Data-driven chimney fire risk prediction using machine learning and point process tools
Author:
Affiliation:
1. Department of Applied Mathematics, University of Twente
2. Stochastics, Centrum Wiskunde & Informatica
3. Innovation Research & Technology, Thales Nederland B.V
4. Sector Strategy & Support, Brandweer Twente
Publisher
Institute of Mathematical Statistics
Subject
Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability
Reference57 articles.
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3. BADDELEY, A. and TURNER, R. (2000). Practical maximum pseudolikelihood for spatial point patterns (with discussion). Aust. N. Z. J. Stat. 42 283–322.
4. CHOIRUDDIN, A., COEURJOLLY, J.-F. and WAAGEPETERSEN, R. (2021). Information criteria for inhomogeneous spatial point processes. Aust. N. Z. J. Stat. 63 119–143.
5. GODAMBE, V. P. and HEYDE, C. C. (1987). Quasi-likelihood and optimal estimation. Int. Stat. Rev. 55 231–244.
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1. M.N.M. van Lieshout and C. Lu’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’;Journal of the Royal Statistical Society Series B: Statistical Methodology;2024-01-07
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