JmatrixLMA {conicfit} | R Documentation |
Compute the Jacobian matrix using algebraic parameters
Description
JmatrixLMA
Computes the Jacobian matrix(Implicit method)
using algebraic parameters
Usage
JmatrixLMA(XY,ParA,XYproj)
Arguments
XY |
array of sample data |
ParA |
initial parameter vector c(Center(1:2), Axes(1:2), Angle) |
XYproj |
corresponding n projection points on the conic |
Value
list(Res , J) |
list with the Residual Sum of Squares and the Jacobian matrix |
Author(s)
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
XY <- matrix(c(1,7,2,6,5,8,7,7,9,5,3,7,6,2,8,4),8,2,byrow=TRUE)
ParA <- matrix(c(0.250000000000000,0,1,0,0,-1),ncol=1)
XYproj=matrix(c(0.394467220216675,0.980356518335872,0.833315950425981,
0.909063326557293,1.40466123643977,0.711850899213363,
1.70601340510202,0.521899957274429,1.89925244997324,0.313384799914835,
1.06482258038841,0.846485805004280,1.95308457257492,
0.215325713960169,1.91319150256275,0.291418202297698),8,2,byrow=TRUE)
JmatrixLMA(XY,ParA,XYproj)