DR {BivRegBLS}

Deming Regression

Description

Estimate the Deming Regression (DR) with unreplicated or replicated data.

Usage

DR(data = NULL, xcol = 1, ycol = 2, ratio.var = NULL, conf.level = 0.95)

Arguments

data

a data set (data frame or matrix).

xcol

a numeric vector to specify the X column(s) or a character vector with the column names.

ycol

a numeric vector to specify the Y column(s) or a character vector with the column names.

ratio.var

a numeric value for λ the ratio of the measurement error variances (Y over X) if known. Otherwise, it may be estimated with replicated data.

conf.level

a numeric value for the confidence level (expressed between 0 and 1).

Details

The BLS regression is more general and includes the Deming Regression. The BLS regression provides more results and should, therefore, be used instead of DR.

Value

A list including the following elements:

Ellipse.DR

a two columns matrix with the coordinates of the joint confidence interval (confidence region, ellipse) for the parameters (β, α).

Estimate.DR

a table (data frame) with the estimates of the intercept and the slope, standard error, confidence interval and pvalue (null hypothesis: slope = 1, intercept = 0). The exact confidence interval for the slope is also given.

Author(s)

Bernard G FRANCQ

References

Francq BG, Govaerts BB. Measurement methods comparison with errors-in-variables regressions. From horizontal to vertical OLS regression, review and new perspectives. Chemometrics and Intelligent Laboratory Systems 2014; 134:123-139.
Tan CY, Iglewicz B. Measurement-methods comparisons and linear statistical relationship. Technometrics, 1999; 41(3):192-201.

See Also

BLS

Examples

library(BivRegBLS)
data(SBP)
res.DR=DR(data=SBP,xcol=c("J1","J2","J3"),ycol=8:10)
res.DR$Estimate.DR
data(Aromatics)
res.DR=DR(data=Aromatics,xcol=3,ycol=4,ratio.var=2)