src/common/linregr.c

#ifndef lint
static const char       RCSid[] = "$Id$";
#endif
/*
 * Basic linear regression calculation.
 */

#include "copyright.h"

#include <math.h>

#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);
}
Revision:	2.4
Committed:	Tue Feb 25 02:47:21 2003 UTC (22 years, 8 months ago) by greg
Content type:	text/plain
Branch:	MAIN
CVS Tags:	rad5R4, rad5R2, rad5R3, rad5R0, rad5R1, rad4R2, rad3R7P2, rad3R7P1, rad6R0, rad4R1, rad4R0, rad3R5, rad3R6, rad3R6P1, rad3R8, rad3R9, rad4R2P1, rad4R2P2, HEAD
Changes since 2.3:	+1 -56 lines
Log Message:	Replaced inline copyright notice with #include "copyright.h"
#	Content
1	#ifndef lint
2	static const char RCSid[] = "$Id$";
3	#endif
4	/*
5	* Basic linear regression calculation.
6	*/
7
8	#include "copyright.h"
9
10	#include <math.h>
11
12	#include "linregr.h"
13
14
15	void
16	lrclear(l) /* initialize sum */
17	register LRSUM *l;
18	{
19	l->xs = l->ys = l->xxs = l->yys = l->xys = 0.0;
20	l->n = 0;
21	}
22
23
24	int
25	flrpoint(x, y, l) /* add point (x,y) to sum */
26	double x, y;
27	register LRSUM *l;
28	{
29	l->xs += x;
30	l->ys += y;
31	l->xxs += x*x;
32	l->yys += y*y;
33	l->xys += x*y;
34	return(++l->n);
35	}
36
37
38	int
39	lrfit(r, l) /* compute linear regression */
40	register LRLIN *r;
41	register LRSUM *l;
42	{
43	double nxvar, nyvar;
44
45	if (l->n < 2)
46	return(-1);
47	nxvar = l->xxs - l->xs*l->xs/l->n;
48	nyvar = l->yys - l->ys*l->ys/l->n;
49	if (nxvar == 0.0 \|\| nyvar == 0.0)
50	return(-1);
51	r->slope = (l->xys - l->xs*l->ys/l->n) / nxvar;
52	r->intercept = (l->ys - r->slope*l->xs) / l->n;
53	r->correlation = r->slope*sqrt(nxvar/nyvar);
54	return(0);
55	}