Kevin YX Wang, Alexander M Menzies, Ines P Silva, James S Wilmott, Yibing Yan, Matthew Wongchenko, Richard F Kefford, Richard A Scolyer, Georgina V Long, Garth Tarr, Samuel Mueller and Jean YH Yang:
bcGST – an interactive bias-correction method to identify over-represented gene-sets in boutique arrays,
Bioinformatics,
35
(2019),
no. 8,
1350–1357.
19.
Nguyen JK, Sullivan M, Alpuerto BB II, Muller S, Sly N
Jacqueline K Nguyen, Martin Sullivan, Bernardino B Alpuerto II, Samuel Mueller, Nicole Sly:
A radiographic analysis of the abnormal hallux interphalangeus angle range: Considerations for surgeons performing Akin osteotomies,
Journal of Orthopaedic Surgery,
27
(2019),
no. 2,
1–5.
20.
Hui FKC, Muller S, Welsh AH
FKC Hui, S Müller, AH Welsh:
Testing random effects in linear mixed models: another look at the F-test (with discussion),
Australian & New Zealand Journal of Statistics,
61
(2019),
no. 1,
61–84.
MR3942093
21.
Hui FKC, Muller S, Welsh AH
FKC Hui, S Müller, AH Welsh:
Sparse pairwise likelihood estimation for multivariate longitudinal mixed models,
Journal of the American Statistical Association,
113
(2018),
no. 524,
1759–1769.
22.
Tarr G, Muller S, Welsh AH
G Tarr, S Müller, AH Welsh:
mplot: An R Package for Graphical Model Stability and Variable Selection Procedures,
Journal of Statistical Software,
83
(2018),
no. 9,
1–28.
23.
Hui FKC, Muller S, Welsh AH
FKC Hui, S Müller, AH Welsh:
Joint selection in mixed models using regularized PQL,
Journal of the American Statistical Association,
112
(2017),
no. 519,
1323–1333.
24.
Ormerod JT, You C, Muller S
JT Ormerod, C You, S Müller:
A variational Bayes approach to variable selection,
Electronic Journal of Statistics,
11
(2017),
3549–3594.
25.
Muller S, Boente G, Croux C, Romo J, Van Aelst S
S Mueller, G Boente, C Croux, J Romo, S Van Aelst:
2nd special issue on robust analysis of complex data,
Computational Statistics and Data Analysis,
113
(2017),
395–397.
26.
Hui FKC, Muller S, Welsh AH
FKC Hui, S Müller, AH Welsh:
Hierarchical selection of fixed and random effects in generalized linear mixed models,
Statistica Sinica,
27
(2017),
501–518.
27.
Patrick E, Schramm S-J, Ormerod JT, Scolyer RA, Mann GJ, Muller S, Yang YH
E Patrick, S-J Schramm, JT Ormerod, RA Scolyer, GJ Mann, S Mueller, YH Yang:
A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types,
Oncotarget,
8
(2017),
no. 2,
2807–2815.
28.
Garcia TP, Muller S
TP Garcia, S Müller:
Cox regression with exclusion frequency-based weights to identify neuroimaging markers relevant to Huntington's disease onset,
The Annals of Applied Statistics,
10
(2016),
no. 4,
2130–2156.
MR3592051
29.
Murray K, Muller S, Turlach BA
K Murray, S Müller, BA Turlach:
Fast and flexible methods for monotone polynomial fitting,
Journal of Statistical Computation and Simulation,
86
(2016),
no. 15,
2946–2966.
MR3523154
30.
Jayawardana K, Schramm SJ, Tembe V, Muller S, Thompson JF, Scolyer RA, Mann GJ, Yang YH
K Jayawardana, S-J Schramm, V Tembe, S Mueller, JF Thompson, RA Scolyer, GJ Mann, J Yang:
Identification, Review, and Systematic Cross-Validation of microRNA Prognostic Signatures in Metastatic Melanoma,
Journal of Investigative Dermatology,
136
(2016),
245–254.
31.
You C, Muller S, Ormerod JT
C You, S Müller, J Ormerod:
On generalized degrees of freedom with application in linear mixed models selection,
Statistics and Computing,
26
(2016),
no. 1,
199–210.
MR3439368
32.
Tarr G, Muller S, Weber NC
G Tarr, S Müller, NC Weber:
Robust Estimation of Precision Matrices under Cellwise Contamination,
Computational Statistics and Data Analysis,
93
(2016),
404–420.
MR3406222
33.
Patrick E, Buckley MJ, Muller S, Lin DM, Yang YH
E Patrick, M Buckley, S Müller, DM Lin, YH Yang:
Inferring data-specific micro-RNA function through the joint ranking of micro-RNA and pathways from small sample miRNA-Seq and mRNA-Seq data,
Bioinformatics,
31
(2015),
no. 17,
2822–2828.
34.
