# Functional Time Series Analysis

## Documentation for package ‘ftsa’ version 6.3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

ftsa-package | Functional Time Series Analysis
all_hmd_female_data | The US female log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).
all_hmd_male_data | The US male log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).
centre | Mean function, variance function, median function, trim mean function of functional data
CoDa_BayesNW | Compositional data analytic approach and nonparametric function-on-function regression for forecasting density
CoDa_FPCA | Compositional data analytic approach and functional principal component analysis for forecasting density
diff.fts | Differences of a functional time series
DJI_return | Dow Jones Industrial Average (DJIA)
dmfpca | Dynamic multilevel functional principal component analysis
dynamic_FLR | Dynamic updates via functional linear regression
dynupdate | Dynamic updates via BM, OLS, RR and PLS methods
error | Forecast error measure
ER_GR | Selection of the number of principal components
extract | Extract variables or observations
facf | Functional autocorrelation function
FANOVA | Functional analysis of variance fitted by means.
farforecast | Functional data forecasting through functional principal component autoregression
fbootstrap | Bootstrap independent and identically distributed functional data
forecast.ftsm | Forecast functional time series
forecast.hdfpca | Forecasting via a high-dimensional functional principal component regression
forecastfplsr | Forecast functional time series
fplsr | Functional partial least squares regression
ftsa | 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 functional time series model.
GAEVforecast | Fit a generalized additive extreme value model to the functional data with given basis numbers
hdfpca | High-dimensional functional principal component analysis
hd_data | Simulated high-dimensional functional time series
Horta_Ziegelmann_FPCA | Dynamic functional principal component analysis for density forecasting
is.fts | Test for functional time series
isfe.fts | Integrated Squared Forecast Error for models of various orders
long_run_covariance_estimation | Estimating long-run covariance function for a functional time series
LQDT_FPCA | Log quantile density transform
MAF_multivariate | Maximum autocorrelation factors
mean.fts | Mean functions for functional time series
median.fts | Median functions for functional time series
MFDM | Multilevel functional data method
MFPCA | Multilevel functional principal component analysis for clustering
mftsc | Multiple funtional time series clustering
pcscorebootstrapdata | Bootstrap independent and identically distributed functional data or functional time series
plot.fm | Plot fitted model components for a functional model
plot.fmres | Plot residuals from a fitted functional model.
plot.ftsf | Plot fitted model components for a functional time series model
plot.ftsm | Plot fitted model components for a functional time series model
plotfplsr | Plot fitted model components for a functional time series model
pm_10_GR | Particulate Matter Concentrations (pm10)
pm_10_GR_sqrt | 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.default | Standard deviation
sd.fts | Standard deviation functions for functional time series
sim_ex_cluster | Simulated multiple sets of functional time series
sim_ex_cluster.smooth | Simulated multiple sets of functional time series
skew_t_fun | Skewed t distribution
stop_time_detect | Detection of the optimal stopping time in a curve time series
stop_time_sim_data | Simulated functional time series from a functional autoregression of order one
summary.fm | Summary for functional time series model
Two_way_median_polish | Two-way functional median polish from Sun and Genton (2012)
Two_way_Residuals | Functional time series decomposition into deterministic (from functional median polish from Sun and Genton (2012)), and time-varying components (functional residuals).
Two_way_Residuals_means | Functional time series decomposition into deterministic (functional analysis of variance fitted by means), and time-varying components (functional residuals).
T_stationary | Testing stationarity of functional time series
var | Variance
var.default | Variance
var.fts | Variance functions for functional time series