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ftsa (version 6.4)
Functional Time Series Analysis
Description
Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.
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Install
install.packages('ftsa')
Monthly Downloads
3,002
Version
6.4
License
GPL-3
Maintainer
Han Lin Shang
Last Published
January 23rd, 2024
Functions in ftsa (6.4)
Search functions
Two_way_Residuals
Functional time series decomposition into deterministic (from functional median polish from Sun and Genton (2012)), and time-varying components (functional residuals).
centre
Mean function, variance function, median function, trim mean function of functional data
facf
Functional autocorrelation function
diff.fts
Differences of a functional time series
error
Forecast error measure
dmfpca
Dynamic multilevel functional principal component analysis
One_way_Residuals
Functional time series decomposition into deterministic (from functional median polish of Sun and Genton (2012)), and functional residual components.
fplsr
Functional partial least squares regression
ftsa-package
Functional Time Series Analysis
Two_way_Residuals_means
Functional time series decomposition into deterministic (functional analysis of variance fitted by means), and time-varying components (functional residuals).
MFPCA
Multilevel functional principal component analysis for clustering
fbootstrap
Bootstrap independent and identically distributed functional data
ftsm
Fit functional time series model
ftsmiterativeforecasts
Forecast functional time series
T_stationary
Testing stationarity of functional time series
hdfpca
High-dimensional functional principal component analysis
extract
Extract variables or observations
forecast.ftsm
Forecast functional time series
farforecast
Functional data forecasting through functional principal component autoregression
is.fts
Test for functional time series
dynupdate
Dynamic updates via BM, OLS, RR and PLS methods
isfe.fts
Integrated Squared Forecast Error for models of various orders
plot.fm
Plot fitted model components for a functional model
dynamic_FLR
Dynamic updates via functional linear regression
mftsc
Multiple funtional time series clustering
quantile
Quantile
ftsmweightselect
Selection of the weight parameter used in the weighted functional time series model.
pcscorebootstrapdata
Bootstrap independent and identically distributed functional data or functional time series
hd_data
Simulated high-dimensional functional time series
long_run_covariance_estimation
Estimating long-run covariance function for a functional time series
mean.fts
Mean functions for functional time series
var
Variance
median.fts
Median functions for functional time series
var.fts
Variance functions for functional time series
sim_ex_cluster
Simulated multiple sets of functional time series
sd.fts
Standard deviation functions for functional time series
quantile.fts
Quantile functions for functional time series
residuals.fm
Compute residuals from a functional model
stop_time_sim_data
Simulated functional time series from a functional autoregression of order one
plot.fmres
Plot residuals from a fitted functional model.
pm_10_GR
Particulate Matter Concentrations (pm10)
plot.ftsf
Plot fitted model components for a functional time series model
stop_time_detect
Detection of the optimal stopping time in a curve time series
skew_t_fun
Skewed t distribution
plotfplsr
Plot fitted model components for a functional time series model
forecast.hdfpca
Forecasting via a high-dimensional functional principal component regression
sd
Standard deviation
plot.ftsm
Plot fitted model components for a functional time series model
summary.fm
Summary for functional time series model
forecastfplsr
Forecast functional time series
DJI_return
Dow Jones Industrial Average (DJIA)
MAF_multivariate
Maximum autocorrelation factors
MFDM
Multilevel functional data method
CoDa_BayesNW
Compositional data analytic approach and nonparametric function-on-function regression for forecasting density
all_hmd_female_data
The US female log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).
FANOVA
Functional analysis of variance fitted by means.
all_hmd_male_data
The US male log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).
GAEVforecast
Fit a generalized additive extreme value model to the functional data with given basis numbers
One_way_median_polish
One-way functional median polish from Sun and Genton (2012)
LQDT_FPCA
Log quantile density transform
CoDa_FPCA
Compositional data analytic approach and functional principal component analysis for forecasting density
Horta_Ziegelmann_FPCA
Dynamic functional principal component analysis for density forecasting
Two_way_median_polish
Two-way functional median polish from Sun and Genton (2012)
ER_GR
Selection of the number of principal components