#ifndef lint
static const char RCSid[] = "$Id: linregr.c,v 2.3 2003/02/22 02:07:22 greg Exp $";
#endif
/*
* Basic linear regression calculation.
*/
/* ====================================================================
* The Radiance Software License, Version 1.0
*
* Copyright (c) 1990 - 2002 The Regents of the University of California,
* through Lawrence Berkeley National Laboratory. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
*
* 3. The end-user documentation included with the redistribution,
* if any, must include the following acknowledgment:
* "This product includes Radiance software
* (http://radsite.lbl.gov/)
* developed by the Lawrence Berkeley National Laboratory
* (http://www.lbl.gov/)."
* Alternately, this acknowledgment may appear in the software itself,
* if and wherever such third-party acknowledgments normally appear.
*
* 4. The names "Radiance," "Lawrence Berkeley National Laboratory"
* and "The Regents of the University of California" must
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* software without prior written permission. For written
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* 5. Products derived from this software may not be called "Radiance",
* nor may "Radiance" appear in their name, without prior written
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*
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL Lawrence Berkeley National Laboratory OR
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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*
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*/
#include
#include "linregr.h"
void
lrclear(l) /* initialize sum */
register LRSUM *l;
{
l->xs = l->ys = l->xxs = l->yys = l->xys = 0.0;
l->n = 0;
}
int
flrpoint(x, y, l) /* add point (x,y) to sum */
double x, y;
register LRSUM *l;
{
l->xs += x;
l->ys += y;
l->xxs += x*x;
l->yys += y*y;
l->xys += x*y;
return(++l->n);
}
int
lrfit(r, l) /* compute linear regression */
register LRLIN *r;
register LRSUM *l;
{
double nxvar, nyvar;
if (l->n < 2)
return(-1);
nxvar = l->xxs - l->xs*l->xs/l->n;
nyvar = l->yys - l->ys*l->ys/l->n;
if (nxvar == 0.0 || nyvar == 0.0)
return(-1);
r->slope = (l->xys - l->xs*l->ys/l->n) / nxvar;
r->intercept = (l->ys - r->slope*l->xs) / l->n;
r->correlation = r->slope*sqrt(nxvar/nyvar);
return(0);
}