Other packages > Find by keyword >

BivRegBLS  

Tolerance Interval and EIV Regression - Method Comparison Studies
View on CRAN: Click here


Download and install BivRegBLS package within the R console
Install from CRAN:
install.packages("BivRegBLS")

Install from Github:
library("remotes")
install_github("cran/BivRegBLS")

Install by package version:
library("remotes")
install_version("BivRegBLS", "1.1.1")



Attach the package and use:
library("BivRegBLS")
Maintained by
Bernard G Francq
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-01-06
Latest Update: 2019-10-10
Description:
Assess the agreement in method comparison studies by tolerance intervals and errors-in-variables (EIV) regressions. The Ordinary Least Square regressions (OLSv and OLSh), the Deming Regression (DR), and the (Correlated)-Bivariate Least Square regressions (BLS and CBLS) can be used with unreplicated or replicated data. The BLS() and CBLS() are the two main functions to estimate a regression line, while XY.plot() and MD.plot() are the two main graphical functions to display, respectively an (X,Y) plot or (M,D) plot with the BLS or CBLS results. Four hyperbolic statistical intervals are provided: the Confidence Interval (CI), the Confidence Bands (CB), the Prediction Interval and the Generalized prediction Interval. Assuming no proportional bias, the (M,D) plot (Band-Altman plot) may be simplified by calculating univariate tolerance intervals (beta-expectation (type I) or beta-gamma content (type II)). Major updates from last version 1.0.0 are: title shortened, include the new functions BLS.fit() and CBLS.fit() as shortcut of the, respectively, functions BLS() and CBLS(). References: B.G. Francq, B. Govaerts (2016) , B.G. Francq, B. Govaerts (2014) , B.G. Francq, B. Govaerts (2014) , B.G. Francq (2013), PhD Thesis, UCLouvain, Errors-in-variables regressions to assess equivalence in method comparison studies, .
How to cite:
Bernard G Francq (2017). BivRegBLS: Tolerance Interval and EIV Regression - Method Comparison Studies. R package version 1.1.1, https://cran.r-project.org/web/packages/BivRegBLS. Accessed 05 Aug. 2026.
Previous versions and publish date:
1.0.0 (2017-01-06 13:14), (2026-07-09 07:59)
Other packages that cited BivRegBLS R package
View BivRegBLS citation profile
Other R packages that BivRegBLS depends, imports, suggests or enhances
Complete documentation for BivRegBLS
Functions, R codes and Examples using the BivRegBLS R package
Some associated functions: Aromatics . BLS.fit . BLS.ht . BLS . BivRegBLS-package . CBLS.fit . CBLS . DR . FullCIs.MD . FullCIs.XY . GraphFullCIs.MD . GraphFullCIs.XY . MD.horiz.lines . MD.plot . OLSh . OLSv . SBP . XY.plot . antilog.pred . desc.stat . df.WS . lambdas . raw.plot . 
Some associated R codes: BLS.R . BLS.fit.R . BLS.ht.R . CBLS.R . CBLS.fit.R . DR.R . FullCIs.MD.R . FullCIs.XY.R . GraphFullCIs.MD.R . GraphFullCIs.XY.R . MD.horiz.lines.R . MD.plot.R . OLSh.R . OLSv.R . XY.plot.R . antilog.pred.R . desc.stat.R . df.WS.R . lambdas.R . raw.plot.R .  Full BivRegBLS package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

dcov  
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency  
kernelPSI  
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency  
dhReg  
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
noisyr  
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA