Showing 11 of total 11 results (show query)
covaruber
sommer:Solving Mixed Model Equations in R
Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.
Maintained by Giovanny Covarrubias-Pazaran. Last updated 3 days ago.
average-informationmixed-modelsrcpparmadilloopenblascppopenmp
44 stars 12.63 score 300 scripts 10 dependents
dsstoffer
astsa:Applied Statistical Time Series Analysis
Contains data sets and scripts for analyzing time series in both the frequency and time domains including state space modeling as well as supporting the texts Time Series Analysis and Its Applications: With R Examples (5th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2025, <https://link.springer.com/book/9783031705830>, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, <DOI:10.1201/9780429273285>.
Maintained by David Stoffer. Last updated 2 months ago.
7 stars 7.86 score 2.2k scripts 8 dependents
bioc
Icens:NPMLE for Censored and Truncated Data
Many functions for computing the NPMLE for censored and truncated data.
Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.
3.83 score 16 scripts 7 dependents
cran
blockmodeling:Generalized and Classical Blockmodeling of Valued Networks
This is primarily meant as an implementation of generalized blockmodeling for valued networks. In addition, measures of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted: Žiberna (2007)<doi:10.1016/j.socnet.2006.04.002>, Žiberna (2008)<doi:10.1080/00222500701790207>, Žiberna (2014)<doi:10.1016/j.socnet.2014.04.002>.
Maintained by Aleš Žiberna. Last updated 2 years ago.
2.78 score 12 dependents
barbehenna
ebTobit:Empirical Bayesian Tobit Matrix Estimation
Estimation tools for multidimensional Gaussian means using empirical Bayesian g-modeling. Methods are able to handle fully observed data as well as left-, right-, and interval-censored observations (Tobit likelihood); descriptions of these methods can be found in Barbehenn and Zhao (2023) <doi:10.48550/arXiv.2306.07239>. Additional, lower-level functionality based on Kiefer and Wolfowitz (1956) <doi:10.1214/aoms/1177728066> and Jiang and Zhang (2009) <doi:10.1214/08-AOS638> is provided that can be used to accelerate many empirical Bayes and nonparametric maximum likelihood problems.
Maintained by Alton Barbehenn. Last updated 11 months ago.
1 stars 2.70 score 4 scripts
blansche
fdm2id:Data Mining and R Programming for Beginners
Contains functions to simplify the use of data mining methods (classification, regression, clustering, etc.), for students and beginners in R programming. Various R packages are used and wrappers are built around the main functions, to standardize the use of data mining methods (input/output): it brings a certain loss of flexibility, but also a gain of simplicity. The package name came from the French "Fouille de Données en Master 2 Informatique Décisionnelle".
Maintained by Alexandre Blansché. Last updated 2 years ago.
1 stars 1.62 score 42 scripts
rpbrowne
leptokurticMixture:Implements Parsimonious Finite Mixtures of Multivariate Elliptical Leptokurtic-Normals
A way to fit Parsimonious Finite Mixtures of Multivariate Elliptical Leptokurtic-Normals. Two methods of estimation are implemented.
Maintained by Ryan Browne. Last updated 2 years ago.
1.00 score
guangbaog
DTSR:Distributed Trimmed Scores Regression for Handling Missing Data
Provides functions for handling missing data using Distributed Trimmed Scores Regression and other imputation methods. It includes facilities for data imputation, evaluation metrics, and clustering analysis. It is designed to work in distributed computing environments to handle large datasets efficiently. The philosophy of the package is described in Guo G. (2024) <doi:10.1080/03610918.2022.2091779>.
Maintained by Guangbao Guo. Last updated 5 months ago.
1.00 scorecran
DEM:The Distributed EM Algorithms in Multivariate Gaussian Mixture Models
The distributed expectation maximization algorithms are used to solve parameters of multivariate Gaussian 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.
1.00 scoreguangbaog
DIRMR:Distributed Imputation for Random Effects Models with Missing Responses
By adding over-relaxation factor to PXEM (Parameter Expanded Expectation Maximization) method, the MOPXEM (Monotonically Overrelaxed Parameter Expanded Expectation Maximization) method is obtained. Compare it with the existing EM (Expectation-Maximization)-like methods. Then, distribute and process five methods and compare them, achieving good performance in convergence speed and result quality.The philosophy of the package is described in Guo G. (2022) <doi:10.1007/s00180-022-01270-z>.
Maintained by Guangbao Guo. Last updated 4 months ago.
1.00 score