R (>= 2.15.0), lattice, igraph, MASS, Matrix
The package "camel" provides the implementation of a family of high-dimensional calibrated machine learning toolkits, including a family of Lasso regression and sparse Gaussian graphical model estimation. Lasso variants including Dantzig Selector, LAD Lasso, SQRT Lasso for estimating high dimensional sparse linear model. The sparse Gaussian graphical model estimation includes TIGER and CLIME using L1 penalty. We adopt the combination of the dual smoothing and monotone fast iterative soft-thresholding algorithm (MFISTA). The computation is memory-optimized using the sparse matrix output.

The package "camel" provides the implementation of a family of high-dimensional calibrated machine learning tools, including (1) LAD, SQRT Lasso and Calibrated Dantzig Selector for estimating sparse linear models; (2) Calibrated Multivariate Regression for estimating sparse multivariate linear models; (3) Tiger, Calibrated Clime for estimating sparse Gaussian graphical models. We adopt the combination of the dual smoothing and monotone fast iterative soft-thresholding algorithm (MFISTA). The computation is memory-optimized using the sparse matrix output, and accelerated by the path following and active set tricks.

Datasets from "Microeconometrics: Methods and Applications" by
Cameron and Trivedi
person(given = "Juliana",
family = "Vega-Lacorte",
role = c("aut", "cre"),
email = "jv@jv-lacorte.de")
Quick and easy access to datasets that let you replicate the
empirical examples in Cameron and Trivedi (2005) "Microeconometrics: Methods and
Applications" (ISBN: 9780521848053).The data are available as soon as you install
and load the package (lazy-loading) as data frames. The documentation includes
reference to chapter sections and page numbers where the datasets are used.

Connect to Campaign Manager via the 'Windsor.ai' API
Collect  marketing data from Campaign Manager using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

c(person(given = "Kiernan",
family = "Nicholls",
role = c("aut", "cre", "cph"),
email = "kiernann@protonmail.com"),
person(given = "Schuyler",
family = "Erle",
role = "cph",
email = "schuyler@geocoder.us"))
Explore and normalize American campaign finance
data. Created by the Investigative Reporting Workshop to facilitate
work on The Accountability Project, an effort to collect public data
into a central, standard database that is more easily searched:
<https://publicaccountability.org/>.
Kiernan Nicholls [aut, cre, cph],
Schuyler Erle [cph]