Package: GrangerRKHS 0.1.0
GrangerRKHS: RKHS-Based Nonlinear Granger Causality Testing via Conditional Centering
Provides methods for nonlinear Granger causality testing in reproducing kernel Hilbert space (RKHS), using kernel ridge regression for conditional mean estimation and conditional centering for construction of the test statistic.
Authors:
GrangerRKHS_0.1.0.tar.gz
GrangerRKHS_0.1.0.zip(r-4.7-any)GrangerRKHS_0.1.0.zip(r-4.6-any)GrangerRKHS_0.1.0.zip(r-4.5-any)
GrangerRKHS_0.1.0.tgz(r-4.6-any)GrangerRKHS_0.1.0.tgz(r-4.5-any)
GrangerRKHS_0.1.0.tar.gz(r-4.7-any)GrangerRKHS_0.1.0.tar.gz(r-4.6-any)
GrangerRKHS_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
GrangerRKHS/json (API)
| # Install 'GrangerRKHS' in R: |
| install.packages('GrangerRKHS', repos = c('https://helloworld9293.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:3e567ef44f. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 101 | ||
| source / vignettes | OK | 121 | ||
| linux-release | OK | 92 | ||
| macos-release | OK | 85 | ||
| macos-oldrel | OK | 107 | ||
| windows-devel | OK | 58 | ||
| windows-release | OK | 47 | ||
| windows-oldrel | OK | 61 | ||
| wasm-release | OK | 81 |
Exports:gc_sigma2_hat_null_exactgranger_rkhskernel_gaussian_taukernel_gramlagged_designnlVAR_sim
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Estimate Innovation Variance Under the Null Model | gc_sigma2_hat_null_exact |
| Nonlinear Granger Causality Test via Conditional Centering in RKHS | granger_rkhs |
| Gaussian Kernel with Bandwidth Parameter | kernel_gaussian_tau |
| Construct an Empirical Kernel (Gram) Matrix | kernel_gram |
| Construct Lagged Design Matrix for VAR Models | lagged_design |
| Simulate a Nonlinear Vector Autoregressive Process | nlVAR_sim |