Estimation of the Calibration Equation with Error-in
Observations
Statistical inferences for estimating the calibration equation with error-in observations

Lasso Penalized Precision Matrix Estimation
Estimates a lasso penalized precision matrix via the blockwise coordinate descent (BCD). This package is a simple wrapper around the popular 'glasso' package that extends and enhances its capabilities. These enhancements include built-in cross validation and visualizations.
See Friedman et al (2008) <doi:10.1093/biostatistics/kxm045> for details regarding the estimation method.
stats, parallel, foreach, ggplot2, dplyr, glasso

Compute Risk Scores for Cardiovascular Diseases
person(given = "Victor",
family = "Castro",
role = c("aut", "cre"),
email = "vcastro@mgh.harvard.edu",
comment = c(ORCID = "https://orcid.org/0000-0001-7390-6354"))
Calculate various cardiovascular disease risk scores from the
Framingham Heart Study (FHS), the American College of Cardiology (ACC),
and the American Heart Association (AHA) as described in D’agostino, et al
(2008) <doi:10.1161/circulationaha.107.699579>, Goff, et al (2013)
<doi:10.1161/01.cir.0000437741.48606.98>, and Mclelland, et al (2015)
<doi:10.1016/j.jacc.2015.08.035>.
Victor Castro [aut, cre] (<https://orcid.org/0000-0001-7390-6354>)

Conditional Density Estimation Network Construction and
Evaluation
A probabilistic extension of the standard multi-layer
perceptron neural network

Parameters of a user-specified probability distribution are modelled by a multi-layer perceptron artificial neural network. This framework can be used to implement probabilistic nonlinear models including mixture density networks, heteroscedastic regression models, zero-inflated models, and the like.

Parameters of a user-specified probability distribution are modelled by a multi-layer perceptron artificial neural network. This framework can be used to implement probabilistic nonlinear models including mixture density networks, heteroscedastic regression models, zero-inflated models, etc. following Cannon (2012) <doi:10.1016/j.cageo.2011.08.023>.