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Scopus Author ID: 56386083500

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Employment (1)

University of Queensland: Brisbane, Queensland, AU

2018-06 to present | Postdoctoral Researcher (School of Mathematics and Physics)
Employment
Source: Self-asserted source
Daniel Ahfock

Education and qualifications (1)

University of Cambridge: Cambridge, Cambridgeshire, GB

2014-09 to 2018-09 | PhD (MRC Biostatistics Unit)
Education
Source: Self-asserted source
Daniel Ahfock

Works (13)

Semi-Supervised Learning of Classifiers from a Statistical Perspective: A Brief Review

Econometrics and Statistics
2023-04 | Journal article
DOI: 10.1016/j.ecosta.2022.03.007
Contributors: Daniel Ahfock; Geoffrey J. McLachlan
Source: check_circle
Crossref

On randomized sketching algorithms and the Tracy–Widom law

Statistics and Computing
2023-02 | Journal article
DOI: 10.1007/s11222-022-10148-5
Contributors: Daniel Ahfock; William J. Astle; Sylvia Richardson
Source: check_circle
Crossref

Statistical file-matching of non-Gaussian data: A game theoretic approach

Computational Statistics & Data Analysis
2022-04 | Journal article
DOI: 10.1016/j.csda.2021.107387
Contributors: Daniel Ahfock; Saumyadipta Pyne; Geoffrey J. McLachlan
Source: check_circle
Crossref

Estimation of Classification Rules From Partially Classified Data

Data Analysis and Rationality in a Complex World
2021 | Conference paper
DOI: 10.1007/978-3-030-60104-1_17
Part of ISBN: 9783030601034
Part of ISBN: 9783030601041
Part of ISSN: 1431-8814
Part of ISSN: 2198-3321
Source: Self-asserted source
Daniel Ahfock

Data fusion using factor analysis and low-rank matrix completion

Statistics and Computing
2021-09 | Journal article
DOI: 10.1007/s11222-021-10033-7
Contributors: Daniel Ahfock; Saumyadipta Pyne; Geoffrey J. McLachlan
Source: check_circle
Crossref

Harmless label noise and informative soft-labels in supervised classification

Computational Statistics & Data Analysis
2021-09 | Journal article
DOI: 10.1016/j.csda.2021.107253
Contributors: Daniel Ahfock; Geoffrey J. McLachlan
Source: check_circle
Crossref

Statistical properties of sketching algorithms

Biometrika
2021-05-15 | Journal article
DOI: 10.1093/biomet/asaa062
Part of ISSN: 0006-3444
Part of ISSN: 1464-3510
Source: Self-asserted source
Daniel Ahfock

An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified

Statistics and Computing
2020-11 | Journal article
DOI: 10.1007/s11222-020-09971-5
Part of ISSN: 0960-3174
Part of ISSN: 1573-1375
Source: Self-asserted source
Daniel Ahfock

Climate regime shift detection with a trans‐dimensional, sequential Monte Carlo, variational Bayes method

Australian & New Zealand Journal of Statistics
2019-06 | Journal article
DOI: 10.1111/anzs.12265
Part of ISSN: 1369-1473
Part of ISSN: 1467-842X
Source: Self-asserted source
Daniel Ahfock

Partial identification in the statistical matching problem

Computational Statistics and Data Analysis
2016 | Journal article
DOI: 10.1016/j.csda.2016.06.005
EID:

2-s2.0-84978224527
Contributors: Ahfock, D.; Pyne, S.; Lee, S.X.; McLachlan, G.J.
Source: Self-asserted source
Daniel Ahfock via Scopus - Elsevier

Characterizing Uncertainty in High-Density Maps from Multiparental Populations

Genetics
2014 | Journal article
DOI: 10.1534/genetics.114.167577
EID:

2-s2.0-84907974409
Contributors: Ahfock, D.; Wood, I.; Stephen, S.; Cavanagh, C.R.; Huang, B.E.
Source: Self-asserted source
Daniel Ahfock via Scopus - Elsevier

Weighted Gibbs sampling for mixture modelling of massive datasets via coresets

Stat
2014 | Journal article
DOI: 10.1002/sta4.62
EID:

2-s2.0-84942327777
Contributors: Mcgrory, C.A.; Ahfock, D.C.; Horsley, J.A.; Alston, C.L.
Source: Self-asserted source
Daniel Ahfock via Scopus - Elsevier

Transdimensional sequential Monte Carlo for hidden Markov models using variational Bayes - SMCVB

Annals of Computer Science and Information Systems
2014-09-29 | Conference paper
DOI: 10.15439/2014f483
Part of ISSN: 2300-5963
Source: Self-asserted source
Daniel Ahfock

Peer review (11 reviews for 2 publications/grants)

Review activity for Advances in data analysis and classification. (3)
Review activity for Statistics and Computing (8)
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