Packaged: 2014-10-02 13:24:24 UTC; dusadrian

Imports: admisc, haven, readr, tibble, xml2
Packaged: 2019-04-26 22:20:11 UTC; dusadrian

Imports: admisc (>= 0.4), haven, readr, tibble, xml2
Packaged: 2019-09-15 20:58:12 UTC; dusadrian

Imports: admisc (>= 0.12), haven, readr, tibble, tools, xml2
Packaged: 2021-03-24 14:00:16 UTC; dusadrian

Imports: admisc (>= 0.16), readr, declared, haven, tools, xml2, readxl,
Packaged: 2021-06-25 09:00:58 UTC; dusadrian

Imports: admisc (>= 0.17), readr, declared (>= 0.6), haven, tools,
Packaged: 2021-08-19 18:45:20 UTC; dusadrian

Imports: admisc (> 0.17), readr, declared (> 0.6), haven, tools, xml2,
Packaged: 2021-09-02 19:22:10 UTC; dusadrian

Imports: admisc (> 0.19), readr, declared (> 0.6), haven, tools, xml2,
Packaged: 2021-11-30 09:51:24 UTC; dusadrian

person("Domagoj", "Ćevid", email = "cevid@stat.math.ethz.ch", role = c("aut")),
person("Chengzhu", "Huang", email="czhuang0710@gmail.com", role = c("aut")),
person("Zijian", "Guo", email = "zijguo@stat.rutgers.edu", role = c("aut","cre")),
person("Peter", "Bühlmann", email = "buhlmann@stat.math.ethz.ch", role = c("aut")))
Description: Statistical inference for the regression coefficients in high-dimensional linear models with hidden confounders. The Doubly Debiased Lasso method was proposed in <arXiv:2004.03758>.

Title: Death Registration Coverage Estimation
Author: Tim Riffe, Everton Lima, Bernardo Queiroz
Description: A set of three two-census methods to the estimate the degree of death registration coverage for a population. Implemented methods include the Generalized Growth Balance method (GGB), the Synthetic Extinct Generation method (SEG), and a hybrid of the two, GGB-SEG. Each method offers automatic estimation, but users may also specify exact parameters or use a graphical interface to guess parameters in the traditional way if desired.

Author: William Hua <whua4@jhu.edu>, Yanxun Xu <yanxun.xu@jhu.edu>
Description: A nonparametric Bayesian approach to survival analysis. The functions perform inference via MCMC simulations from the posterior distributions for a Dependent Dirichlet Process-Gaussian Process prior. To maximize computational efficiency, some of the computations are performed in 'Rcpp'.
Imports: Rcpp (>= 0.12.11), MASS, survival, mc2d, mvnfast