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-4.5-noble)esemifar_2.0.1.tar.gz(r-4.4-noble)
esemifar_2.0.1.tgz(r-4.4-emscripten)esemifar_2.0.1.tgz(r-4.3-emscripten)
esemifar.pdf |esemifar.html✨
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

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 1 packages 1 scripts 341 downloads 10 exports 46 dependencies

Last updated 8 months agofrom:39efaf28b5. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 04 2024
R-4.5-linux-x86_64	OK	Dec 04 2024

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

Dependencies:cli codetools colorspace crayon digest fansi farver fracdiff furrr future future.apply ggplot2 globals glue gtable hms isoband labeling lattice lifecycle listenv magrittr MASS Matrix mgcv munsell nlme parallelly pillar pkgconfig prettyunits progress progressr purrr R6 RColorBrewer Rcpp RcppArmadillo rlang scales smoots tibble utf8 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)