Package: Blend 0.1.0
Kun Fan
Blend: Bayesian Longitudinal Regularized Semiparametric Quantile Mixed Models
Our recently developed fully Bayesian semiparametric quantile mixed-effect model for high-dimensional longitudinal studies with heterogeneous observations can be implemented through this package. This model can distinguish between time-varying interactions and constant-effect-only cases to avoid model misspecifications. Facilitated by spike-and-slab priors, this model leads to superior performance in estimation, identification and statistical inference. In particular, robust Bayesian inferences in terms of valid Bayesian credible intervals on both parametric and nonparametric effects can be validated on finite samples. The Markov chain Monte Carlo algorithms of the proposed and alternative models are efficiently implemented in 'C++'.
Authors:
Blend_0.1.0.tar.gz
Blend_0.1.0.tar.gz(r-4.5-noble)Blend_0.1.0.tar.gz(r-4.4-noble)
Blend_0.1.0.tgz(r-4.4-emscripten)Blend_0.1.0.tgz(r-4.3-emscripten)
Blend.pdf |Blend.html✨
Blend/json (API)
| # Install 'Blend' in R: |
| install.packages('Blend', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kunfa/blend/issues
- J - Simulated data for demonstrating the features of Blend
- degree - Simulated data for demonstrating the features of Blend
- kn - Simulated data for demonstrating the features of Blend
- t - Simulated data for demonstrating the features of Blend
- x - Simulated data for demonstrating the features of Blend
- y - Simulated data for demonstrating the features of Blend
Last updated 1 months agofrom:29355a178b. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 25 2024 |
| R-4.5-linux-x86_64 | OK | Dec 25 2024 |
Exports:BlendCoverageplot_Blendselection
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Longitudinal Regularized Semiparametric Quantile Mixed Model | Blend-package |
| fit a Bayesian longitudinal regularized semi-parametric quantile mixed model | Blend |
| 95% coverage for a Blend object with structural identification | Coverage |
| simulated data for demonstrating the features of Blend | data degree J kn t x y |
| plot a Blend object | plot_Blend |
| Variable selection for a Blend object | selection |
