Age | Commit message (Collapse) | Author | Files | Lines |
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Minor pkglinting
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A framework for creating HTML widgets that render in various contexts
including the R console, 'R Markdown' documents, and 'Shiny' web
applications.
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Implements an S3 class for storing and formatting time-of-day values,
based on the 'difftime' class.
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Import excel files into R. Supports '.xls' via the embedded 'libxls' C
library <https://github.com/evanmiller/libxls> and '.xlsx' via the
embedded 'RapidXML' C++ library <http://rapidxml.sourceforge.net>.
Works on Windows, Mac and Linux without external dependencies.
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Function to read and write the 'Stata' file format.
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The goal of 'readr' is to provide a fast and friendly way to read
rectangular data (like 'csv', 'tsv', and 'fwf'). It is designed to
flexibly parse many types of data found in the wild, while still
cleanly failing when data unexpectedly changes.
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Changes:
20190730
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Extractors
* [youtube] Fix and improve title and description extraction (#21934)
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Simplifies the creation of Excel .xlsx files by providing a high level
interface to writing, styling and editing worksheets. Through the use
of 'Rcpp', read/write times are comparable to the 'xlsx' and
'XLConnect' packages with the added benefit of removing the dependency
on Java.
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Tables with state-of-the-art layout elements such as row spanners,
column spanners, table spanners, zebra striping, and more. While
allowing advanced layout, the underlying css-structure is simple in
order to maximize compatibility with word processors such as 'MS Word'
or 'LibreOffice'. The package also contains a few text formatting
functions that help outputting text compatible with HTML/LaTeX.
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Import foreign statistical formats into R via the embedded 'ReadStat'
C library, <https://github.com/WizardMac/ReadStat>.
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Fast aggregation of large data (e.g. 100GB in RAM), fast ordered
joins, fast add/modify/delete of columns by group using no copies at
all, list columns, friendly and fast character-separated-value
read/write. Offers a natural and flexible syntax, for faster
development.
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Helper functions to work with spreadsheets and the "A1:D10" style of cell
range specification.
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Configurable Progress bars, they may include percentage, elapsed time,
and/or the estimated completion time. They work in terminals, in
'Emacs' 'ESS', 'RStudio', 'Windows' 'Rgui' and the 'macOS' 'R.app'.
The package also provides a 'C++' 'API', that works with or without
'Rcpp'.
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Contains many functions useful for data analysis, high-level graphics,
utility operations, functions for computing sample size and power,
importing and annotating datasets, imputing missing values, advanced
table making, variable clustering, character string manipulation,
conversion of R objects to LaTeX and html code, and recoding
variables.
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Provides a %<-% operator to perform multiple, unpacking, and
destructuring assignment in R. The operator unpacks the right-hand
side of an assignment into multiple values and assigns these values to
variables on the left-hand side of the assignment.
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Defines new notions of prototype and size that are used to provide
tools for consistent and well-founded type-coercion and
size-recycling, and are in turn connected to ideas of type- and
size-stability useful for analyzing function interfaces.
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Unit root and cointegration tests encountered in applied econometric
analysis are implemented.
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Summary statistics, two-sample tests, rank tests, generalised linear
models, cumulative link models, Cox models, loglinear models, and
general maximum pseudolikelihood estimation for multistage stratified,
cluster-sampled, unequally weighted survey samples. Variances by
Taylor series linearisation or replicate weights. Post-stratification,
calibration, and raking. Two-phase subsampling designs. Graphics. PPS
sampling without replacement. Principal components, factor analysis.
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Model-robust standard error estimators for cross-sectional, time
series, clustered, panel, and longitudinal data.
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Access the RStudio API (if available) and provide informative error
messages when it's not.
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Functions to facilitate inference on the relative importance of
predictors in a linear or generalized linear model, and a couple of
useful Tcl/Tk widgets.
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Five omnibus tests for testing the composite hypothesis of normality.
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Tools to perform analyses and combine results from multiple-imputation
datasets.
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Helpers for reordering factor levels (including moving specified
levels to front, ordering by first appearance, reversing, and randomly
shuffling), and tools for modifying factor levels (including
collapsing rare levels into other, 'anonymising', and manually
'recoding').
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Provides tools for determining estimability of linear functions of
regression coefficients, and 'epredict' methods that handle
non-estimable cases correctly. Estimability theory is discussed in
many linear-models textbooks including Chapter 3 of Monahan, JF
(2008), "A Primer on Linear Models", Chapman and Hall (ISBN
978-1-4200-6201-4).
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The ellipsis is a powerful tool for extending functions. Unfortunately
this power comes at a cost: misspelled arguments will be silently
ignored. The ellipsis package provides a collection of functions to
catch problems and alert the user.
