Package: PDMIF 0.1.0
PDMIF: Fits Heterogeneous Panel Data Models
Fits heterogeneous panel data models with interactive effects for linear regression, logistic, count, probit, quantile, and clustering. Based on Ando, T. and Bai, J. (2015) "A simple new test for slope homogeneity in panel data models with interactive effects" <doi:10.1016/j.econlet.2015.09.019>, Ando, T. and Bai, J. (2015) "Asset Pricing with a General Multifactor Structure" <doi:10.1093/jjfinex/nbu026> , Ando, T. and Bai, J. (2016) "Panel data models with grouped factor structure under unknown group membership" <doi:10.1002/jae.2467>, Ando, T. and Bai, J. (2017) "Clustering huge number of financial time series: A panel data approach with high-dimensional predictors and factor structures" <doi:10.1080/01621459.2016.1195743>, Ando, T. and Bai, J. (2020) "Quantile co-movement in financial markets" <doi:10.1080/01621459.2018.1543598>, Ando, T., Bai, J. and Li, K. (2021) "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity" <doi:10.1016/j.jeconom.2020.11.013.>.
Authors:
PDMIF_0.1.0.tar.gz
PDMIF_0.1.0.zip(r-4.7)PDMIF_0.1.0.zip(r-4.6)PDMIF_0.1.0.zip(r-4.5)
PDMIF_0.1.0.tgz(r-4.6-any)PDMIF_0.1.0.tgz(r-4.5-any)
PDMIF_0.1.0.tar.gz(r-4.7-any)PDMIF_0.1.0.tar.gz(r-4.6-any)
PDMIF_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
PDMIF/json (API)
| # Install 'PDMIF' in R: |
| install.packages('PDMIF', repos = c('https://tomohiro-ando.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tomohiro-ando/pdmif/issues
- data1X - A synthesized input variable dataset to fit a linear model on a panel dataset.
- data1Y - A synthesized output variable dataset to fit a linear model on a panel dataset.
- data2X - A synthesized input variable dataset to fit a binomial model on a panel dataset.
- data2Y - A synthesized output variable dataset to fit a binomial model on a panel dataset.
- data3X - A synthesized input variable dataset to fit a poisson model on a panel dataset.
- data3Y - A synthesized output variable dataset to fit a poisson model on a panel dataset.
- data4LAB - A synthesized vector of memberships needed to fit a linear model on a panel dataset under known group memberships.
- data4X - A synthesized input variable dataset to fit a linear model on a panel dataset under known group memberships.
- data4Y - A synthesized output variable dataset to fit a linear model on a panel dataset under known group memberships.
- data5X - A synthesized input variable dataset to cluster individuals by heterogeneous panel data models with interactive effects.
- data5Y - A synthesized output variable dataset to cluster individuals by heterogeneous panel data models with interactive effects.
- data6X - A synthesized input variable dataset to cluster individual units by nonlinear heterogeneous panel data models with interactive effects when the group membership is unknown
- data6Y - A synthesized output variable dataset to cluster individual units by nonlinear heterogeneous panel data models with interactive effects when the group membership is unknown.
- data7X - A synthesized input variable dataset to fit a quantile panel data model on a panel dataset.
- data7Y - A synthesized output variable dataset to fit a quantile panel data model on a panel dataset.
- data8Y - A synthesized output variable dataset to fit a quantile VAR model with interactive effects and lag=2.
Last updated from:3a275ee7e2. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 119 | ||
| source / vignettes | OK | 142 | ||
| linux-release-x86_64 | NOTE | 118 | ||
| macos-release-arm64 | NOTE | 162 | ||
| macos-oldrel-arm64 | NOTE | 204 | ||
| windows-devel | NOTE | 88 | ||
| windows-release | NOTE | 99 | ||
| windows-oldrel | NOTE | 86 | ||
| wasm-release | OK | 98 |
Exports:HOMTESTHOMTESTGLMHYPTESTPDMIFCLUSTPDMIFCLUSTGLMPDMIFCOUNTPDMIFGLMPDMIFLINPDMIFLINGPDMIFLOGITPDMIFPROBITPDMIFQUANTILEPDMIFQVAR
Dependencies:diagonalslatticeMASSMatrixMatrixModelsncvregquantregSparseMsurvival
