R Observatory: Metrics for mhpfilter version 0.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

mhpfilter

0.1.0Package record

Modified Hodrick-Prescott Filter with Optimal Smoothing Parameter Selection

0packages depend

1.8Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Muhammad YaseenCRAN page ↗GitHub ↗Website ↗Issues ↗

High-performance implementation of the Modified Hodrick-Prescott (HP) Filter for decomposing macroeconomic time series into trend and cyclical components. Based on the methodology of Choudhary, Hanif and Iqbal (2014) doi:10.1080/00036846.2014.894631 "On smoothing macroeconomic time series using the modified HP filter", which uses generalized cross-validation (GCV) to automatically select the optimal smoothing parameter lambda, following McDermott (1997) "An automatic method for choosing the smoothing parameter in the HP filter" (as described in Coe and McDermott (1997) doi:10.2307/3867497). Unlike the standard HP filter that uses fixed lambda values (1600 for quarterly, 100 for annual data), this package estimates series-specific lambda values that minimize the GCV criterion. Implements efficient C++ routines via 'RcppArmadillo' for fast computation, supports batch processing of multiple series, and provides comprehensive visualization tools using 'ggplot2'. Particularly useful for cross-country macroeconomic comparisons, business cycle analysis, and when the appropriate smoothing parameter is uncertain.

Changes in 0.1.0

Initial CRAN Release (2026-02-06)

This is the first official release of **mhpfilter** to CRAN.

Overview

**mhpfilter** implements the Modified Hodrick-Prescott (HP) Filter for decomposing macroeconomic time series into trend and cyclical components. The package automatically selects the optimal smoothing parameter λ using generalized cross-validation (GCV), based on the methodology of Choudhary, Hanif & Iqbal (2014).

Core Features

Filtering Functions

mhp_filter() - Modified HP filter with automatic λ selection via GCV
hp_filter() - Standard HP filter with fixed λ parameter
mhp_compare() - Compare HP vs Modified HP for single series
mhp_batch() - Batch processing for multiple time series
batch_compare() - Batch comparison of HP vs Modified HP

Visualization Functions

Show all changes in 0.1.0Hide the rest of the changes in 0.1.0

autoplot.mhp() - ggplot2-based visualization for mhp objects
plot_comparison() - Visual comparison of HP vs Modified HP results
plot_batch() - Visualization of batch processing results

Utility Functions

get_lambda() - Extract optimal λ from results
get_gcv() - Extract GCV value from results
print.mhp() - Print method for mhp class objects

Technical Implementation

High Performance

Fast C++ implementation using RcppArmadillo for matrix operations
Optimized grid search algorithm for λ selection
Efficient memory management for large time series
Linear scaling for batch processing of multiple series

Modern R Integration

Full compatibility with data.table (≥ 1.14.0)
Integration with collapse (≥ 2.0.0) for fast statistics
Support for kit (≥ 0.0.11) utilities
Works seamlessly with tidyverse (≥ 2.0.0) and fastverse (≥ 0.3.0)
ggplot2-based professional visualizations

Documentation

Comprehensive Vignettes

**Introduction** - Quick start guide with practical examples
Basic usage and workflow
Comparison with standard HP filter
Real-world applications
**Methodology** - Mathematical theory and derivations
Standard HP filter formulation
Generalized cross-validation criterion
Optimal λ selection procedure
Performance characteristics

Function Documentation

Complete roxygen2 documentation for all functions
Mathematical formulas properly rendered with LaTeX
Extensive examples with commentary
Author affiliations and ORCID identifiers

Package Website

Professional pkgdown site with full documentation
Download statistics and badges
Interactive examples and tutorials
API reference with search functionality

Methodology Reference

This implementation is based on:

**Choudhary, M.A., Hanif, M.N., & Iqbal, J. (2014).** "On smoothing macroeconomic time series using the modified HP filter." *Applied Economics*, 46(19), 2205-2214. https://doi.org/10.1080/00036846.2014.896982

Authors and Contributors

Package Author and Maintainer

**Muhammad Yaseen**

Postdoctoral Research Fellow

School of Mathematical and Statistical Sciences

Clemson University

Original Methodology Authors

**Javed Iqbal** - State Bank of Pakistan

**M. Nadim Hanif** - State Bank of Pakistan

Installation

```r

From CRAN (recommended)

install.packages("mhpfilter")

From GitHub (development version)

devtools::install_github("myaseen208/mhpfilter")

```

System Requirements

R ≥ 4.0.0
C++ compiler for building from source
Operating systems: Windows, macOS, Linux

Testing and Quality Assurance

Comprehensive test suite with testthat (≥ 3.0.0)
Continuous integration via GitHub Actions
R CMD check passes on all platforms
CRAN policy compliance verified
No NOTEs, WARNINGs, or ERRORs

License

MIT License

Bug Reports and Issues

Please report bugs at: https://github.com/myaseen208/mhpfilter/issues

Acknowledgments

Original methodology: Choudhary, Hanif & Iqbal (2014)
RcppArmadillo team for excellent C++ integration
R Core Team for the R statistical computing environment
CRAN team for review and hosting

---

For more information, visit: https://github.com/myaseen208/mhpfilter

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("mhpfilter", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("myaseen208/mhpfilter")

Development version from myaseen208/mhpfilter. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-mhpfilter

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-mhpfilter

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-mhpfilter

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 5.8 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-04-22
ERROR13 OK, 1 ERROR2026-04-18
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.0

READMEYes · 339 wordsVignettesYes · 2 · dynamicNEWSYes · 67% structured · mentions 0.1.0Citation fileYes · cites a publicationWebsiteYes · pkgdown

Help pages: 12includes a package overview page
Examples that run: 91%10 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 33%

Vignettes (2)

How these are measured

Downloads

1.8K

CRAN downloads in the past year

Rank #21,921 · ~5/day · ~150/mo

Releases R versions

Daily download trend is not available in this view yet.

21930 days

60490 days

1.8K1 year

Compare downloads with other packages →

Also on215 r2u6 autocran

How downloads are counted

Repository

myaseen208/mhpfilter ↗Account: myaseen208

2Stars

0Forks

1Open issues

0Open PRs

0Releases

10Commits

1Commit identities

10 commits · Last activity 2026-02-13 · 0% stars, 30d

Responsiveness

not measured

Stars over time

2026-02-13 · 22026-07-07 · 2

How these are measured

PracticesBeta

3 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/myaseen208/mhpfilter on 2026-10-18.

Docs source (2)

pkgdown

GitHub Pages site last deployed 2026-02-13

pkgdown site last built 2026-02-13

CRAN release process (1)

CRAN-SUBMISSION

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

12 external dependencies (excludes base and recommended)

Installing mhpfilter adds 21 packages (11 with compiled code, 23 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, Rcpp 1.8 MB.

Depends (1)

R >= 4.0.0

Imports (5)

Rcpp RcppArmadillo data.table (>= 1.14.0)collapse ggplot2

LinkingTo (2)

Rcpp RcppArmadillo

Suggests (5)

knitr rmarkdown testthat tidyverse fastverse

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (3)

Muhammad Yaseen

Author, Maintainer since 0.1.0 (2026)

M. Nadim Hanif

Contributor

Original methodology author

Javed Iqbal

Contributor

Original methodology author

Releases (1)

R
R 4.6.0 released · 2026-04-24
0.1.0Latest
record
2026-02-13 · current release
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2026-02-13
Total releases: 1 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.0.0
Download size: 443 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("mhpfilter")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1080/00036846.2014.894631.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mhpfilter version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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