ftsa v5.5
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Functional Time Series Analysis
Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.
Functions in ftsa
| Name | Description | |
| centre | Mean function, variance function, median function, trim mean function of functional data | |
| diff.fts | Differences of a functional time series | |
| plot.ftsf | Plot fitted model components for a functional time series model | |
| T_stationary | Testing stationarity of functional time series | |
| MFDM | Multilevel functional data method | |
| ftsa-package | Functional Time Series Analysis | |
| ftsm | Fit functional time series model | |
| extract | Extract variables or observations | |
| facf | Functional autocorrelation function | |
| is.fts | Test for functional time series | |
| hd_data | Simulated high-dimensional functional time series | |
| ftsmiterativeforecasts | Forecast functional time series | |
| hdfpca | High-dimensional functional principal component analysis | |
| ftsmweightselect | Selection of the weight parameter used in the weighted functional time series model. | |
| pm_10_GR | Particulate Matter Concentrations (pm10) | |
| isfe.fts | Integrated Squared Forecast Error for models of various orders | |
| quantile | Quantile | |
| sim_ex_cluster | Simulated multiple sets of functional time series | |
| quantile.fts | Quantile functions for functional time series | |
| residuals.fm | Compute residuals from a functional model | |
| summary.fm | Summary for functional time series model | |
| dmfpca | Dynamic multilevel functional principal component analysis | |
| dynamic_FLR | Dynamic updates via functional linear regression | |
| pcscorebootstrapdata | Bootstrap independent and identically distributed functional data or functional time series | |
| forecastfplsr | Forecast functional time series | |
| fplsr | Functional partial least squares regression | |
| median.fts | Median functions for functional time series | |
| plot.fm | Plot fitted model components for a functional model | |
| sd.fts | Standard deviation functions for functional time series | |
| sd | Standard deviation | |
| mftsc | Clustering multiple functional time series | |
| var | Variance | |
| var.fts | Variance functions for functional time series | |
| farforecast | Functional data forecasting through functional principal component autoregression | |
| fbootstrap | Bootstrap independent and identically distributed functional data | |
| long_run_covariance_estimation | Estimating long-run covariance function for a functional time series | |
| mean.fts | Mean functions for functional time series | |
| plot.ftsm | Plot fitted model components for a functional time series model | |
| plotfplsr | Plot fitted model components for a functional time series model | |
| dynupdate | Dynamic updates via BM, OLS, RR and PLS methods | |
| error | Forecast error measure | |
| forecast.ftsm | Forecast functional time series | |
| forecast.hdfpca | Forecasting via a high-dimensional functional principal component regression | |
| plot.fmres | Plot residuals from a fitted functional model. | |
| No Results! | ||
Vignettes of ftsa
| Name | ||
| KokoszkaShang.bib | ||
| ftsa.Rnw | ||
| ftsa_test.Rnw | ||
| ibm.pdf | ||
| master.bib | ||
| pm10.pdf | ||
| pm10_ftsm.pdf | ||
| No Results! | ||
Last month downloads
Details
| Type | Package |
| Date | 2019-4-16 |
| LazyLoad | yes |
| LazyData | yes |
| ByteCompile | TRUE |
| License | GPL-3 |
| NeedsCompilation | no |
| Packaged | 2019-04-16 01:52:26 UTC; hanlinshang |
| Repository | CRAN |
| Date/Publication | 2019-04-21 15:10:06 UTC |
| imports | colorspace , fda , MASS , pcaPP , pdfCluster |
| suggests | fds , meboot , R2jags , vars |
| depends | forecast , R (>= 3.4.0) , rainbow , sde |
| Contributors | Rob Hyndman |
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