ORCID Profile
0000-0002-6319-2332
Current Organisations
University of Zurich
,
Universitat Zurich
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Publisher: Elsevier BV
Date: 02-2017
DOI: 10.1016/J.VETPAR.2016.12.007
Abstract: The prevalence of anthelmintic resistance has increased in recent years, as a result of the extensive use of anthelmintic drugs to reduce the infection of parasitic worms in livestock. In order to detect the resistance, the number of parasite eggs in animal faeces is counted. Typically a subs le of the diluted faeces is examined, and the mean egg counts from both untreated and treated animals are compared. However, the conventional method ignores the variabilities introduced by the counting process and by different infection levels across animals. In addition, there can be extra zero counts, which arise as a result of the unexposed animals in an infected population or animals. In this paper, we propose the zero-inflated Bayesian hierarchical models to estimate the reduction in faecal egg counts. The simulation study compares the Bayesian models with the conventional faecal egg count reduction test and other methods such as bootstrap and quasi-Poisson regression. The results show the Bayesian models are more robust and they perform well in terms of both the bias and the coverage. We further illustrate the advantages of our proposed model using a case study about the anthelmintic resistance in Swedish sheep flocks.
Publisher: Cold Spring Harbor Laboratory
Date: 10-02-2021
DOI: 10.1101/2021.02.09.430391
Abstract: Ecosystem heterogeneity has been widely recognized as a key ecological feature, influencing several ecological functions, since it is strictly related to several ecological functions like ersity patterns and change, metapopulation dynamics, population connectivity, or gene flow. In this paper, we present a new R package - raster - to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The raster package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open source algorithms.
Publisher: Elsevier BV
Date: 12-2018
Publisher: Wiley
Date: 15-03-2021
DOI: 10.1111/GEB.13270
Publisher: Wiley
Date: 03-05-2021
Abstract: Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, ersity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package— raster —to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The raster package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open‐source algorithms.
Publisher: Wiley
Date: 2019
DOI: 10.1002/STA4.216
Publisher: Elsevier BV
Date: 03-2018
Publisher: Institute of Mathematical Statistics
Date: 03-2011
DOI: 10.1214/10-AOAS369
Publisher: Springer Science and Business Media LLC
Date: 14-12-2018
Location: United States of America
No related grants have been discovered for Reinhard Furrer.