Matthew R Schofield
statistician in New Zealand
Facts
14 properties- Instance of
- human
- Occupation
- researcher
- Position held
- associate professor[2]
- Educated at
- University of Otago, University of Otago
- Doctoral advisor
- Richard J Barker[4]
- Doctoral student
- John B. Holmes, Paula Bran, Sree Soundarya Tejaswi Karamcheti, Timothy P Bilton, Nicholas W Daudt, Leah Marie Crowe[6][7][8][9][10][11]
- Academic degree
- Doctor of Philosophy[12]
- Academic thesis
- Hierarchical capture-recapture models[15]
- Maintained by WikiProject
- WikiProject Mathematics[17]
- On focus list of Wikimedia project
- NZThesisProject[16]
🏷️ Also known as
en Matthew R Schofield
en Matthew Ryan Schofield
en Matthew Schofield
en Matt R Schofield
en Matt Schofield
en M R Schofield
it Matthew R. Schofield
🔖 Identifiers · 7
- ORCID iD
- 0000-0003-1481-2766
- OpenAlex ID
- A5033690997
- Dimensions author ID
- 01371312715.77
- MR Author ID
- 831428
- Mathematics Genealogy Project ID
- 151435
- Scopus author ID
- 23029094500
- ZbMATH author ID
- schofield.matthew-r
🔗 Connections
Author of 8
50-Year-Old Curiosities: Ancillarity and Inference in Capture–Recapture Models,
A Model-Based Approach to Climate Reconstruction Using Tree-Ring Data,
Bayesian Modelling of Marked Point Processes with Incomplete Records: Volcanic Eruptions,
Continuous-time Capture–Recapture in Closed Populations,
Convolutional Neural Network for Malware Classification Based on API Call Sequence,
On the Reliability of N-mixture Models for Count Data,
On the robustness of latent class models for diagnostic testing with no gold standard,
On the robustness of N‐mixture models
← Authored by 8
50-Year-Old Curiosities: Ancillarity and Inference in Capture–Recapture Models,
A Model-Based Approach to Climate Reconstruction Using Tree-Ring Data,
Bayesian Modelling of Marked Point Processes with Incomplete Records: Volcanic Eruptions,
Continuous-time Capture–Recapture in Closed Populations,
Convolutional Neural Network for Malware Classification Based on API Call Sequence,
On the Reliability of N-mixture Models for Count Data,
On the robustness of latent class models for diagnostic testing with no gold standard,
On the robustness of N‐mixture models
Affiliated with 2
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