This package is considered a duplicate. The official version of this package is found at:https://dschulz13.r-universe.dev/esemifar

Package: esemifar 2.0.1

Dominik Schulz

esemifar: Smoothing Long-Memory Time Series

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>.

Authors:Yuanhua Feng [aut], Jan Beran [aut], Sebastian Letmathe [aut], Dominik Schulz [aut, cre]

esemifar_2.0.1.tar.gz
esemifar_2.0.1.tar.gz(r-4.7-arm64)esemifar_2.0.1.tar.gz(r-4.7-x86_64)esemifar_2.0.1.tar.gz(r-4.6-arm64)esemifar_2.0.1.tar.gz(r-4.6-x86_64)
esemifar_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
esemifar/json (API)
NEWS

# Install 'esemifar' in R:

install.packages('esemifar', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

airLDN - Daily Observations of the Air Quality Index of London
gdpG7 - Quarterly G7 GDP, Q1 1962 to Q4 2019

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas cpp

2.48 score 1 stars 2 packages 1 scripts 319 downloads 10 exports 37 dependencies

Last updated from:39efaf28b5. Checks:6 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	141
linux-devel-x86_64	OK	137
source / vignettes	OK	208
linux-release-arm64	OK	128
linux-release-x86_64	OK	162
wasm-release	OK	120

Exports:arma_to_ar arma_to_ma critMatlm d_to_coef dsmoothlm esemifar farima_to_ar farima_to_ma gsmooth tsmoothlm

Dependencies:cli codetools cpp11 crayon digest farver fracdiff furrr future future.apply ggplot2 globals glue gtable hms isoband labeling lifecycle listenv magrittr parallelly pkgconfig prettyunits progress progressr purrr R6 RColorBrewer Rcpp RcppArmadillo rlang S7 scales smoots vctrs viridisLite withr

Help page	Topics
Daily Observations of the Air Quality Index of London (Britain)	airLDN
AR Representation of an ARMA Model	arma_to_ar
MA Representation of an ARMA Model	arma_to_ma
FARIMA Order Selection Matrix	critMatlm
Filter Coefficients of the Fractional Differencing Operator	d_to_coef
Data-driven Local Polynomial for the Trend's Derivatives in Equidistant Time Series	dsmoothlm
esemifar: A package for data-driven nonparametric estimation of the trend and its derivatives in equidistant time series.	esemifar-package esemifar
AR Representation of a FARIMA Model	farima_to_ar
MA Representation of a FARIMA Model	farima_to_ma
Extract Model Fitted Values	fitted.esemifar
Quarterly G7 GDP, Q1 1962 to Q4 2019	gdpG7
Estimation of Trends and their Derivatives via Local Polynomial Regression	gsmooth
Plot Method for the Package 'esemifar'	plot.esemifar
Plot Method for Class '"esemifar_fc"'	plot.esemifar_fc
ESEMIFAR Prediction Method	predict.esemifar
Print Method for the Package 'esemifar'	print.esemifar
Extract Model Residuals	residuals.esemifar
Advanced Data-driven Nonparametric Regression for the Trend in Equidistant Time Series	tsmoothlm

Package: esemifar 2.0.1

esemifar: Smoothing Long-Memory Time Series

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)