Packaged: 2022-08-28 22:39:50 UTC; Weksi Budiaji

Title: Fast K-Mer Counting and Clustering for Biological Sequence
Authors@R: person("Shaun", "Wilkinson", role = c("aut", "cre"),
Description: Contains tools for rapidly computing distance matrices
and clustering large sequence datasets using fast alignment-free
k-mer counting and recursive k-means partitioning.
See Vinga and Almeida (2003) <doi:10.1093/bioinformatics/btg005>
for a review of k-mer counting methods and applications for
Imports: openssl, phylogram, Rcpp (>= 0.12.13), stats

Imports: openssl, phylogram, Rcpp (>= 0.12.13)
Suggests: ape (>= 4.0), dendextend, knitr, rmarkdown, testthat

Title: Kaplan-Meier multiple imputation for the analysis of cumulative
incidence functions in the competing risks setting
Description: The package performs a Kaplan-Meier multiple imputation to
recover the missing potential censoring information from
competing risks events, so that standard right-censored methods
could be applied to the imputed data sets to perform analyses

Description: The package performs a Kaplan-Meier multiple imputation to recover the missing potential censoring information from competing risks events, so that standard right-censored methods could be applied to the imputed data sets to perform analyses of the cumulative incidence functions.

Title: Kaplan-Meier Multiple Imputation for the Analysis of Cumulative
Incidence Functions in the Competing Risks Setting
Description: The kmi package performs a Kaplan-Meier multiple imputation to recover the missing potential censoring information from competing risks events, so that standard right-censored methods could be applied to the imputed data sets to perform analyses of the cumulative incidence functions.

Description: Performs a Kaplan-Meier multiple imputation to recover the missing potential censoring information from competing risks events, so that standard right-censored methods could be applied to the imputed data sets to perform analyses of the cumulative incidence functions (Allignol and Beyersmann, 2010 <doi:10.1093/biostatistics/kxq018>).