Approximate conditional inference for logistic and loglinear
models
S original by Alessandra R. Brazzale
<alessandra.brazzale@unimore.it>. R port by Alessandra R.
Brazzale <alessandra.brazzale@unimore.it>, following earlier
work by Douglas Bates.
Higher order likelihood-based inference for logistic and
loglinear models

S original by Alessandra R. Brazzale <alessandra.brazzale@unipd.it>.
R port by Alessandra R. Brazzale <alessandra.brazzale@unipd.it>, following
earlier work by Douglas Bates.

Approximate Conditional Inference for Logistic and Loglinear
Models
Higher order likelihood-based inference for logistic and
loglinear models.

Parameter estimation in conditional GEE for recurrent event gap
times
Solves for the mean parameters, the variance parameter,
and their asymptotic variance in a conditional GEE for
recurrent event gap times, as described by Clement and
Strawderman (2009) in the journal Biostatistics. Makes a
parametric assumption for the length of the censored gap time.

Solves for the mean parameters, the variance parameter, and their asymptotic variance in a conditional GEE for recurrent event gap times, as described by Clement and Strawderman (2009) in the journal Biostatistics. Makes a parametric assumption for the length of the censored gap time.

Parameter Estimation in Conditional GEE for Recurrent Event Gap
Times

c(person("Ravi", "Varadhan", role = c("aut", "cre"),
email = "ravi.varadhan@jhu.edu"))
Computes conditional multivariate normal probabilities, random deviates and densities.

Computes conditional multivariate normal densities, probabilities, and random deviates.

Estimation of the Conditional Survival Function for Ordered
Multivariate Failure Time Data
Method to implement some newly developed methods for the
estimation of the conditional survival function.
KernSmooth, doParallel, parallel, doRNG, foreach

KernSmooth, np, survival, doParallel, parallel, doRNG, foreach

Conditional Truncated Multivariate Normal Distribution
person("Paul M.", "Hargarten",
email = "hargartenp@vcu.edu",
role = c("aut", "cre"))
Computes the density and probability for the conditional truncated multivariate normal (Horrace (2005) p. 4, <doi:10.1016/j.jmva.2004.10.007>). Also draws random samples from this distribution.
formatR, knitr, rmarkdown, roxygen2, sessioninfo, spelling,
testthat