Last updated on 2025-04-28 00:50:24 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.9.1 | 11.15 | 100.23 | 111.38 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 1.9.1 | 8.73 | 74.42 | 83.15 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 1.9.1 | 174.23 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 1.9.1 | 167.47 | NOTE | |||
| r-devel-windows-x86_64 | 1.9.1 | 14.00 | 118.00 | 132.00 | NOTE | |
| r-patched-linux-x86_64 | 1.9.1 | 12.67 | 98.42 | 111.09 | NOTE | |
| r-release-linux-x86_64 | 1.9.1 | 11.11 | 98.54 | 109.65 | NOTE | |
| r-release-macos-arm64 | 1.9.1 | 58.00 | NOTE | |||
| r-release-macos-x86_64 | 1.9.1 | 94.00 | NOTE | |||
| r-release-windows-x86_64 | 1.9.1 | 15.00 | 119.00 | 134.00 | NOTE | |
| r-oldrel-macos-arm64 | 1.9.1 | 49.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 1.9.1 | 80.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 1.9.1 | 17.00 | 147.00 | 164.00 | NOTE |
Version: 1.9.1
Check: Rd files
Result: NOTE
checkRd: (-1) ivmodel.Rd:37: Lost braces
37 | and produces statistics for \eqn{\beta}. In particular, \code{ivmodel} computes the OLS, TSLS, k-class, limited information maximum likelihood (LIML), and Fuller-k (Fuller 1977) estimates of \eqn{\beta} using \code{KClass}, \code{LIML}, and code{Fuller}. Also, \code{ivmodel} computes confidence intervals and hypothesis tests of the type \eqn{H_0: \beta = \beta_0} versus \eqn{H_0: \beta \neq \beta_0} for the said estimators as well as two weak-IV confidence intervals, Anderson and Rubin (Anderson and Rubin 1949) confidence interval (Anderson and Rubin 1949) and the conditional likelihood ratio confidence interval (Moreira 2003). Finally, the code also conducts a sensitivity analysis if \eqn{Z} is one-dimensional (i.e. there is only one instrument) using the method in Jiang et al. (2015).
| ^
checkRd: (-1) ivmodelFormula.Rd:42: Lost braces
42 | and produces statistics for \eqn{\beta}. In particular, \code{ivmodel} computes the OLS, TSLS, k-class, limited information maximum likelihood (LIML), and Fuller-k (Fuller 1977) estimates of \eqn{\beta} using \code{KClass}, \code{LIML}, and code{Fuller}. Also, \code{ivmodel} computes confidence intervals and hypothesis tests of the type \eqn{H_0: \beta = \beta_0} versus \eqn{H_0: \beta \neq \beta_0} for the said estimators as well as two weak-IV confidence intervals, Anderson and Rubin (Anderson and Rubin 1949) confidence interval (Anderson and Rubin 1949) and the conditional likelihood ratio confidence interval (Moreira 2003). Finally, the code also conducts a sensitivity analysis if \eqn{Z} is one-dimensional (i.e. there is only one instrument) using the method in Jiang et al. (2015).
| ^
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 1.9.1
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Hyunseung Kang <hyunseung@stat.wisc.edu>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Hyunseung",
family = "Kang",
role = c("aut", "cre"),
email = "hyunseung@stat.wisc.edu"),
person(given = "Yang",
family = "Jiang",
role = "aut"),
person(given = "Qingyuan",
family = "Zhao",
role = "aut"),
person(given = "Dylan",
family = "Small",
role = "aut"))
as necessary.
Flavor: r-devel-linux-x86_64-debian-gcc