myconf_utils.c,v

这是P2P流媒体方案－NICE的实现源码

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date	2002.07.02.19.29.58;	author rbraud;	state Exp;
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@Initial revision
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@#include <stdio.h>
#include <math.h>
#include <stdlib.h>

/*************** FUNCTION TO CALCULATE CONFIDENCE STATISTICS  ***************


Function Usage:

        confidence(x,n,conf-level,mu_x,delta_x)


        Input parameters:

        long x[MAXCAMP]        vector of data values 
        int n                  number of data values
        float conf-level         confidence level (90%, 95%, 98% or 99%) 


        Modified parameters:

        double mu_x              average of data values 
        double delta_x           confidence interval 


Function Behavior:

        This function calculates the confidence interval at 90, 95, 98
or 99% confidence for a set of data values.  For less than 30 data values,
it uses the Student's T distribution.  For more than 30 data values,
it uses the normal (Gaussian) distribution. 

*******************************************************************************/

float tabella(short nu, float conf_level);

int confidence(long * x,int n,float conf_level,float * mu_x,float *delta_x)
{
        short nu=n-1;     
        float sigma_x;   
        float t;         
	//        float tabella(); /* function to return Student's T value */

        register float num=0.0;
        register short i;

        /*      Calculate the average: */
        for (i=0; i<=nu; i++)
                num = num + x[i];
        *mu_x = num/n;

        /*      Calculate the variance: */
        num=0.0;
        for (i=0; i<=nu; i++)
                num = num + (*mu_x - x[i]) * (*mu_x - x[i]);
        sigma_x = sqrt(num/n);

        /*      Get the Student's T value: */
        t = tabella(nu,conf_level);

        /*      Calculate confidence interval: */
        if (nu <= 30)
                *delta_x = sigma_x * t / sqrt(nu);  
        else
                *delta_x = sigma_x * t / sqrt(n);   
	return 0;
}



float tabella(short nu, float conf_level)
{
        short riga=nu-1;
        short column;
        float t;         
        static float val_tabella[31][4] =
        /* table containing Student's T distribution
           column 1 (.90), column 2 (.95), column 3 (.98), column 4 (.99) */
        {
		{6.314,12.706,31.821,63.657},
		{2.920, 4.303, 6.965, 9.925},
		{2.353, 3.182, 4.541, 5.841},
		{2.132, 2.776, 3.747, 4.604},
		{2.015, 2.571, 3.365, 4.032},
		{1.943, 2.447, 3.143, 3.707},
		{1.895, 2.365, 2.998, 3.499},
		{1.860, 2.306, 2.896, 3.355},
		{1.833, 2.262, 2.821, 3.250},
		{1.812, 2.228, 2.764, 3.169},
		{1.796, 2.201, 2.718, 3.106},
		{1.782, 2.179, 2.681, 3.055},
		{1.771, 2.160, 2.650, 3.012},
		{1.761, 2.145, 2.624, 2.977},
		{1.753, 2.131, 2.602, 2.947},
		{1.746, 2.120, 2.583, 2.921},
		{1.740, 2.110, 2.567, 2.898},
		{1.734, 2.101, 2.552, 2.878},
		{1.729, 2.093, 2.539, 2.861},
		{1.725, 2.086, 2.528, 2.845},
		{1.721, 2.080, 2.518, 2.831},
		{1.717, 2.074, 2.508, 2.819},
		{1.714, 2.069, 2.500, 2.807},
		{1.711, 2.064, 2.492, 2.797},
		{1.708, 2.060, 2.485, 2.787},
		{1.706, 2.056, 2.479, 2.779},
		{1.703, 2.052, 2.473, 2.771},
		{1.701, 2.048, 2.467, 2.763},
		{1.699, 2.045, 2.462, 2.756},
		{1.697, 2.042, 2.457, 2.750},
		{1.645, 1.960, 2.326, 2.576},	/* nu=infinito 
                        	 	           (stimatore gaussiano) */


        };

        if (conf_level >= 0.85 && conf_level <= 0.925)
                column=0;
        else if (conf_level >= 0.925 && conf_level <= 0.965)
               column=1;
        else if (conf_level >= 0.965 && conf_level <= 0.985)
                column=2;
        else if (conf_level >= 0.985 && conf_level <= 0.9945)
                column=3;
        else
        {
                fprintf(stderr,"The confidence level must be 90%%,95%%,98%% or 99%%).\n");
                exit(1);
        }
        if (nu <= 30)
                t=val_tabella[riga][column];    /* stimatore di Student */
        else
                t=val_tabella[30][column];      /* stimatore gaussiano */
        return(t);
}

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