Residuals.hyperbola

This function is not intended for external use. It is called from <code>fitConic</code> when iterating to find the best-fit hyperbola.

Fit data to an ellipse, hyperbola, or parabola. Bootstrapping is available when needed. The conic curve can be rotated through an arbitrary angle and the fit will still succeed. Helper functions are provided to convert generator coefficients from one style to another, generate test data sets, rotate conic section parameters, and so on. References include Nikolai Chernov (2014) "Fitting ellipses, circles, and lines by least squares" <https://people.cas.uab.edu/~mosya/cl/>; A. W. Fitzgibbon, M. Pilu, R. B. Fisher (1999) "Direct Least Squares Fitting of Ellipses" IEEE Trans. PAMI, Vol. 21, pages 476-48; N. Chernov, Q. Huang, and H. Ma (2014) "Fitting quadratic curves to data points", British Journal of Mathematics & Computer Science, 4, 33-60; N. Chernov and H. Ma (2011) "Least squares fitting of quadratic curves and surfaces", Computer Vision, Editor S. R. Yoshida, Nova Science Publishers, pp. 285-302.

Carl Witthoft

fitConic

Fit Data to Any Conic Section

Jose Gama

Nikolai Chernov

Residuals.hyperbola function

<dl> <dt>XY</dt>
<dd>The x,y dataset
</dd> <dt>parG</dt>
<dd>The "G-parameter" set for the current iteration.
</dd></dl>

Arguments

Carl Witthoft &lt;carl@witthoft.com&gt;

Author

Calculate Residual Error For Current Coefficients
 — Residuals.hyperbola

<dl>

 <dt>XY</dt>
<dd>The x,y dataset
</dd>

 <dt>parG</dt>
<dd>The "G-parameter" set for the current iteration.
</dd>

</dl>

Residuals.hyperbola: Calculate Residual Error For Current Coefficients

Description

Usage

Value

Arguments

Author

References