David Hugh-Jones

David Hugh-Jones

9 packages on CRAN

anim.plots

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Simple animated versions of basic R plots, using the 'animation' package. Includes animated versions of plot, barplot, persp, contour, filled.contour, hist, curve, points, lines, text, symbols, segments, and arrows.

huxtable

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Creates styled tables for data presentation. Export to HTML, LaTeX, RTF, 'Word', 'Excel', and 'PowerPoint'. Simple, modern interface to manipulate borders, size, position, captions, colours, text styles and number formatting. Table cells can span multiple rows and/or columns. Includes a 'huxreg' function for creation of regression tables, and 'quick_*' one-liners to print data to a new document.

rcheology

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Provides a dataset of functions in all base packages of R versions 1.0.1 onwards.

refset

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Provides subsets with reference semantics, i.e. subsets which automatically reflect changes in the original object, and which optionally update the original object when they are changed.

santoku

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A tool for cutting data into intervals. Allows singleton intervals. Always includes the whole range of data by default. Flexible labelling. Convenience functions for cutting by quantiles etc. Handles dates and times.

truelies

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Implements Bayesian methods, described in Hugh-Jones (2019) <doi:10.1007/s40881-019-00069-x>, for estimating the proportion of liars in coin flip-style experiments, where subjects report a random outcome and are paid for reporting a "good" outcome.

broom

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Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.

covr

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Track and report code coverage for your package and (optionally) upload the results to a coverage service like 'Codecov' <https://codecov.io> or 'Coveralls' <https://coveralls.io>. Code coverage is a measure of the amount of code being exercised by a set of tests. It is an indirect measure of test quality and completeness. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/FORTRAN code.

knitr

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Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.