void AssocEntropy::Calc(int ** nn, int ni, int nj)
{
int i, j;
double p;
Vector sumi(ni), sumj(nj);
sumi.Zero();
sumj.Zero();
sum = 0.0;
// Get the row totals
for (i = 0; i < ni; i++)
for ( j = 0; j < nj; j++)
{
sumi[i] += nn[i][j];
sum += nn[i][j];
}
// Get the column totals
for (j = 0; j < nj; j++)
for ( i = 0; i < ni; i++ )
sumj[j] += nn[i][j];
// Entropy of the x distribution
hx = 0.0;
for (i = 0; i < ni; i++)
if (sumi[i] > FPMIN)
{
p = sumi[i] / sum;
hx -= p * log(p);
}
// Entropy of the y distribution
hy = 0.0;
for (j = 0; j < nj; j++)
if (sumj[j] > FPMIN)
{
p = sumj[j] / sum;
hx -= p * log(p);
}
// Total entropy for the table
h = 0.0;
for (i = 0; i < ni; i++)
for (j = 0; j < nj; j++)
if (nn[i][j] > 0)
{
p = nn[i][j] / sum;
h -= p * log ( p );
}
hygx = h - hx;
hxgy = h - hy;
uygx = (hy - hygx) / ( hy + TINY );
uxgy = (hx - hxgy) / ( hx + TINY );
uxy = 2.0 * ( hx + hy - h ) / ( hx + hy + TINY );
isValid = 1;
}
void AssocChi::Calc(int ** nn, int ni, int nj)
{
int nnj, nni, j, i, minij;
double expected, temp;
Vector sumi(ni), sumj(nj);
sumi.Zero();
sumj.Zero();
sum = 0.0;
nni = ni;
nnj = nj;
// Get the row totals
for (i = 0; i < ni; i++)
{
for ( j = 0; j < nj; j++)
{
sumi[i] += nn[i][j];
sum += nn[i][j];
}
if ( sumi[i] < FPMIN) --nni; // eliminate zero rows by reducing number
}
// Get the column totals
for (j = 0; j < nj; j++)
{
for ( i = 0; i < ni; i++ )
sumj[j] += nn[i][j];
if ( sumj[j] < FPMIN) --nnj; // eliminated any zero columns
}
df = nni * nnj - nni - nnj + 1; // corrected degrees of freedom
chisq = 0.0;
for (i = 0; i < ni; i++)
{
for (j = 0; j < nj; j++)
{
expected = sumj[j] * sumi[i] / sum;
temp = nn[i][j] - expected;
chisq += temp * temp / (expected + TINY);
}
}
prob = df ? gammq ( 0.5 * df, 0.5 * chisq ) : 1.0;
lop = prob > 1e-100 ? -log10(prob) : 99.999;
minij = nni < nnj ? nni - 1 : nnj - 1;
cramrv = minij ? sqrt ( chisq / ( sum * minij ) ) : 0.0;
ccc = sum ? sqrt ( chisq / ( chisq + sum) ) : 0.0;
isValid = 1;
}
int main(){
std::cout << sumi(std::cin);
}
