Jacob van Etten
5 packages on CRAN
Toolkit for climate variability indices for ecological modelling. The indices produced here can be used as explanatory variables for crop modelling, trends in climate change and to assess the interactions of plants and animals with the environment.
API client for 'ClimMob', an open source software for crowdsourcing citizen science in agriculture under the 'tricot' method <https://climmob.net/climmob3/>. Developed by van Etten et al. (2019) <doi:10.1017/S0014479716000739>, it turns the research paradigm on its head; instead of a few researchers designing complicated trials to compare several technologies in search of the best solutions, it enables many farmers to carry out reasonably simple experiments that taken together can offer even more information. 'ClimMobTools' enables project managers to deep explore and analyse their 'ClimMob' data in R.
Calculate distances and routes on geographic grids.
Functions to prepare rankings data and fit the Plackett-Luce model jointly attributed to Plackett (1975) <doi:10.2307/2346567> and Luce (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized to accommodate ties of any order in the ranking. Partial rankings, in which only a subset of items are ranked in each ranking, are also accommodated in the implementation. Disconnected/weakly connected networks implied by the rankings may be handled by adding pseudo-rankings with a hypothetical item. Optionally, a multivariate normal prior may be set on the log-worth parameters and ranker reliabilities may be incorporated as proposed by Raman and Joachims (2014) <doi:10.1145/2623330.2623654>. Maximum a posteriori estimation is used when priors are set. Methods are provided to estimate standard errors or quasi-standard errors for inference as well as to fit Plackett-Luce trees. See the package website or vignette for further details.
Reading, writing, manipulating, analyzing and modeling of gridded spatial data. The package implements basic and high-level functions. Processing of very large files is supported. There is a also support for vector data operations such as intersections. See the manual and tutorials on <https://rspatial.org/> to get started.