A framework for 'scalable' statistical computing on large on-disk matrices stored in 'HDF5' files. It provides efficient block-wise implementations of core linear-algebra operations (matrix multiplication, SVD, PCA, QR decomposition, and canonical correlation analysis) written in C++ and R. These building blocks are designed not only for direct use, but also as foundational components for developing new statistical methods that must operate on datasets too large to fit in memory. The package supports data provided either as 'HDF5' files or standard R objects, and is intended for high-dimensional applications such as 'omics' and precision-medicine research.

Application of theoretical results which ensure that the summation of an infinite discrete series is within an arbitrary margin of error of its true value. The C code under the hood is shared through header files to allow users to sum their own low level functions as well. Based on the paper by Braden (1992) &lt;<a href="https://doi.org/10.2307%2F2324995" target="_top">doi:10.2307/2324995</a>&gt;.

Solving high-dimensional double sparse linear regression via an iterative hard thresholding algorithm. Furthermore, the method is extended to jointly estimate multiple graphical models. For more details, please see &lt;<a href="https://www.jmlr.org/papers/v25/23-0653.html" target="_top">https://www.jmlr.org/papers/v25/23-0653.html</a>&gt; and &lt;<a href="https://doi.org/10.48550%2FarXiv.2503.18722" target="_top">doi:10.48550/arXiv.2503.18722</a>&gt;.

Package for the access and distribution of long-term lake datasets from lakes in the Adirondack Park, northern New York state. Includes a wide variety of physical, chemical, and biological parameters from 28 lakes. Data are from multiple collection organizations and have been harmonized in both time and space for ease of reuse.

Provides functions for detecting spatial clusters using the flexible spatial scan statistic developed by Tango and Takahashi (2005) &lt;<a href="https://doi.org/10.1186%2F1476-072X-4-11" target="_top">doi:10.1186/1476-072X-4-11</a>&gt;. This package implements a wrapper for the 'C' routine used in the 'FleXScan' 3.1.2 &lt;<a href="https://sites.google.com/site/flexscansoftware/home" target="_top">https://sites.google.com/site/flexscansoftware/home</a>&gt; developed by Takahashi, Yokoyama, and Tango. For details, see Otani et al. (2021) &lt;<a href="https://doi.org/10.18637%2Fjss.v099.i13" target="_top">doi:10.18637/jss.v099.i13</a>&gt;.

Functions for reading and decompressing the 'DBC' (compressed 'DBF') files. Please note that this is the file format used by the Brazilian Ministry of Health ('DATASUS') to publish healthcare datasets. It is not related to the 'FoxPro' or 'CANdb' 'DBC' file formats.

Provides design-based and model-based estimators for the population average marginal component effects in general factorial experiments, including conjoint analysis. The package also implements a series of recommendations offered in de la Cuesta, Egami, and Imai (2022) &lt;<a href="https://doi.org/10.1017%2Fpan.2020.40" target="_top">doi:10.1017/pan.2020.40</a>&gt;, and Egami and Imai (2019) &lt;<a href="https://doi.org/10.1080%2F01621459.2018.1476246" target="_top">doi:10.1080/01621459.2018.1476246</a>&gt;.

A toolset for generating Ecological Limit Function (ELF) models and evaluating potential species loss resulting from flow change, based on the 'elfgen' framework. ELFs describe the relation between aquatic species richness (fish or benthic macroinvertebrates) and stream size characteristics (streamflow or drainage area). Journal publications are available outlining framework methodology (Kleiner et al. (2020) &lt;<a href="https://doi.org/10.1111%2F1752-1688.12876" target="_top">doi:10.1111/1752-1688.12876</a>&gt;) and application (Rapp et al. (2020) &lt;<a href="https://doi.org/10.1111%2F1752-1688.12877" target="_top">doi:10.1111/1752-1688.12877</a>&gt;).