I am not sure that it is your answer or not. But I have used this function to find the best values for p and q for a given time series y
function ar=checkArima(y,pp,qq)
% pp is the maximum for p
% qq is the maximum for q
LOGL = zeros(pp+1,qq+1); %Initialize
PQ = zeros(pp+1,qq+1);
for p = 1:pp+1
for q = 1:qq+1
mod = arima(p-1,0,q-1)
[fit,~,logL] = estimate(mod,y,'print',false);
LOGL(p,q) = logL;
PQ(p,q) = p+q;
end
end
LOGL = reshape(LOGL,(pp+1)*(qq+1),1);
PQ = reshape(PQ,(pp+1)*(qq+1),1);
[~,bic] = aicbic(LOGL,PQ+1,100);
ar=reshape(bic,pp+1,qq+1);
% the rows correspond to the AR degree (p) and the
% columns correspond to the MA degree (q). The smallest value is best
