A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
This package provides a new way of computing bootstrap supports in large phylogenies.
B2 makes it easy to build C++ projects, everywhere. B2 has been the primary build system for the Boost C++ Libraries for many years.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
Boosting Regression Quantiles is a component-wise boosting algorithm, that embeds all boosting steps in the well-established framework of quantile regression. It is initialized with the corresponding quantile, uses a quantile-specific learning rate, and uses quantile regression as its base learner. The package implements this algorithm and allows cross-validation and stability selection.
Jointly models the multivariate longitudinal responses and multiple covariates and time using gradient boosting approach.
The Boost.Sync library provides mutexes, semaphores, locks and events and other thread related facilities. Boost.Sync originated from Boost.Thread.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
BOOST-RE is a small, portable, lightweight, and quick, regular expression library for Common Lisp. It is a non-recursive, backtracking VM.
R bindings for the various functions and statistical distributions provided by the Boost Math library <https://www.boost.org/doc/libs/latest/libs/math/doc/html/index.html>.
A collection of libraries intended to be widely useful, and usable across a broad spectrum of applications.
BOOST-RE is a small, portable, lightweight, and quick, regular expression library for Common Lisp. It is a non-recursive, backtracking VM.
This package implements Friedman's gradient descent boosting algorithm for modeling longitudinal response using multivariate tree base learners. Longitudinal response could be continuous, binary, nominal or ordinal. A time-covariate interaction effect is modeled using penalized B-splines (P-splines) with estimated adaptive smoothing parameter. Although the package is design for longitudinal data, it can handle cross-sectional data as well. Implementation details are provided in Pande et al. (2017), Mach Learn <DOI:10.1007/s10994-016-5597-1>.
BOOST-JSON is a simple JSON parsing library for Common Lisp.
BOOST-RE is a small, portable, lightweight, and quick, regular expression library for Common Lisp. It is a non-recursive, backtracking VM.
Includes functions to estimate production frontiers and make ideal output predictions in the Data Envelopment Analysis (DEA) context using both standard models from DEA and Free Disposal Hull (FDH) and boosting techniques. In particular, EATBoosting (Guillen et al., 2023 <doi:10.1016/j.eswa.2022.119134>) and MARSBoosting. Moreover, the package includes code for estimating several technical efficiency measures using different models such as the input and output-oriented radial measures, the input and output-oriented Russell measures, the Directional Distance Function (DDF), the Weighted Additive Measure (WAM) and the Slacks-Based Measure (SBM).
BOOST-JSON is a simple JSON parsing library for Common Lisp.