plyr: Tools for splitting, applying and combining data. plyr is a set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each pieces and then put all the pieces back together. For example, you might want to fit a model to each spatial location or time point in your study, summarise data by panels or collapse high-dimensional arrays to simpler summary statistics. The development of plyr has been generously supported by BD (Becton Dickinson).
Keywords for this software
References in zbMATH (referenced in 11 articles , 1 standard article )
Showing results 1 to 11 of 11.
- Yavuv, Fulya Gokalp; Schloerke, Barret: Parallel computing in linear mixed models (2020)
- Zhuang, Yonghua; Wade, Kristen; Saba, Laura M.; Kechris, Katerina: Development of a tissue augmented Bayesian model for expression quantitative trait loci analysis (2020)
- Kaplan, Andee J.; Hare, Eric R.: Putting down roots: a graphical exploration of community attachment (2019)
- Maurer, Karsten; Osthus, Dave; Loy, Adam: A tale of four cities: exploring the soul of State College, Detroit, Milledgeville and Biloxi (2019)
- McNamara, Amelia A.: Community engagement and subgroup meta-knowledge: some factors in the soul of a community (2019)
- Quach, Anna; Symanzik, Jürgen; Forsgren, Nicole: Soul of the community: an attempt to assess attachment to a community (2019)
- Niemi, Jarad; Mittman, Eric; Landau, Will; Nettleton, Dan: Empirical Bayes analysis of RNA-seq data for detection of gene expression heterosis (2015)
- Lawrence, Michael; Morgan, Martin: Scalable genomics with \textttRand bioconductor (2014)
- Gałecki, Andrzej; Burzykowski, Tomasz: Linear mixed-effects models using R. A step-by-step approach (2013)
- Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)
- Hadley Wickham: The Split-Apply-Combine Strategy for Data Analysis (2011) not zbMATH