Imports: stats, cubature, tmvtnorm, ggplot2, glm2, magrittr, dplyr,
plyr, pracma, foreach, parallel, doParallel, utils,
Packaged: 2018-01-03 11:29:38 UTC; eduardgrebe

Imports: stats, utils, magrittr, rlang, dplyr, tibble, cubature,
tmvtnorm, ggplot2, glm2, plyr, pracma, foreach, parallel,
Packaged: 2018-09-21 22:19:07 UTC; eduardgrebe

sectional surveys and for calibrating tests for recent infection.
Imports: stats, utils, cubature, ggplot2, glm2, MASS, plyr, pracma,
Packaged: 2016-05-18 11:05:01 UTC; eduardgrebe

Packaged: 2016-05-26 09:52:06 UTC; eduardgrebe

Imports: stats, cubature, ggplot2, glm2, MASS, plyr, pracma, foreach,
Packaged: 2016-09-13 11:41:51 UTC; eduardgrebe

Title: Parametric Time-to-Event Analysis with Variable Incubation
Description: Fit parametric models for time-to-event data that show an initial
'incubation period', i.e., a variable phase where the hazard is zero. The
delayed Weibull distribution serves as the foundational data model. The
specific method of MSE (maximum spacing estimation) is used for parameter
estimation. Bootstrap confidence intervals for parameters and significance
tests in a two group setting are provided.
Imports: future (>= 1.21), future.apply (>= 1.6), ggplot2 (>= 3.3),
Suggests: boot, cowplot, future.callr, knitr, testthat (>= 3.0.0)
Author: Matthias Kuhn [aut, cre] (<https://orcid.org/0000-0003-2868-5155>)

'incubation period', i.e., a variable delay phase where the hazard is zero. The
specific method of 'MPSE' (maximum product of spacings estimation) is used for parameter
Imports: future (>= 1.21), future.apply (>= 1.6), glue (>= 1.4), MASS,
purrr (>= 0.3), rlang (>= 0.4), stats, survival, tibble
Suggests: boot, future.callr, ggplot2 (>= 3.3), knitr, testthat (>=

Title: Insertion Deletion Analysis While Accounting for Possible
Author: Utkarsh J. Dang and G. Brian Golding
Maintainer: Utkarsh J. Dang <udang@binghamton.edu>
Description: Genome-wide gene insertion and deletion rates can be modelled in a maximum
likelihood framework with the additional flexibility of modelling potential missing
data using the models included within. These models simultaneously estimate insertion
and deletion (indel) rates of gene families and proportions of "missing" data for
(multiple) taxa of interest. The likelihood framework is utilized for parameter
estimation. A phylogenetic tree of the taxa and gene presence/absence patterns
(with data ordered by the tips of the tree) are required. For more details, see
Utkarsh J. Dang, Alison M. Devault, Tatum D. Mortimer, Caitlin S. Pepperell,
Hendrik N. Poinar, G. Brian Golding (2016). Gene insertion deletion analysis
while accounting for possible missing data. Genetics (accepted).