LinCal-package: Static Univariate Frequentist and Bayesian Linear Calibration

Description Details Author(s) References Examples

Description

A collection of R functions for conducting linear statistical calibration.

Details

Package: LinCal
Type: Package
Version: 1.0
Date: 2014-11-06
License: GPL-2

Author(s)

Derick L. Rivers and Edward L. Boone

Maintainer: Derick L. Rivers <riversdl@vcu.edu>

References

Eisenhart, C. (1939). The interpretation of certain regression methods and their use in biological and industrial research. Annals of Mathematical Statistics. 10, 162-186.

Krutchkoff, R. G. (1967). Classical and Inverse Regression Methods of Calibration. Technometrics. 9, 425-439.

Hoadley, B. (1970). A Bayesian look at Inverse Linear Regression. Journal of the American Statistical Association. 65, 356-369.

Hunter, W., and Lamboy, W. (1981). A Bayesian Analysis of the Linear Calibration Problem. Technometrics. 3, 323-328.

Examples

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library(LinCal)

data(wheat)

plot(wheat[,6],wheat[,2])

## Classical Approach
class.calib(wheat[,6],wheat[,2],0.05,105)

## Inverse Approach
inver.calib(wheat[,6],wheat[,2],0.05,105)

## Bayesian Inverse Approach
hoad.calib(wheat[,6],wheat[,2],0.05,105)

##Bayesian Classical Approach
huntlam.calib(wheat[,6],wheat[,2],0.05,105)

Example output

$x.pre
(Intercept) 
   11.09548 

$lim
         [,1]     [,2]
[1,] 10.66133 11.52824

$x.pre
(Intercept) 
    11.1027 

$lim
         [,1]     [,2]
[1,] 10.70394 11.50146

$x.pre
[1] 11.1027

$sd
[1] 0.318569

$lim
        lower    upper
[1,] 10.67973 11.52567

$x.pre
(Intercept) 
   11.09548 

$sd
        x 
0.3256772 

$lim
         [,1]     [,2]
[1,] 10.55979 11.63117

LinCal documentation built on May 1, 2019, 10:11 p.m.