src/common/linregr.c

/* Copyright (c) 1991 Regents of the University of California */

#ifndef lint
static char SCCSid[] = "$SunId$ LBL";
#endif

/*
 * Basic linear regression calculation.
 */

#include <math.h>

#include "linregr.h"


lrclear(l)                      /* initialize sum */
register LRSUM  *l;
{
        l->xs = l->ys = l->xxs = l->yys = l->xys = 0.0;
        l->n = 0;
}


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);
}


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:	2.2
Committed:	Fri Mar 5 15:14:02 1993 UTC (32 years, 8 months ago) by greg
Content type:	text/plain
Branch:	MAIN
Changes since 2.1:	+2 -0 lines
Log Message:	portability improvements
#	User	Rev	Content
1	greg	1.1	/* Copyright (c) 1991 Regents of the University of California */
2
3			#ifndef lint
4			static char SCCSid[] = "$SunId$ LBL";
5			#endif
6
7			/*
8			* Basic linear regression calculation.
9			*/
10
11	greg	2.2	#include <math.h>
12
13	greg	1.1	#include "linregr.h"
14
15
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			flrpoint(x, y, l) /* add point (x,y) to sum */
25			double x, y;
26			register LRSUM *l;
27			{
28			l->xs += x;
29			l->ys += y;
30			l->xxs += x*x;
31			l->yys += y*y;
32			l->xys += x*y;
33			return(++l->n);
34			}
35
36
37			lrfit(r, l) /* compute linear regression */
38			register LRLIN *r;
39			register LRSUM *l;
40			{
41			double nxvar, nyvar;
42
43			if (l->n < 2)
44			return(-1);
45			nxvar = l->xxs - l->xs*l->xs/l->n;
46			nyvar = l->yys - l->ys*l->ys/l->n;
47			if (nxvar == 0.0 \|\| nyvar == 0.0)
48			return(-1);
49			r->slope = (l->xys - l->xs*l->ys/l->n) / nxvar;
50			r->intercept = (l->ys - r->slope*l->xs) / l->n;
51			r->correlation = r->slope*sqrt(nxvar/nyvar);
52			return(0);
53			}