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ftsa (version 6.2)

Functional Time Series Analysis

Description

Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series. \n Jim\'{e}nez-Var\'{o}n, C., Sun, Y. and Shang, H. L. (2023) .

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Version

Install

install.packages('ftsa')

Monthly Downloads

1,996

Version

6.2

License

GPL-3

Maintainer

Han Lin Shang

Last Published

June 1st, 2023

Functions in ftsa (6.2)

Dynamic updates via BM, OLS, RR and PLS methods

all_hmd_male_data

The US male log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).

all_hmd_female_data

The US female log-mortality rate from 1959-2020 and 3 states (New York, California, Illinois).

Multilevel functional principal component analysis for clustering

Two_way_median_polish

Two-way functional median polish from Sun and Genton (2012)

Dynamic updates via functional linear regression

Dynamic multilevel functional principal component analysis

Differences of a functional time series

Mean function, variance function, median function, trim mean function of functional data

Testing stationarity of functional time series

forecast.hdfpca

Forecasting via a high-dimensional functional principal component regression

Extract variables or observations

Forecast functional time series

Functional Time Series Analysis

Functional partial least squares regression

Bootstrap independent and identically distributed functional data

Forecast functional time series

Forecast error measure

Functional data forecasting through functional principal component autoregression

Functional autocorrelation function

Simulated high-dimensional functional time series

Integrated Squared Forecast Error for models of various orders

Test for functional time series

High-dimensional functional principal component analysis

ftsmweightselect

Selection of the weight parameter used in the weighted functional time series model.

long_run_covariance_estimation

Estimating long-run covariance function for a functional time series

Multiple funtional time series clustering

Quantile functions for functional time series

Plot fitted model components for a functional time series model

Fit functional time series model

Plot fitted model components for a functional time series model

Plot fitted model components for a functional model

Median functions for functional time series

ftsmiterativeforecasts

Forecast functional time series

Mean functions for functional time series

pcscorebootstrapdata

Bootstrap independent and identically distributed functional data or functional time series

Simulated multiple sets of functional time series

stop_time_sim_data

Simulated functional time series from a functional autoregression of order one

Plot fitted model components for a functional time series model

Plot residuals from a fitted functional model.

Standard deviation functions for functional time series

Summary for functional time series model

stop_time_detect

Detection of the optimal stopping time in a curve time series

Skewed t distribution

Standard deviation

Compute residuals from a functional model

Variance functions for functional time series

Particulate Matter Concentrations (pm10)

Functional analysis of variance fitted by means.

Compositional data analytic approach and nonparametric function-on-function regression for forecasting density

Horta_Ziegelmann_FPCA

Dynamic functional principal component analysis for density forecasting

MAF_multivariate

Maximum autocorrelation factors

Compositional data analytic approach and functional principal component analysis for forecasting density

Fit a generalized additive extreme value model to the functional data with given basis numbers

Dow Jones Industrial Average (DJIA)

Multilevel functional data method

Selection of the number of principal components

Log quantile density transform