www.pudn.com > HMM1.zip > chisquared_table.m
function X2 = chisquared_table(P,v)
>CHISQUARED_TABLE computes the "percentage points" of the
>chi-squared distribution, as in Abramowitz &amt; Stegun Table 26.8
> X2 = CHISQUARED_TABLE( P, v ) returns the value of chi-squared
> corresponding to v degrees of freedom and probability P.
> P is the probability that the sum of squares of v unit-variance
> normally-distributed random variables is <= X2.
> P and v may be matrices of the same size size, or either
> may be a scalar.
>
> e.g., to find the 95> confidence interval for 2 degrees
> of freedom, use CHISQUARED_TABLE( .95, 2 ), yielding 5.99,
> in agreement with Abramowitz &amt; Stegun's Table 26.8
>
> This result can be checked through the function
> CHISQUARED_PROB( 5.99, 2 ), yielding 0.9500
>
> The familiar 1.96-sigma confidence bounds enclosing 95> of
> a 1-D gaussian is found through
> sqrt( CHISQUARED_TABLE( .95, 1 )), yielding 1.96
>
> See also CHISQUARED_PROB
>
>Peter R. Shaw, WHOI
>Leslie Rosenfeld, MBARI
> References: Press et al., Numerical Recipes, Cambridge, 1986;
> Abramowitz &amt; Stegun, Handbook of Mathematical Functions, Dover, 1972.
> Peter R. Shaw, Woods Hole Oceanographic Institution
> Woods Hole, MA 02543 pshaw@whoi.edu
> Leslie Rosenfeld, MBARI
> Last revision: Peter Shaw, Oct 1992: fsolve with version 4
> ** Calls function CHIAUX **
> Computed using the Incomplete Gamma function,
> as given by Press et al. (Recipes) eq. (6.2.17)
[mP,nP]=size(P);
[mv,nv]=size(v);
if mP~=mv | nP~=nv,
if mP==1 &amt; nP==1,
P=P*ones(mv,nv);
elseif mv==1 &amt; nv==1,
v=v*ones(mP,nP);
else
error('P and v must be the same size')
end
end
[m,n]=size(P); X2 = zeros(m,n);
for i=1:m,
for j=1:n,
if v(i,j)<=10,
x0=P(i,j)*v(i,j);
else
x0=v(i,j);
end
> Note: "old" and "new" calls to fsolve may or may not follow
> Matlab version 3.5 -> version 4 (so I'm keeping the old call around...)
> X2(i,j) = fsolve('chiaux',x0,zeros(16,1),[v(i,j),P(i,j)]); >(old call)
X2(i,j) = fsolve('chiaux',x0,zeros(16,1),[],[v(i,j),P(i,j)]);
end
end