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Functions introduced or changed since R v3.0.0 are re-implemented in
this package. The backports are conditionally exported in order to let
R resolve the function name to either the implemented backport, or the
respective base version, if available. Package developers can make use
of new functions or arguments by selectively importing specific
backports to support older installations.
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Two nonparametric methods for multiple regression transform selection
are provided. The first, Alternative Conditional Expectations (ACE),
is an algorithm to find the fixed point of maximal correlation, i.e.
it finds a set of transformed response variables that maximizes R^2
using smoothing functions [see Breiman, L., and J.H. Friedman. 1985.
"Estimating Optimal Transformations for Multiple Regression and
Correlation". Journal of the American Statistical Association.
80:580-598. <doi:10.1080/01621459.1985.10478157>]. Also included is
the Additivity Variance Stabilization (AVAS) method which works better
than ACE when correlation is low [see Tibshirani, R.. 1986.
"Estimating Transformations for Regression via Additivity and Variance
Stabilization". Journal of the American Statistical Association.
83:394-405. <doi:10.1080/01621459.1988.10478610>]. A good introduction
to these two methods is in chapter 16 of Frank Harrel's "Regression
Modeling Strategies" in the Springer Series in Statistics.
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Various statistical, graphics, and data-management functions used by
the Rcmdr package in the R Commander GUI for R.
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Various utilities are provided that might be used in spatial
statistics and elsewhere. It delivers a method for solving linear
equations that checks the sparsity of the matrix before any algorithm
is used. Furthermore, it includes the Struve functions.
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Infrastructure for extended formulas with multiple parts on the
right-hand side and/or multiple responses on the left-hand side (see
<DOI:10.18637/jss.v034.i01>).
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Implementation of the 'viridis' - the default -, 'magma', 'plasma',
'inferno', and 'cividis' color maps for 'R'. 'viridis', 'magma',
'plasma', and 'inferno' are ported from 'matplotlib'
<http://matplotlib.org/>, a popular plotting library for 'python'.
'cividis', was developed by Jamie R. Nu<c3><b1>ez and Sean M. Colby.
These color maps are designed in such a way that they will
analytically be perfectly perceptually-uniform, both in regular form
and also when converted to black-and-white. They are also designed to
be perceived by readers with the most common form of color blindness
(all color maps in this package) and color vision deficiency
('cividis' only).
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Graphical and tabular effect displays, e.g., of interactions, for
various statistical models with linear predictors.
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This version fixes several slightly obscure bugs, and hopefully makes a
few things easier to find. Those playing on high-resolution monitors
(such as 4k) and use the UI scaling options should also find that things
appear less squished than they used to.
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Changes since the v0.10 release:
* Fix two potential integer overflows. (These were not security-critical unless the compiler took the opportunity provided by the undefined behavior to format your hard drive.)
* Allow JPEGs in METADATA_BLOCK_PICTURE tags to include EXIF data.
* A few warning fixes for gcc 8.
* Make opus_tags_copy return OP_EFAULT on failure instead of returning success.
* Various integration and testing environment improvements.
This release is backward-compatible with the previous release.
We recommend all users upgrade.
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Version 2.2.0 (released 2019-05-23)
* Perform A-Label roundtrip for lookup functions by default
* Stricter check of input to punycode decoder
* Fix punycode decoding with no ASCII chars but given delimiter
* Fix 'idn2 --no-tr64' (was a no-op)
* Allow _ as a basic code point in domain labels
* Fail building documentatino if 'ronn' isn't installed
* git tag changed to reflect https://semver.org/
Version 2.1.1 (released 2019-02-08)
* Revert SONAME bump from release 2.1.0
* Fix NULL dereference in idn2_register_u8() and idn2_register_ul()
* Fix free of random value in idn2_to_ascii_4i()
* Improved fuzzer (which found the above issues)
* Fix printf() crash in test-lookup.c on Solaris
* Check for valid unicode input in punycode encoder
* Avoid excessive CPU usage in punycode encoding with
large inputs
* Deprecate idn2_to_ascii_4i() in favor of idn2_to_ascii_4i2()
* Restrict output length of idn2_to_ascii_4i() to 63 bytes
Version 2.1.0 (released 2019-01-04)
* Two exposed functions are no longer exposed:
_idn2_punycode_encode() and _idn2_punycode_decode() which were
meant to be used internally only. The output needs additional
checks to be used safely.
This is the reason to for the SONAME bump, just in case.
* Fix label length check for idn2_register_u8()
* Remove compiler warnings
* Use gnulib-python tool for bootstrapping if possible
* Improve build system (several small issues)
* Add missing error messages to idn2_strerror_name()
* Improve docs and remove typos
* Update gnulib
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just apply the same workaround as upstream is using for FreeBSD.
bump PKGREVISION
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Doesn't seem to actually be used. curl pulls in libidn2, but that's all.
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This adds support for OCaml 4.08.
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