Package: varjmcm 0.1.1

Naimin Jing

varjmcm: Estimations for the Covariance of Estimated Parameters in Joint Mean-Covariance Models

The goal of the package is to equip the 'jmcm' package (current version 0.2.1) with estimations of the covariance of estimated parameters. Two methods are provided. The first method is to use the inverse of estimated Fisher's information matrix, see M. Pourahmadi (2000) <doi:10.1093/biomet/87.2.425>, M. Maadooliat, M. Pourahmadi and J. Z. Huang (2013) <doi:10.1007/s11222-011-9284-6>, and W. Zhang, C. Leng, C. Tang (2015) <doi:10.1111/rssb.12065>. The second method is bootstrap based, see Liu, R.Y. (1988) <doi:10.1214/aos/1176351062> for reference.

Authors:Naimin Jing [aut, cre], Hexin Bai [aut], Tong Wang [aut], Cheng Yong Tang [aut]

varjmcm_0.1.1.tar.gz
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varjmcm.pdf |varjmcm.html✨
varjmcm/json (API)
NEWS

# Install 'varjmcm' in R:
install.packages('varjmcm', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 130 downloads 5 exports 9 dependencies

Last updated 5 years agofrom:deadc2807c. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-linuxOKMar 17 2025

Exports:bootcovjmcmcovjmcmcovjmcm_acdcovjmcm_hpccovjmcm_mcd

Dependencies:expmFormulajmcmlatticeMASSMatrixRcppRcppArmadilloroptim

Citation

To cite package ‘varjmcm’ in publications use:

Jing N, Bai H, Wang T, Tang C (2020). varjmcm: Estimations for the Covariance of Estimated Parameters in Joint Mean-Covariance Models. R package version 0.1.1, https://CRAN.R-project.org/package=varjmcm.

Corresponding BibTeX entry: 

  @Manual{,
    title = {varjmcm: Estimations for the Covariance of Estimated
      Parameters in Joint Mean-Covariance Models},
    author = {Naimin Jing and Hexin Bai and Tong Wang and Cheng Yong
      Tang},
    year = {2020},
    note = {R package version 0.1.1},
    url = {https://CRAN.R-project.org/package=varjmcm},
  }

Readme and manuals

varjmcm

The goal of varjmcm is to equip 'jmcm' package with estimations of the covariance of estimated parameters. Two methods are provided. The first method is bootstrap based. The second method is to use the inverse of estimated Fisher's information matrix as the estimated covariance.

The bootstrap method may need large number of replications and thus may be very time consuming, especially for the HPC model. The explicit formula in the second method is asymptotically correct, and thus is valid only when the sample size is large. When the sample size is large, the second method is a better choice. Results from these two methods are close to each other if both the number of replications and the sample size are large, otherwise, they may be very different.

The current version of the 'jmcm' package is 0.1.8.0. The 'varjmcm' package is based on this version of 'jmcm'. For further versions of 'jmcm', updates in 'varjmcm' may be needed.

Example

This is a basic example.

## cattleA <- cattle[cattle$group=='A', ]
## fit.mcd <- jmcm(weight|id|I(ceiling(day/14+1))~1|1,
                data = cattleA,
                cov.method = "mcd",
                triple = c(8,4,3))
## covjmcm(fit.mcd)
## bootcovjmcm(fit.mcd, 
               mydata = cattleA, 
               numboot = 100)