2009
DOI: 10.32614/rj-2009-017
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sos: Searching Help Pages of R Packages

Abstract: The sos package provides a means to quickly and flexibly search the help pages of contributed packages, finding functions and datasets in seconds or minutes that could not be found in hours or days by any other means we know. Its findFn function accesses Jonathan Baron's R Site Search database and returns the matches in a data frame of class "findFn", which can be further manipulated by other sos functions to produce, for example, an Excel file that starts with a summary sheet that makes it relatively easy to … Show more

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Cited by 63 publications
(66 citation statements)
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“…Search Tools There are several search mechanisms, both inside and outside of R, that help users to locate resources -for example, the help.search and RSiteSearch commands in R; various search sites, such as http://www. rseek.org/; the sos package (Graves et al, 2009); and the Crantastic web site, http:// crantastic.org/, which has both package search and tagging features. My experience with these facilities is that they are useful, but they often both produce large numbers of irrelevant hits and miss relevant information.…”
Section: Negotiating Cranmentioning
confidence: 99%
“…Search Tools There are several search mechanisms, both inside and outside of R, that help users to locate resources -for example, the help.search and RSiteSearch commands in R; various search sites, such as http://www. rseek.org/; the sos package (Graves et al, 2009); and the Crantastic web site, http:// crantastic.org/, which has both package search and tagging features. My experience with these facilities is that they are useful, but they often both produce large numbers of irrelevant hits and miss relevant information.…”
Section: Negotiating Cranmentioning
confidence: 99%
“…Data on the infestation index were analysed using the Kruskal-Wallis test to compare the median between vegetation productivity classes, followed by the Dunn’s test for posthoc analyses where P values were adjusted with the Benjamini-Hochberg method. Statistical analyses were performed in R version 3.6.3 [ 59 ], using the packages nlme [ 60 ], emmeans [ 61 ] and multcompView [ 62 ]. Significance was appreciated at α = 0.05.…”
Section: Methodsmentioning
confidence: 99%
“…For significant differences, Tukey contrasts were used to analyse variations between years. Tukey post hoc test contrasts were performed using the “multicomp” R packages (Hothorn et al ., 2016), “lsmeans” (Lenth & Lenth, 2018) and “multicompView” (Graves et al ., 2015). Assumptions of normality and homoscedasticity were assessed using Kolmogorov–Smirnov/Lilliefors and Bartlett's tests.…”
Section: Methodsmentioning
confidence: 99%