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Selection: Warton:DI [3 articles] 

Publications by author Warton:DI.
 

Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure

  
Ecography, Vol. 40, No. 8. (1 August 2017), pp. 913-929, https://doi.org/10.1111/ecog.02881

Abstract

Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor performance of uncorrected (random) cross-validation, noted often by modellers, are dependence structures in the data that persist as dependence structures in model residuals, violating the assumption of independence. Even more concerning, because often overlooked, is that structured data also ...

 

Point process models for presence-only analysis

  
Methods in Ecology and Evolution, Vol. 6, No. 4. (1 April 2015), pp. 366-379, https://doi.org/10.1111/2041-210x.12352

Abstract

[::] Presence-only data are widely used for species distribution modelling, and point process regression models are a flexible tool that has considerable potential for this problem, when data arise as point events. [::] In this paper, we review point process models, some of their advantages and some common methods of fitting them to presence-only data. [::] Advantages include (and are not limited to) clarification of what the response variable is that is modelled; a framework for choosing the number and location of quadrature ...

 

Poisson point process models solve the “pseudo-absence problem” for presence-only data in ecology

  
The Annals of Applied Statistics, Vol. 4, No. 3. (September 2010), pp. 1383-1402, https://doi.org/10.1214/10-aoas331

Abstract

Presence-only data, point locations where a species has been recorded as being present, are often used in modeling the distribution of a species as a function of a set of explanatory variables—whether to map species occurrence, to understand its association with the environment, or to predict its response to environmental change. Currently, ecologists most commonly analyze presence-only data by adding randomly chosen “pseudo-absences” to the data such that it can be analyzed using logistic regression, an approach which has weaknesses in ...

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Integrated Natural Resources Modelling and Management - Meta-information Database. http://mfkp.org/INRMM/author/Warton:DI

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