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binfunest
View on CRAN: Click
here
Download and install binfunest package within the R console
Install from CRAN:
install.packages("binfunest")
Install from Github:
library("remotes")
install_github("cran/binfunest") Install by package version:
library("remotes")
install_version("binfunest", "0.1.0") Attach the package and use:
library("binfunest")
Maintained by
Philip Shea
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-09
Latest Update: 2022-09-09
Description:
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, )), polarization shifted
QPSK (Agrell & Karlsson (2009, )), and utility
functions to work with the performance functions.
How to cite:
Philip Shea (2022). binfunest: Estimates Parameters of Functions Driving Binomial Random Variables. R package version 0.1.0, https://cran.r-project.org/web/packages/binfunest. Accessed 07 Mar. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for binfunest
Functions, R codes and Examples using
the binfunest R package
Some associated functions: B2BConvert . BERDFc . Theoretical . binfunest-package . mleB2B .
Some associated R codes: B2BConvert.R . B2BQ.R . Data.R . mleB2B.R . theory.R . Full binfunest package functions and examples
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