cranhaven. To fix this you can add URL: https://cranhaven.r-universe.dev/NlinTS to the package DESCRIPTION file. See also theR-universe documentation.Package: NlinTS 1.4.7
NlinTS: Models for Non Linear Causality Detection in Time Series
Models for non-linear time series analysis and causality detection. The main functionalities of this package consist of an implementation of the classical causality test (C.W.J.Granger 1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy <doi:10.1103/PhysRevLett.85.461>, and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors <doi:10.1103/PhysRevE.69.066138>. There are also some other useful tools, like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented test of stationarity, and the discrete and continuous entropy and mutual information.
Authors:
NlinTS_1.4.7.tar.gz
NlinTS_1.4.7.zip(r-4.7-x86_64)NlinTS_1.4.7.zip(r-4.7-arm64)NlinTS_1.4.7.zip(r-4.6-x86_64)NlinTS_1.4.7.zip(r-4.6-arm64)NlinTS_1.4.7.zip(r-4.5-x86_64)
NlinTS_1.4.7.tgz(r-4.6-x86_64)NlinTS_1.4.7.tgz(r-4.6-arm64)NlinTS_1.4.7.tgz(r-4.5-x86_64)NlinTS_1.4.7.tgz(r-4.5-arm64)
NlinTS_1.4.7.tar.gz(r-4.7-arm64)NlinTS_1.4.7.tar.gz(r-4.7-x86_64)NlinTS_1.4.7.tar.gz(r-4.6-arm64)NlinTS_1.4.7.tar.gz(r-4.6-x86_64)
NlinTS_1.4.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
NlinTS/json (API)
| # Install 'NlinTS' in R: |
| install.packages('NlinTS', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues
Last updated from:883f877736 (on package/NlinTS). Checks:15 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 141 | ||
| linux-devel-x86_64 | OK | 154 | ||
| source / vignettes | OK | 226 | ||
| linux-release-arm64 | OK | 132 | ||
| linux-release-x86_64 | OK | 154 | ||
| macos-release-arm64 | OK | 90 | ||
| macos-release-x86_64 | OK | 191 | ||
| macos-oldrel-arm64 | OK | 131 | ||
| macos-oldrel-x86_64 | OK | 551 | ||
| windows-devel-arm64 | OK | 262 | ||
| windows-devel-x86_64 | OK | 183 | ||
| windows-release-arm64 | OK | 205 | ||
| windows-release-x86_64 | OK | 123 | ||
| windows-oldrel-x86_64 | OK | 156 | ||
| wasm-release | OK | 135 |
Exports:causality.testdf.testentropy_contentropy_discmi_contmi_discmi_disc_binlin_causality.testte_contte_discvarmlp
Dependencies:rbibutilsRcppRdpacktimeDatetimeSeries
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Models for non-linear causality detection in time series. | NlinTS-package NlinTS |
| The Granger causality test | causality.test |
| Augmented Dickey_Fuller test | df.test |
| Continuous entropy | entropy_cont |
| Discrete Entropy | entropy_disc |
| Continuous Mutual Information | mi_cont |
| Discrete multivariate Mutual Information | mi_disc |
| Discrete bivariate Mutual Information | mi_disc_bi |
| A non linear Granger causality test | nlin_causality.test |
| Continuous Transfer Entropy | te_cont |
| Discrete Transfer Entropy | te_disc |
| Artificial Neural Network VAR (Vector Auto-Regressive) model using a MultiLayer Perceptron, with the sigmoid activation function. The optimization algorithm is based on the stochastic gradient descent. | varmlp |