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r-future
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public |
The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, on in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implements additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
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2025-03-25 |
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r-listenv
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public |
List environments are environments that have list-like properties. For instance, the elements of a list environment are ordered and can be accessed and iterated over using index subsetting, e.g. 'x <- listenv(a = 1, b = 2); for (i in seq_along(x)) x[[i]] <- x[[i]] ^ 2; y <- as.list(x)'.
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2025-03-25 |
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r-globals
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public |
Identifies global ("unknown" or "free") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal. The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.
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2025-03-25 |
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r-corrplot
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public |
A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering. In addition, corrplot is good at details, including choosing color, text labels, color labels, layout, etc.
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2025-03-25 |
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r-glm2
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public |
Fits generalized linear models using the same model specification as glm in the stats package, but with a modified default fitting method that provides greater stability for models that may fail to converge using glm.
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2025-03-25 |
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r-elasticnet
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public |
This package provides functions for fitting the entire solution path of the Elastic-Net and also provides functions for estimating sparse Principal Components. The Lasso solution paths can be computed by the same function. First version: 2005-10.
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2025-03-25 |
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r-dynlm
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public |
Dynamic linear models and time series regression.
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2025-03-25 |
