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paytonjjones

networktools:Tools for Identifying Important Nodes in Networks

Includes assorted tools for network analysis. Bridge centrality; goldbricker; MDS, PCA, & eigenmodel network plotting.

Maintained by Payton Jones. Last updated 1 months ago.

10 stars 6.75 score 93 scripts 5 dependents

marcburri

bridgr:Bridging Data Frequencies for Timely Economic Forecasts

Provides tools for implementing bridge models, which are used to nowcast and forecast macroeconomic variables by linking high-frequency indicator variables (e.g., monthly data) to low-frequency target variables (e.g., quarterly GDP). Forecasting and aggregation of the indicator variables to match the target frequency are simplified, enabling timely predictions before official data releases are available. For more information about bridge models, see Baffigi, A., Golinelli, R., \& Parigi, G. (2004) <doi:10.1016/S0169-2070(03)00067-0>, Burri (2023) <https://www5.unine.ch/RePEc/ftp/irn/pdfs/WP23-02.pdf> or Schumacher (2016) <doi:10.1016/j.ijforecast.2015.07.004>.

Maintained by Marc Burri. Last updated 4 months ago.

2 stars 4.52 score 11 scripts

rbgramacy

monomvn:Estimation for MVN and Student-t Data with Monotone Missingness

Estimation of multivariate normal (MVN) and student-t data of arbitrary dimension where the pattern of missing data is monotone. See Pantaleo and Gramacy (2010) <doi:10.48550/arXiv.0907.2135>. Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail, the package can handle a nearly arbitrary amount of missing data. The current version supports maximum likelihood inference and a full Bayesian approach employing scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness patterns. A fully functional standalone interface to the Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown), Horseshoe (from Carvalho, Polson, & Scott), and ridge regression with model selection via Reversible Jump, and student-t errors (from Geweke) is also provided.

Maintained by Robert B. Gramacy. Last updated 6 months ago.

fortranopenblascpp

4 stars 3.05 score 127 scripts

byuzbasi

rbridge:Restricted Bridge Estimation

Bridge Regression estimation with linear restrictions defined in Yuzbasi et al. (2019) <arXiv:1910.03660>. Special cases of this approach fit the restricted LASSO, restricted RIDGE and restricted Elastic Net estimators.

Maintained by Bahadir Yuzbasi. Last updated 5 years ago.

openblascpp

1.00 score 7 scripts

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