# 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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