binfunest: Estimates Parameters of Functions Driving Binomial Random Variables

Provides maximum likelihood estimates of the performance parameters that drive a binomial distribution of observed errors, and takes full advantage of zero error observations. High performance communications systems typically have inherent noise sources and other performance limitations that need to be estimated. Measurements made at high signal to noise ratios typically result in zero errors due to limitation in available measurement time. Package includes theoretical performance functions for common modulation schemes (Proakis, "Digital Communications" (1995, <ISBN:0-07-051726-6>)), polarization shifted QPSK (Agrell & Karlsson (2009, <doi:10.1109/JLT.2009.2029064>)), and utility functions to work with the performance functions.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: pracma, stats, stats4
Suggests: covr, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2022-09-09
Author: Philip Shea ORCID iD [aut, cre]
Maintainer: Philip Shea <philshea at gmail.com>
BugReports: https://github.com/PhilShea/binfunest/issues
License: MIT + file LICENSE
URL: https://github.com/PhilShea/binfunest
NeedsCompilation: no
Materials: NEWS
CRAN checks: binfunest results

Documentation:

Reference manual: binfunest.pdf
Vignettes: Estimating B2B Q and Offsets

Downloads:

Package source: binfunest_0.1.0.tar.gz
Windows binaries: r-devel: binfunest_0.1.0.zip, r-release: binfunest_0.1.0.zip, r-oldrel: binfunest_0.1.0.zip
macOS binaries: r-release (arm64): binfunest_0.1.0.tgz, r-oldrel (arm64): binfunest_0.1.0.tgz, r-release (x86_64): binfunest_0.1.0.tgz

Linking:

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