Zobrazeno 1 - 10
of 199
pro vyhledávání: '"Achim, Zeileis"'
Publikováno v:
Journal of Statistical Software, Vol 100, Pp 1-53 (2021)
Over the last decades, the challenges in applied regression and in predictive modeling have been changing considerably: (1) More flexible regression model specifications are needed as data sizes and available information are steadily increasing, cons
Externí odkaz:
https://doaj.org/article/f73117aebc464fbf8efc06d34ba7ed46
Autor:
Achim Zeileis, Jason C. Fisher, Kurt Hornik, Ross Ihaka, Claire D. McWhite, Paul Murrell, Reto Stauffer, Claus O. Wilke
Publikováno v:
Journal of Statistical Software, Vol 96, Iss 1, Pp 1-49 (2020)
The R package colorspace provides a flexible toolbox for selecting individual colors or color palettes, manipulating these colors, and employing them in statistical graphics and data visualizations. In particular, the package provides a broad range o
Externí odkaz:
https://doaj.org/article/b70547f35265413ab3d0b8d363c81d4f
Publikováno v:
Journal of Statistical Software, Vol 95, Iss 1, Pp 1-36 (2020)
Clustered covariances or clustered standard errors are very widely used to account for correlated or clustered data, especially in economics, political sciences, and other social sciences. They are employed to adjust the inference following estimatio
Externí odkaz:
https://doaj.org/article/725153453d124f00ac30f225ed64885c
Publikováno v:
Journal of Statistical Software, Vol 93, Iss 1, Pp 1-21 (2020)
An R package for computing the all-subsets regression problem is presented. The proposed algorithms are based on computational strategies recently developed. A novel algorithm for the best-subset regression problem selects subset models based on a pr
Externí odkaz:
https://doaj.org/article/dc5551b767e643c6b404141fe7cba7ab
Publikováno v:
eISSN
Physical numerical weather prediction models have biases and miscalibrations that can depend on the weather situation, which makes it difficult to postprocess them effectively using the traditional model output statistics (MOS) framework based on par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a85a4c56fa8f947b9e47c38d6a5bf10
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1021/
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1021/
Meteorological environments favorable for thunderstorms are studied across Europe, including rare thunderstorm conditions from seasons with climatologically few thunderstorms. Using cluster analysis on ERA5 reanalysis data and EUCLID (European Cooper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c418b87b74756a321ee509dda5c2ff2a
https://wcd.copernicus.org/articles/4/489/2023/
https://wcd.copernicus.org/articles/4/489/2023/
Autor:
Isabell Stucke, Deborah Morgenstern, Gerhard Diendorfer, Georg J. Mayr, Hannes Pichler, Wolfgang Schulz, Thorsten Simon, Achim Zeileis
Publikováno v:
Journal of Geophysical Research: Atmospheres. 128
Publikováno v:
Journal of Open Research Software, Vol 7, Iss 1 (2019)
Typical models estimating treatment effects assume that the treatment effect is the same for all individuals. Model-based recursive partitioning allows to relax this assumption and to estimate stratified treatment effects (model-based trees) or even
Externí odkaz:
https://doaj.org/article/7a3aa85184504808aa22028689ae2b4a
Differentiating lightning in winter and summer with characteristics of the wind field and mass field
Publikováno v:
Weather and Climate Dynamics. 3:361-375
Lightning in winter (December–January–February, DJF) is rare compared to lightning in summer (June–July–August, JJA) in central Europe north of the Alps. The conventional explanation attributes the scarcity of lightning in winter to seasonall
Lightning characteristics in all seasons are investigated across Europe because it is observed that lightning strikes to tall infrastructure have no or only a weak annual cycle whereas lightning in general has a pronounced annual cycle. Using cluster
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::727a0c7b2d50201f4fee2882e53074f1
https://doi.org/10.5194/egusphere-2022-1453
https://doi.org/10.5194/egusphere-2022-1453