# CircleFitByTaubin: Algebraic circle fit (Taubin method) In conicfit: Algorithms for Fitting Circles, Ellipses and Conics Based on the Work by Prof. Nikolai Chernov

## Description

`CircleFitByTaubin` applies the simple algebraic circle fit (Taubin method)

## Usage

 `1` ```CircleFitByTaubin(XY) ```

## Arguments

 `XY` array of sample data

## Value

 `vector(a, b, R)` vector with the values for the circle: center (a,b) and radius R

Jose Gama

## Source

Nikolai Chernov, 2014 Fitting ellipses, circles, and lines by least squares http://people.cas.uab.edu/~mosya/cl/

Nikolai Chernov, 2010 Circular and linear regression: Fitting circles and lines by least squares Chapman & Hall/CRC, Monographs on Statistics and Applied Probability, Volume 117

## References

Nikolai Chernov, 2014 Fitting ellipses, circles, and lines by least squares http://people.cas.uab.edu/~mosya/cl/

Nikolai Chernov, 2010 Circular and linear regression: Fitting circles and lines by least squares Chapman & Hall/CRC, Monographs on Statistics and Applied Probability, Volume 117

## Examples

 ```1 2 3 4 5``` ```xy<-calculateCircle(0,0,200,50,randomDist=TRUE,noiseFun=function(x) (x+rnorm(1,mean=0,sd=50))) plot(xy[,1],xy[,2],xlim=c(-250,250),ylim=c(-250,250));par(new=TRUE) c1 <- CircleFitByTaubin(xy) xyc1<-calculateCircle(c1[1],c1[2],c1[3]) plot(xyc1[,1],xyc1[,2],xlim=c(-250,250),ylim=c(-250,250),col='red',type='l');par(new=TRUE) ```

### Example output

```Loading required package: pracma