person("Mohieddin", "Jafari", role = c("aut"),email = "mohieddin.jafari@helsinki.fi"),
person("Cheng", "Chen", role = c("aut","cre"),email = "cheng.chen@helsinki.fi")
Description: Functions for nominal data mining based on bipartite graphs, which build a pipeline for analysis and missing values imputation. Methods are mainly from the paper: Jafari, Mohieddin, et al. (2021) <doi:10.1101/2021.03.18.436040>, some new ones are also included.
Suggests: knitr, utils, rmarkdown, htmltools, testthat (>= 3.0.0)
Imports: plotly, tidyr, bipartite, crayon, dplyr, ggplot2, igraph,
purrr, skimr, bnstruct, RColorBrewer, fpc, mice, missMDA,
networkD3, scales, softImpute, tibble, tidytext, visNetwork,

person("Mohieddin", "Jafari", role = c("aut","cre"),email = "mohieddin.jafari@helsinki.fi"),
person("Cheng", "Chen", role = c("aut"),email = "cheng.chen@helsinki.fi")

Title: Fast and Accurate Trisomy Prediction in Non-Invasive Prenatal
Description: Fast and accurate trisomy prediction in non-invasive prenatal
Imports: stats, Rsamtools, sets, S4Vectors
Packaged: 2015-11-06 12:30:38 UTC; dirkdeweerd

Author: Dirk de Weerd, Lennart Johansson
Packaged: 2016-01-02 17:20:13 UTC; ljohansson

Description: Fast and Accurate Trisomy Prediction in Non-Invasive Prenatal
Packaged: 2016-03-09 14:02:38 UTC; ljohansson

Title: Novel Statistical Methods for Studying Near-Infrared
Depends: R (>= 3.1.0), ggplot2, mgcv, gridExtra
Description: Provides transfusion-related differential tests on Near-infrared spectroscopy (NIRS) time series with detection limit, which contains two testing statistics: Mean Area Under the Curve (MAUC) and slope statistic. This package applied a penalized spline method within an imputation setting. Testing is conducted by a nested permutation approach within imputation. Refer to Guo et al (2018) <arXiv:1801.08153> for further details.

Author: Yikai Wang [Emory University], Xiao Wang [ICF]
Description: Provides transfusion-related differential tests on Near-infrared spectroscopy (NIRS) time series with detection limit, which contains two testing statistics: Mean Area Under the Curve (MAUC) and slope statistic. This package applied a penalized spline method within imputation setting. Testing is conducted by a nested permutation approach within imputation. Refer to Guo et al (2018) <doi:10.1177/0962280218786302> for further details.