How to store all outputs from this nested for loop

I have this for loop which goes through 3 different variables. I need to record all outputs so that I can plot the 3 variables and the outputs as a 3D colour surface plot similar to the second plot here https://www.mathworks.com/help/matlab/ref/surf.html

At the moment it only gives the last output so if someone can point me in the right direction to gettiing all outputs.

for s=0:9 % Variable 1
    for om=0.1:0.1:1 % Variable 2
        for mu=0.1:0.1:1 % Variable 3
            nll = mylikelihood(s,om,mu); % This is a function I made.
        end
    end
end

Also if anyone could see how I can vectorise the code so that it runs faster that would be appreciated.

[Walter Roberson]

That code cannot be vectorized unless your function can be vectorized, but you did not show the code for your function so we do not know what can be done with it.

[Leo Tu]

Thank you @Walter Roberson, the function is quite long as it contains a function itself and requires the temperatures vector attached. I'm not sure if it can be vectorized any further.

function nll = mylikelihood(s,om,mu)
% output; nll is the negative log likelihood
% input; s is lag, om is decay rate, mu is baseline rate
% T is temperatures, t = time in days
load("Temperature.mat")
T = T'; % from column vector to row vector
AT = T-min(T); % this is the adjusted positive temperatures

r = mypoiss(5,0.5,1); % this function can be seen below
t = max(s)+1:numel(AT);
for ti = 1:numel(t)
    k = abs(s:-1:(s-t(ti)+1));
    id = ((t(ti)-1):-1:0)+1;
    lambda(t(ti)) = mu+sum(om.^k.*AT(id))/sum(om.^k);
    % store all the results
end
nll = 0;
nll = nll - (r(ti).*log(lambda(t(ti)))) + (lambda(t(ti)));
end

function r = mypoiss(s,om,mu) 
% output; r is synthetic time series for number of cases
% input; s is lag, om is decay rate, mu is baseline rate
% T is temperatures, t = time in days
load("Temperature.mat")
T = T'; % from column vector to row vector
AT = T-min(T); % this is the adjusted positive temperatures

for t=s+1:length(AT)
k = abs(s:-1:(s-t+1)); 
id=[(t-1):-1:0]+1;
lambda(t) = mu+sum(om.^k.*AT(id))/sum(om.^k);
end

r = poissrnd(lambda);

Answer 1

[Stephen23]

Vs = 0:9; % Variable 1
Vom = 0.1:0.1:1; % Variable 2
Vmu = 0.1:0.1:1; % Variable 3
Ns = numel(Vs);
Nom = numel(Vom);
Nmu = numel(Vmu);
nll = nan(Ns,Nom,Nmu);
for k1 = 1:Ns
    for k2 = 1:Nom
        for k3 = 1:Nmu
            nll(k1,k2,k3) = mylikelihood(Vs(k1),Vom(k2),Vmu(k3));
        end
    end
end

[Leo Tu]

@Stephen Cobeldick Thank you for your help!