ftsa: Functional Time Series Analysis

Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.

Install the latest version of this package by entering the following in R:
install.packages("ftsa")
AuthorRob J Hyndman and Han Lin Shang
Date of publication2017-04-25 07:42:50 UTC
MaintainerHan Lin Shang <hanlin.shang@anu.edu.au>
LicenseGPL (>= 2)
Version4.8

View on CRAN

Man pages

centre: Mean function, variance function, median function, trim mean...

diff.fts: Differences of a functional time series

dynamic_FLR: Dynamic updates via functional linear regression

dynupdate: Dynamic updates via BM, OLS, RR and PLS methods

error: Forecast error measure

extract: Extract variables or observations

farforecast: Functional data forecasting through functional principal...

fbootstrap: Bootstrap independent and identically distributed functional...

forecastfplsr: Forecast functional time series

forecast.ftsm: Forecast functional time series

fplsr: Functional partial least squares regression

ftsa-package: Functional Time Series Analysis

ftsm: Fit functional time series model

ftsmiterativeforecasts: Forecast functional time series

ftsmweightselect: Selection of the weight parameter used in the weighted...

isfe.fts: Integrated Squared Forecast Error for models of various...

is.fts: Test for functional time series

long_run_covariance_estimation: Estimating long-run covariance function for a functional time...

mean.fts: Mean functions for functional time series

median.fts: Median functions for functional time series

MFDM: Multilevel functional data method

pcscorebootstrapdata: Bootstrap independent and identically distributed functional...

plot.fm: Plot fitted model components for a functional model

plot.fmres: Plot residuals from a fitted functional model.

plotfplsr: Plot fitted model components for a functional time series...

plot.ftsf: Plot fitted model components for a functional time series...

plot.ftsm: Plot fitted model components for a functional time series...

pm_10_GR: Particulate Matter Concentrations (pm10)

quantile: Quantile

quantile.fts: Quantile functions for functional time series

residuals.fm: Compute residuals from a functional model

sd: Standard deviation

sd.fts: Standard deviation functions for functional time series

summary.fm: Summary for functional time series model

T_stationary: Testing stationarity of functional time series

var: Variance

var.fts: Variance functions for functional time series

Functions

centre Man page
diff.fts Man page
dynamic_FLR Man page
dynupdate Man page
error Man page
extract Man page
farforecast Man page
fbootstrap Man page
forecastfplsr Man page
forecast.ftsm Man page
fplsr Man page
ftsa Man page
ftsa-package Man page
ftsm Man page
ftsmiterativeforecasts Man page
ftsmweightselect Man page
isfe.fts Man page
is.fts Man page
long_run_covariance_estimation Man page
mean.fts Man page
median.fts Man page
MFDM Man page
pcscorebootstrapdata Man page
plot.fm Man page
plot.fmres Man page
plotfplsr Man page
plot.ftsf Man page
plot.ftsm Man page
pm_10_GR Man page
pm_10_GR_sqrt Man page
quantile Man page
quantile.fts Man page
residuals.fm Man page
sd Man page
sd.default Man page
sd.fts Man page
summary.fm Man page
T_stationary Man page
var Man page
var.default Man page
var.fts Man page

Files

inst
inst/CITATION
inst/doc
inst/doc/ftsa_test.pdf
inst/doc/ftsa.pdf
NAMESPACE
data
data/pm_10_GR.rda
data/pm_10_GR_sqrt.rda
R
R/func.med.RPD.R R/colQn.r R/pcscorebootstrapdata.R R/ftsmweightselect.R R/rmdspe.R R/sd.R R/diff.R R/rapca.r R/mape.R R/fplsrPI.R R/depth.FM.R R/ftsmiterativeforecasts.R R/struct.forecast.r R/dynupdate.R R/rstep.r R/me.R R/summary.fm.R R/var.R R/smdape.R R/plot.ftsm.R R/unitsimpls.R R/depth.mode.R R/nicerange.r R/relmse.R R/plsr.R R/sd.default.R R/hossjercroux.r R/nipals.R R/plotfplsr.R R/plsrPIs.R R/depth.RP.R R/mse.R R/print.fmres.R R/DataPostProc.r R/skernel.norm.R R/quantile.fts.R R/repmat.r R/wpcr.R R/rmse.R R/depth.RPD.R R/Long_run_covariance_estimation.r R/func.var.R R/depth.radius.R R/rmsse.R R/ScaleAdv.r R/print.ftsf.R R/mdrae.R R/median.fts.R R/L1median2.r R/mdae.R R/forecast.ftsm2.R R/func.mode.R R/fplsr.R R/smape.R R/func.trimvar.mode.R R/mean.fts.R R/mae.R R/simpls.R R/metri.p.r R/mdse.R R/func.trimvar.RPD.R R/ftsm.R R/func.med.mode.R R/plsPI.R R/func.mean.R R/fbootstrap.R R/error.R R/sd.fts.R R/func.trim.mode.R R/FlatTop.r R/MISE.r R/aveISFE.r R/mrobj.r R/center.R R/diff.default.R R/hyman.filter.r R/pegelsna.r R/mdase.R R/Qn.r R/var.default.R R/norm.r R/quantile.outliers.trim.R R/ParseDevString.r R/diff.fts.R R/relmae.R R/rmspe.R R/dynamic_FLR.R R/MFDM.R R/print.fm.R R/matrix.rank.r R/ParseControlStructure.r R/norme.r R/func.trim.RPD.R R/mpe.R R/extract.R R/spl.coef.conv.r R/print.ftsm.R R/mrae.R R/mdape.R R/Jacob.R R/extract.time.R R/forecastfplsr.R R/forecast.ftsm.R R/gmrae.R R/ftsmPI.R R/plsrPIsboot.R R/centre.R R/residuals.fm.R R/isfe.fts.r R/plot.fm.R R/T_stationary.R R/rw.drift.r R/plot.fmres.R R/farforecast.R R/loadSgnU.r R/quantile.outliers.pond.R R/kweights.r R/is.fts.R R/mase.R R/var.fts.R R/fdpca.R R/sse.R R/plot.ftsf.R R/extract.x.R
vignettes
vignettes/master.bib
vignettes/KokoszkaShang.bib
vignettes/ibm.pdf
vignettes/pm10.pdf
vignettes/ftsa_test.tex
vignettes/ftsa.Rnw
vignettes/ftsa.tex
vignettes/ftsa_test.Rnw
vignettes/pm10_ftsm.pdf
MD5
DESCRIPTION
ChangeLog
man
man/var.Rd man/ftsm.Rd man/quantile.Rd man/plot.ftsm.Rd man/summary.fm.Rd man/sd.Rd man/quantile.fts.Rd man/mean.fts.Rd man/ftsmiterativeforecasts.Rd man/pcscorebootstrapdata.Rd man/MFDM.Rd man/var.fts.Rd man/farforecast.Rd man/median.fts.Rd man/plot.fmres.Rd man/plot.fm.Rd man/pm_10_GR.Rd man/isfe.fts.Rd man/plot.ftsf.Rd man/ftsmweightselect.Rd man/fbootstrap.Rd man/forecast.ftsm.Rd man/long_run_covariance_estimation.Rd man/forecastfplsr.Rd man/error.Rd man/plotfplsr.Rd man/dynamic_FLR.Rd man/diff.fts.Rd man/dynupdate.Rd man/sd.fts.Rd man/is.fts.Rd man/centre.Rd man/extract.Rd man/residuals.fm.Rd man/ftsa-package.Rd man/T_stationary.Rd man/fplsr.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.