Package: garma 0.9.23
Richard Hunt
garma: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Methods for estimating univariate long memory-seasonal/cyclical Gegenbauer time series processes. See for example (2022) <doi:10.1007/s00362-022-01290-3>. Refer to the vignette for details of fitting these processes.
Authors:
garma_0.9.23.tar.gz
garma_0.9.23.zip(r-4.5)garma_0.9.23.zip(r-4.4)garma_0.9.23.zip(r-4.3)
garma_0.9.23.tgz(r-4.4-any)garma_0.9.23.tgz(r-4.3-any)
garma_0.9.23.tar.gz(r-4.5-noble)garma_0.9.23.tar.gz(r-4.4-noble)
garma_0.9.23.tgz(r-4.4-emscripten)garma_0.9.23.tgz(r-4.3-emscripten)
garma.pdf |garma.html✨
garma/json (API)
NEWS
| # Install 'garma' in R: |
| install.packages('garma', repos = c('https://rlph50.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rlph50/garma/issues
Last updated 2 months agofrom:ef1f3c2fe7. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 12 2024 |
| R-4.5-win | OK | Nov 12 2024 |
| R-4.5-linux | OK | Nov 12 2024 |
| R-4.4-win | OK | Nov 12 2024 |
| R-4.4-mac | OK | Nov 12 2024 |
| R-4.3-win | OK | Nov 12 2024 |
| R-4.3-mac | OK | Nov 12 2024 |
Exports:extract_armagarmagarma_ggtsdisplaygg_raw_pgramggbr_semiparagof
Dependencies:clicolorspacecpp11crayoncurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestlubridatemagrittrMASSMatrixmgcvmunsellnlmenloptrnnetpillarpkgconfigpracmaquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangRsolnpscalessignaltibbletimechangetimeDatetruncnormtseriesTTRurcautf8vctrsviridisLitewithrxtszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| AIC for model | AIC.garma_model |
| ggplot of the Forecasts of the model. | autoplot.garma_model |
| Model Coefficients | coef.garma_model |
| Extract underlying ARMA process. | extract_arma |
| Extract fitted values | fitted.garma_model |
| Forecast future values. | forecast.garma_model |
| garma: A package for estimating and foreasting Gegenbauer time series models. | garma-package garma |
| ggtsdisplay of underlying ARMA process. | garma_ggtsdisplay |
| Display raw periodogram | gg_raw_pgram |
| Extract semiparametric estimates of the Gegenbauer factors. | ggbr_semipara |
| Goodness-of-Fit test for a garma_model. | gof |
| Log Likelihood | logLik.garma_model |
| Plot Forecasts from model. | plot.garma_model |
| Predict future values. | predict.garma_model |
| print a garma_model object. | print.garma_model |
| Print a 'ggbr_factors' object. | print.ggbr_factors |
| Residuals | residuals.garma_model |
| summarise a garma_model object. | summary.garma_model |
| Diagnostic fit of a garma_model. | tsdiag.garma_model |
| Covariance matrix | vcov.garma_model |