Depends: reshape, methods, lattice, grid, XML, MASS

distributions, reporting of output tables and creation of
detailed analysis logs.  Deprecated.  Please see the

Title: Mixture summary method for multiple imputation
Author: Russell Steele, Naisyin Wang, and Adrian Raftery
Description: Tools to combine results for multiply-imputed data using

Title: Learn Direct Interaction Networks
Author: Surojit Biswas, Meredith McDonald, Derek S. Lundberg, Jeffery L. Dangl,
Description: Learns direct microbe-microbe interaction networks using a Poisson
multivariate-normal hierarchical model with an L1 penalized precision
matrix. Optimization is carried out using an iterative conditional modes

Title: Maximum kernel likelihood estimation
Description: Package to compute the maximum kernel likelihood estimator (MKLE) for mu.
Packaged: Sun Jul 23 23:16:51 2006; hornik

Title: Maximum kernel likelihood estimation.
Description: Package for fast computation of the maximum kernel likelihood estimator (mkle)
Packaged: Tue Aug 14 14:58:20 2007; jaki

Packaged: Wed Feb 27 11:12:40 2008; jaki

Description: Package for fast computation of the maximum kernel

Title: Maximum Kernel Likelihood Estimation
Description: Package for fast computation of the maximum kernel likelihood estimator (mkle).

Title: A Modern K-Means (MKMeans) Clustering Algorithm
Author: Yi Ya, Yarong Yang, and Jacob Zhang
Description: It's a modern K-Means clustering method with no limitation on the selection of initial centers but only the number of clusters is needed.
Collate: AllClasses.R MKMeans.R C.f.R Dist.R
Packaged: 2021-11-13 14:07:26 UTC; Administrator

Description: It's a Modern K-Means clustering algorithm allowing data of any number of dimensions, any initial center, and any number of clusters to expect.
Packaged: 2021-12-05 10:31:22 UTC; Administrator

Packaged: 2022-06-12 15:04:22 UTC; Administrator

Authors@R: person("Matthias", "Kohl", role = c("aut", "cre"),
Author: Matthias Kohl [aut, cre] (<https://orcid.org/0000-0001-9514-8910>)
Suggests: knitr, rmarkdown, foreach, parallel, doParallel
Description: Performance measures and scores for statistical classification such as accuracy, sensitivity, specificity, recall, similarity coefficients, AUC, GINI index, Brier score and many more. Calculation of optimal cut-offs and decision stumps (Iba and Langley (1991), <doi:10.1016/B978-1-55860-247-2.50035-8>) for all implemented performance measures. Hosmer-Lemeshow goodness of fit tests (Lemeshow and Hosmer (1982), <doi:10.1093/oxfordjournals.aje.a113284>; Hosmer et al (1997), <doi:10.1002/(SICI)1097-0258(19970515)16:9%3C965::AID-SIM509%3E3.0.CO;2-O>). Statistical and epidemiological risk measures such as relative risk, odds ratio, number needed to treat (Porta (2014), <doi:10.1093%2Facref%2F9780199976720.001.0001>).