Packaged: 2014-11-24 18:46:01 UTC; Kevin_Jakob

Description: Analyze the default risk of credit portfolios. Commonly known models,
Imports: Rcpp (>= 0.11.2), methods, RcppProgress(>= 0.1), parallel

Title: Implements Generic Composite Similarity Measure
Description: Provides implementation of the generic composite similarity measure
(GCSM) described in Liu et al. (2020) <doi:10.1016/j.ecoinf.2020.101169>. The
implementation is in C++ and uses 'RcppArmadillo'. Additionally, implementations
of the structural similarity (SSIM) and the composite similarity measure based
on means, standard deviations, and correlation coefficient (CMSC), are included.
Author: Yadong Liu [aut, cre] (<https://orcid.org/0000-0002-1283-3451>)

Title: A Data Manipulation and Analysis Package for Calcium Indicator
Description: Provides shortcuts in extracting useful data points and summarizing waveform data. It is optimized for speed to work efficiently with large data sets so you can get to the analysis phase more quickly. It also utilizes a user-friendly format for use by both beginners and seasoned R users.
Imports: stats, graphics, caTools, dplyr

Title: Simple Peak Alignment for Gas-Chromatography Data
Authors@R: c(person("Martin", "Stoffel", email = "martin.adam.stoffel@gmail.com", role = c("aut")),
person("Meinolf", "Ottensmann", email = "meinolf.ottensmann@web.de", role = c("aut","cre")),
person("Joseph I.", "Hoffman", email = "j_i_hoffman@hotmail.com", role = c("aut")))
Description: Aligns chromatography peaks with a three step algorithm: (1) Linear
transformation of retention times to maximise shared peaks among samples
(2) Align peaks within a certain error-interval (3) Merges rows that are likely
representing the same substance (i.e. no sample shows peaks in both rows and
the rows have similar retention time means).
The method was first described in Stoffel et al. (2015) <doi:10.1073/pnas.1506076112>.
Imports: ggplot2 (>= 2.2.1), graphics, stats, readr, reshape2, stringr,
Suggests: knitr, pander, rmarkdown, testthat, vegan (>= 2.4.2)