LinCal-package: Static Univariate Frequentist and Bayesian Linear Calibration

In LinCal: Static Univariate Frequentist and Bayesian Linear Calibration

Static Univariate Frequentist and Bayesian Linear Calibration

Description

A collection of R functions for conducting linear statistical calibration.

Details

Package:	LinCal
Type:	Package
Version:	1.0.1
Date:	2022-04-27
License:	GPL-2

Author(s)

Derick L. Rivers and Edward L. Boone

Maintainer: Derick L. Rivers <[e-mail]>

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

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)

LinCal documentation built on April 30, 2022, 1:06 a.m.