Kaeser SA, Froelicher J, Li Q, Muller S, Metzger U, Castiglione M, Laffer UT, Maurer CA
SA Kaeser, J Froelicher, Q Li, S Müller, U Metzger, M Castiglione, UT Laffer, CA Maurer:
Adenocarcinomas of the upper third of the rectum and the rectosigmoid junction seem to have similar prognosis as colon cancers even without radiotherapy, SAKK 40/87,
Langenbeck's Archives of Surgery,
400
(2015),
675–682.
35.
Muller S, Tarr G
Samuel Müller, Garth Tarr:
Much more than \(U\)-statistics: A symposium to celebrate Neville C. Weber,
SSAI newsletter,
151
(2015),
10–12.
36.
Tarr G, Weber NC, Muller S
G Tarr, NC Weber, S Müller:
The difference of symmetric quantiles under long range dependence,
Statistics and Probability Letters,
98
(2015),
144–150.
37.
Jayawardana K, Schramm SJ, Haydu L, Thompson JF, Scolyer RA, Mann GJ, Muller S, Yang YH
Kaushala Jayawardana, Sarah-Jane Schramm, Lauren Haydu, John F Thompson, Richard A Scolyer, Graham J Mann, Samuel Müller and Jean Yee Hwa Yang:
Determination of prognosis in metastatic melanoma through integration of clinico-pathologic, mutation, mRNA, microRNA, and protein information,
International Journal of Cancer,
136
(2015),
no. 4,
863–874.
38.
Garcia TP, Muller S
Tanya P. Garcia and Samuel Müller:
Influence of Measures of Significance based Weights in the Weighted Lasso,
Journal of the Indian Society of Agricultural Statistics,
68
(2014),
no. 2,
131–144.
39.
You C, Ormerod JT, Muller S
C You, JT Ormerod, S Müller:
On Variational Bayes Estimation and Variational Bayes Information Criteria for Linear Regression Models,
Australian and New Zealand Journal of Statistics,
56
(2014),
73–87.
40.
Garcia TP, Muller S, Carroll RJ, Walzem RL
TP Garcia, S Müller, RJ Carroll, RL Walzem:
Identification of important regressor groups, subgroups and individuals via regularization methods: application to gut microbiome data,
Bioinformatics,
30
(2014),
no. 6,
831–837.
41.
Murray K, Heritier S, Muller S
Murray K, Heritier S, Müller S:
Graphical tools for model selection in generalized linear models,
Statistics in Medicine,
32
(2013),
4438–4451.
42.
Murray K, Muller S, Turlach BA
Murray K, Müller S, Turlach BA:
Revisiting fitting monotone polynomials to data,
Computational Statistics,
28
(2013),
1989–2005.
43.
You C, Muller S, Ormerod JT
You C, Müller S, Ormerod JT:
On Generalized Degrees of Freedom and their Application in Linear Mixed Model Selection,
Proceedings,
59th ISI World Statistics Congress,
(2013),
1–5.
44.
Jayawardana K, Muller S, Schramm SJ, Mann GJ, Yang YH
Kaushala Jayawardana, Samuel Müller, Sarah-Jane Schramm, Graham J Mann and Jean Yang:
Vertical Data Integration for Melanoma Prognosis,
Proceedings,
59th ISI World Statistics Congress,
(2013),
1–6.
45.
Muller S, Garcia TP, Carroll RJ
Samuel Müller, Tanya P. Garcia, Raymond J Carroll:
Informative Measures of Significance for Constructing Intelligent Feature Weights,
Proceedings,
59th ISI World Statistics Congress,
(2013),
1–6.
46.
Sampson JN, Chatterjee N, Carroll RJ, Muller S
Joshua N. Sampson, Nilanjan Chatterjee, Raymond J. Carroll, Samuel Müller:
Controlling the local false discovery rate in the adaptive Lasso,
Biostatistics,
14
(2013),
no. 4,
653–666.
47.
Garcia TP, Muller S, Carroll RJ, Dunn TN, Thomas AP, Adams SH, Pillai SD, Walzem RL
Tanya P. Garcia, Samuel Müller, Raymond J. Carroll, Tamara N. Dunn, Anthony P. Thomas, Sean H. Adams, Suresh D. Pillai, Rosemary L. Walzem:
Structured variable selection with \(q\)-values,
Biostatistics,
14
(2013),
no. 4,
695–707.
48.
Muller S, Scealy JL, Welsh AH
Samuel Müller, J. L. Scealy and A. H. Welsh:
Model selection in linear mixed models,
Statistical Science,
28
(2013),
no. 2,
135–167.
49.
Oates J, Casikar I, Campain AE, Muller S, Yang YH, Reid S, Condous G
Jennifer Oates, Ishwari Casikar, Anna Campain, Samuel Müller, Jean Yang, Shannon Reid, George Condous:
A prediction model for viability at the end of the first trimester after a single early pregnancy evaluation,
Australian and New Zealand Journal of Obstetrics and Gynaecology,
53
(2013),
51–57.
50.
Firmin L, Muller S, Rösler KM
Lea Firmin, Samuel Müller, Kai M. Rösler:
The latency distribution of motor evoked potentials in patients with multiple sclerosis,
Clinical Neurophysiology,
123
(2012),
2414–2421.
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