utils, stats, methods, graphics, grDevices, MASS, Rcpp
Rcpp, RcppEigen, RcppProgress, BH, bigmemory

utils, stats, methods, graphics, grDevices, MASS, Rcpp,
bigmemory

A Robust Missing Imputation Method for Gene Expression Data
Md. Shahjaman and Md. Nurul Haque Mollah
It was developed especially for gene expression and metabolomics data analysis when the datasets are corrupted by outliers and missing values. The beta-divergence method was used to impute the missing values and modify the outliers.

c(
person("Shuxia", "Guo", email = "shuxia.guo@uni-jena.de", role = c("cre","aut")),
person("Thomas", "Bocklitz", role = "aut"),
person("Juergen", "Popp", role = c("ctb","cph")))
Shuxia Guo [cre, aut],
Thomas Bocklitz [aut],
Juergen Popp [ctb, cph]
A framework of cross-validation for spectral data analysis that allows for automatic tuning of model parameters and for model evaluation. It is particularly useful for applications where intra-group heterogeneity is significant due to inter individual differences. S. Guo, T. Bocklitz, U. Neugebauer, J.Popp (2017) <doi:10.1039/C7AY01363A>.

Collection of functions to calculate performance metrics of mutual funds/exchange traded funds. This package aids investors in researching mutual funds/exchange traded funds for their investment decision. Also, this package contains tools to manage a portfolio of different mutual fund/exchange traded funds. For more information see Bruce J. Feibel [2003, ISBN:978-0471445630].
PerformanceAnalytics, quantmod, xts, stringr, rvest, xml2,
readr, purrr, tidyr, stringi, ggplot2, dplyr
2020-06-25 17:29:28 UTC; Kanhaiiya Agrawal

Automate Mouse Clicks and Send Keyboard Input
person("Dejan", "Prvulovic", email = "dejan.prv@gmail.com", role = c("aut", "cre"))
Provides wrapper functions to the Java Robot class to automate user input, like mouse movements, clicks and keyboard input.

An implementation of robust nonnegative matrix factorization (rNMF). The rNMF algorithm decomposes a nonnegative high dimension data matrix into the product of two low rank nonnegative matrices, while detecting and trimming outliers. The main function is rnmf(). The package also includes a visualization tool, see(), that arranges and prints vectorized images.
Yifan Ethan Xu <ethan.yifanxu@gmail.com>, Jiayang Sun <jsun@case.edu>