c(person(c("Ilya", "Y."), "Zhbannikov", email = "ilya.zhbannikov@duke.edu", role = c("aut", "cre")))

Diagnostic Plot and Multivariate Summary Statistics of Weighted
Samples from Importance Sampling
Fast functions for effective sample size, weighted multivariate mean and variance computation,
and weight diagnostic plot for generic importance sampling type results.

Rcpp (>= 0.12.7), ggplot2 (>= 2.1.0), gridExtra, coda

Fast functions for effective sample size, weighted multivariate
mean, variance, and quantile computation, and weight diagnostic plot for
generic importance sampling type or other probability weighted samples.
coda, ggplot2 (>= 2.1.0), gridExtra, Rcpp (>= 0.12.7)

Meta-Analysis of Diagnostic Accuracy Studies with Several
Cutpoints
c(person("Gerta","Rücker", role="aut"),
person("Susanne","Steinhauser", role="aut"),
person("Srinath","Kolampally", role="aut"),
person("Guido","Schwarzer", email="sc@imbi.uni-freiburg.de", role=c("aut","cre")))
Gerta Rücker [aut],
Susanne Steinhauser [aut],
Srinath Kolampally [aut],
Guido Schwarzer [aut, cre]
Provides methods by Steinhauser et al. (2016) <DOI:10.1186/s12874-016-0196-1> for meta-analysis of diagnostic accuracy studies with several cutpoints.

c(person("Gerta", "Rücker",
role = "aut",
comment = c(ORCID = "0000-0002-2192-2560")),
person("Susanne", "Steinhauser",
role = "aut"),
person("Srinath", "Kolampally",
role = "aut"),
person("Guido", "Schwarzer",
role = c("aut", "cre"),
email = "sc@imbi.uni-freiburg.de",
comment = c(ORCID = "0000-0001-6214-9087")))
Gerta Rücker [aut] (<https://orcid.org/0000-0002-2192-2560>),
Susanne Steinhauser [aut],
Srinath Kolampally [aut],
Guido Schwarzer [aut, cre] (<https://orcid.org/0000-0001-6214-9087>)

Block Diagonal Extraction or Replacement
person("Bastiaan", "Quast", email = "bquast@gmail.com", role = c("aut", "cre"))
Several tools for handling block-matrix diagonals and similar constructs are implemented. Block-diagonal matrices can be extracted or removed using two small functions implemented here. In addition, non-square matrices are supported. Block diagonal matrices occur when two dimensions of a data set are combined along one edge of a matrix. For example, trade-flow data in the 'decompr' and 'gvc' packages have each country-industry combination occur along both edges of the matrix.