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pro vyhledávání: '"Dambon, Jakob A"'
Gaussian processes (GPs) are well-known tools for modeling dependent data with applications in spatial statistics, time series analysis, or econometrics. In this article, we present the R package varycoef that implements estimation, prediction, and v
Externí odkaz:
http://arxiv.org/abs/2106.02364
Spatially varying coefficient (SVC) models are a type of regression model for spatial data where covariate effects vary over space. If there are several covariates, a natural question is which covariates have a spatially varying effect and which not.
Externí odkaz:
http://arxiv.org/abs/2101.01932
In regression models for spatial data, it is often assumed that the marginal effects of covariates on the response are constant over space. In practice, this assumption might often be questionable. In this article, we show how a Gaussian process-base
Externí odkaz:
http://arxiv.org/abs/2001.08089
Publikováno v:
In Spatial Statistics March 2021 41
Autor:
Dambon, Jakob A.1,2,3 (AUTHOR) jakob.dambon@math.uzh.ch, Sigrist, Fabio2 (AUTHOR), Furrer, Reinhard1,4 (AUTHOR)
Publikováno v:
International Journal of Geographical Information Science. Dec2022, Vol. 36 Issue 12, p2525-2548. 24p.
Akademický článek
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Autor:
Dambon, Jakob A.1,2 (AUTHOR) jakob.dambon@gmail.com, Fahrländer, Stefan S.3 (AUTHOR), Karlen, Saira3 (AUTHOR), Lehner, Manuel3 (AUTHOR), Schlesinger, Jaron3 (AUTHOR), Sigrist, Fabio2 (AUTHOR), Zimmermann, Anna3 (AUTHOR)
Publikováno v:
Swiss Journal of Economics & Statistics. 1/6/2022, Vol. 158 Issue 1, p1-14. 14p.