Multivariate density estimation for interval‐censored data with application to a forest fire modelling problem | Zendy

Braun W. J. | Zendy; Stafford J. E. | Zendy

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Multivariate density estimation for interval‐censored data with application to a forest fire modelling problem

Author(s) -

Braun W. J.,

Stafford J. E.

Publication year - 2016

Publication title -

environmetrics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.68

H-Index - 58

eISSN - 1099-095X

pISSN - 1180-4009

DOI - 10.1002/env.2396

Subject(s) - multivariate statistics , estimator , statistics , density estimation , interval estimation , mathematics , interval (graph theory) , estimation , context (archaeology) , econometrics , confidence interval , geography , engineering , systems engineering , archaeology , combinatorics

Local likelihood‐based density estimation methods are developed for multivariate interval‐censored data. An extension of the Nadaraya–Watson local regression estimator to the interval‐censored data context arises in a natural way. The conditional density estimation scheme is used to study the holdover distribution of lightning‐caused wildfire ignitions in Northern Ontario. Copyright © 2016 John Wiley & Sons, Ltd.

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