Supplies a LazyData facility for packages which have data
sets but do not provide LazyData: true.  A single function is
is included, requireData, which is a drop-in replacement for
base::require, but carrying the additional
functionality. By default, it suppresses package
startup messages as well.  See argument 'reallyQuitely'.

Provides a new type of numbers called the lazy numbers.
Arithmetic on lazy numbers is exact, contrary to ordinary
floating-point arithmetic. The lazy numbers are implemented in 'C++'
with the 'CGAL' library (<https://www.cgal.org/>).
'classes.R' 'Arith.R' 'Compare.R' 'Concat.R' 'Extract.R'
'Math.R' 'RcppExports.R' 'Summary.R' 'Transpose.R' 'aaa.R'
'lazyMatrices.R' 'lazyNumbers.R'

Provides the functionality to write LaTeX code from within R without having to learn LaTeX.

Provides the functionality to write LaTeX code from within
R without having to learn LaTeX.

Provides the functionality to write LaTeX code from within R
without having to learn LaTeX.  Functionality also exists to create HTML
and Markdown code.  While the functionality still exists to write
complete documents with lazyWeave, it is generally easier to do so with
with markdown and knitr.  lazyWeave's main strength now is the ability
to design custom and complex tables for reporting results.

c(
person("Benjamin", "Nutter", email = "benjamin.nutter@gmail.com",
role = c("aut", "cre")))

Persistent Large Data Array with Lazy-Loading on Demand
c(
person("Zhengjia", "Wang", email = "dipterix.wang@gmail.com", role = c("aut", "cre", "cph")),
person("Mark", "Klik", email = "markklik@gmail.com", role = c("ctb", "cph"),
comment = "Copyright holder of fstcore package")
)
Multi-threaded serialization of compressed array that
fully utilizes modern solid state drives. It allows
to store and load extremely large data on demand within seconds
without occupying too much memories. With data stored on hard drive,
a lazy-array data can be loaded, shared across multiple R sessions.
For arrays with partition mode on, multiple R sessions can write to
a same array simultaneously along the last dimension (partition).
Zhengjia Wang [aut, cre, cph],
Mark Klik [ctb, cph] (Copyright holder of fstcore package)