Showing 5 of total 5 results (show query)
jaredhuling
oem:Orthogonalizing EM: Penalized Regression for Big Tall Data
Solves penalized least squares problems for big tall data using the orthogonalizing EM algorithm of Xiong et al. (2016) <doi:10.1080/00401706.2015.1054436>. The main fitting function is oem() and the functions cv.oem() and xval.oem() are for cross validation, the latter being an accelerated cross validation function for linear models. The big.oem() function allows for out of memory fitting. A description of the underlying methods and code interface is described in Huling and Chien (2022) <doi:10.18637/jss.v104.i06>.
Maintained by Jared Huling. Last updated 8 months ago.
group-lassolassomachine-learningmcpoemoem-algorithmpenalized-regressionscadvariable-selectionopenblascppopenmp
98.2 match 27 stars 6.02 score 26 scripts 1 dependents
flr
mse:Tools for Running Management Strategy Evaluations using FLR
A set of functions and methods to enable the development and running of Management Strategy Evaluation (MSE) analyses, using the FLR packages and classes and the a4a methods and algorithms.
Maintained by Iago Mosqueira. Last updated 24 days ago.
17.1 match 4 stars 7.04 score 137 scripts 3 dependents
sprfmo
FLjjm:Running the JJM Stock Assessment Model Inside the MSE FLR System
Runs the JJM stock assessment model for Chilean Jack Mackerel inside the MSE system of FLR's mse package.
Maintained by Iago Mosqueira. Last updated 12 days ago.
5.8 match 3.74 score 3 scripts
ericdunipace
WpProj:Linear p-Wasserstein Projections
Performs Wasserstein projections from the predictive distributions of any model into the space of predictive distributions of linear models. We utilize L1 penalties to also reduce the complexity of the model space. This package employs the methods as described in Dunipace, Eric and Lorenzo Trippa (2020) <doi:10.48550/arXiv.2012.09999>.
Maintained by Eric Dunipace. Last updated 1 months ago.
2.7 match 3.48 score
cran
DOEM:The Distributed Online Expectation Maximization Algorithms to Solve Parameters of Poisson Mixture Models
The distributed online expectation maximization algorithms are used to solve parameters of Poisson mixture models. The philosophy of the package is described in Guo, G. (2022) <doi:10.1080/02664763.2022.2053949>.
Maintained by Qian Wang. Last updated 3 years ago.
6.4 match 1.00 score 1 scripts