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pdl::linfit(3) [redhat man page]

Linfit(3)						User Contributed Perl Documentation						 Linfit(3)

NAME
PDL::Fit::Linfit - routines for fitting data with linear combinations of functions. DESCRIPTION
This module contains routines to perform general curve-fits to a set (linear combination) of specified functions. Given a set of Data: (y0, y1, y2, y3, y4, y5, ...ynoPoints-1) The fit routine tries to model y as: y' = beta0*x0 + beta1*x1 + ... beta_noCoefs*x_noCoefs Where x0, x1, ... x_noCoefs, is a set of functions (curves) that the are combined linearly using the beta coefs to yield an approximation of the input data. The Sum-Sq error is reduced to a minimum in this curve fit. Inputs: $data This is your data you are trying to fit. Size=n $functions 2D array. size (n, noCoefs). Row 0 is the evaluation of function x0 at all the points in y. Row 1 is the evaluation of of function x1 at all the points in y, ... etc. Example of $functions array Structure: $data is a set of 10 points that we are trying to model using the linear combination of 3 functions. $functions = ( [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ], # Constant Term [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ], # Linear Slope Term [ 0, 2, 4, 9, 16, 25, 36, 49, 64, 81] # quadradic term ) SYNOPSIS
$yfit = linfit1d $data, $funcs FUNCTIONS
linfit1d 1D Fit linear combination of supplied functions to data using min chi^2 (least squares). Usage: ($yfit, [$coeffs]) = linfit1d [$xdata], $data, $fitFuncs, [Options...] Signature: (xdata(n); ydata(n); $fitFuncs(n,order); [o]yfit(n); [o]coeffs(order)) Uses a standard matrix inversion method to do a least squares/min chi^2 fit to data. Returns the fitted data and optionally the coefficients. One can thread over extra dimensions to do multiple fits (except the order can not be threaded over - i.e. it must be one fixed set of fit functions "fitFuncs". The data is normalised internally to avoid overflows (using the mean of the abs value) which are common in large polynomial series but the returned fit, coeffs are in unnormalised units. # Generate data from a set of functions $xvalues = sequence(100); $data = 3*$xvalues + 2*cos($xvalues) + 3*sin($xvalues*2); # Make the fit Functions $fitFuncs = cat $xvalues, cos($xvalues), sin($xvalues*2); # Now fit the data, Coefs should be the coefs in the linear combination # above: 3,2,3 ($yfit, $coeffs) = linfit1d $data,$fitFuncs; Options: Weights Weights to use in fit, e.g. 1/$sigma**2 (default=1) perl v5.8.0 2000-12-06 Linfit(3)

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Polynomial(3pm) 					User Contributed Perl Documentation					   Polynomial(3pm)

NAME
PDL::Fit::Polynomial - routines for fitting with polynomials DESCRIPTION
This module contains routines for doing simple polynomial fits to data SYNOPSIS
$yfit = fitpoly1d $data; FUNCTIONS
fitpoly1d Fit 1D polynomials to data using min chi^2 (least squares) Usage: ($yfit, [$coeffs]) = fitpoly1d [$xdata], $data, $order, [Options...] Signature: (x(n); y(n); [o]yfit(n); [o]coeffs(order)) Uses a standard matrix inversion method to do a least squares/min chi^2 polynomial fit to data. Order=2 is a linear fit (two parameters). Returns the fitted data and optionally the coefficients. One can thread over extra dimensions to do multiple fits (except the order can not be threaded over - i.e. it must be one fixed scalar number like "4"). The data is normalised internally to avoid overflows (using the mean of the abs value) which are common in large polynomial series but the returned fit, coeffs are in unnormalised units. $yfit = fitpoly1d $data,2; # Least-squares line fit ($yfit, $coeffs) = fitpoly1d $x, $y, 4; # Fit a cubic $fitimage = fitpoly1d $image,3 # Fit a quadratic to each row of an image $myfit = fitpoly1d $line, 2, {Weights => $w}; # Weighted fit Options: Weights Weights to use in fit, e.g. 1/$sigma**2 (default=1) BUGS
May not work too well for data with large dynamic range. SEE ALSO
"polyfit" in PDL::Slatec AUTHOR
This file copyright (C) 1999, Karl Glazebrook (kgb@aaoepp.aao.gov.au). All rights reserved. There is no warranty. You are allowed to redistribute this software documentation under certain conditions. For details, see the file COPYING in the PDL distribution. If this file is separated from the PDL distribution, the copyright notice should be included in the file. perl v5.14.2 2012-01-02 Polynomial(3pm)
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