Description Details Author(s) References Examples

A collection of R functions for conducting linear statistical calibration.

Package: | LinCal |

Type: | Package |

Version: | 1.0 |

Date: | 2014-11-06 |

License: | GPL-2 |

Derick L. Rivers and Edward L. Boone

Maintainer: Derick L. Rivers <[email protected]>

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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
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 May 29, 2017, 12:58 p.m.

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