CRAN/E | esemifar

esemifar

Smoothing Long-Memory Time Series

Installation

About

The nonparametric trend and its derivatives in equidistant time series (TS) with long-memory errors can be estimated. The estimation is conducted via local polynomial regression using an automatically selected bandwidth obtained by a built-in iterative plug-in algorithm or a bandwidth fixed by the user. The smoothing methods of the package are described in Letmathe, S., Beran, J. and Feng, Y., (2023) doi:10.1080/03610926.2023.2276049.

wiwi.uni-paderborn.de/en/dep4/feng/

Key Metrics

Version 2.0.1
R ≥ 2.10
Published 2024-05-07 129 days ago
Needs compilation? yes
License GPL-3
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Maintainer

Maintainer

Dominik Schulz

Authors

Yuanhua Feng

aut

(Paderborn University, Germany)

Jan Beran

aut

(University of Konstanz, Germany)

Sebastian Letmathe

aut

(Paderborn University, Germany)

Dominik Schulz

aut / cre

(Paderborn University, Germany)

Material

README
NEWS
Reference manual
Package source

In Views

TimeSeries

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

esemifar archive

Depends

R ≥ 2.10

Imports

fracdiff
stats
utils
smoots
graphics
grDevices
Rcpp
future
furrr
ggplot2

LinkingTo

Rcpp
RcppArmadillo

Reverse Imports

ufRisk