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Can you please help to fix the pN calculation with the users in the queue and being served. function [ Ws , Wq , c

Can you please help to fix the pN calculation with the users in the queue and being served. function [Ws, Wq, c_util, p_drop, p_state]= MMCQ(lambda, mu, c, Nwait)
% Calculate the utilization factor
% rho = lambda / mu;
rho = lambda /(c * mu);
% Calculate the average number of customers in the queue
% c_bar = rho *(1+(c * rho)^(c -1)/ factorial(c -1)/(1- rho)^2); % Fix c_bar calculation
% Calculate p0(probability of no customers in the system)
p0_denom = sum((c * rho).^(0:(c -1))/ factorial(0:(c -1)))+(c * rho)^c / factorial(c)/(1- rho); % Fix p0_denom calculation
p0=1/ p0_denom;
% Calculate the probability of zero customers in the system
% P0=1/(sum((c*rho).^(0:c-1)/ factorial(0:c-1))+((c*rho)^c /(factorial(c)*(1- rho))));
p_state = zeros(1, Nwait +1);
p_state(1)= p0;
% Calculate pN (probability of having N customers in the system)
% for i =1:Nwait
%% p_state(1)=(c-i)/(c -(c - i));
% if i <= c
% p_state(i +1)=(rho^i / factorial(i))* p0;
% else
% p_state(i +1)=(rho^i / factorial(c)*(c^(i - c)))* p0; % Fix the p_state calculation
% end
% end
for i =1:Nwait
ci = min(i, c);
if i <= c
p_state(i +1)= ci / c * p_state(i)* rho / factorial(i);
else
p_state(i +1)= c^ci / factorial(ci)* p_state(i)* rho^i / factorial(c);
end
end
% Normalize p_state to ensure probabilities sum to 1
p_state = p_state / sum(p_state);
pN = p_state(Nwait +1); % Probability of having N customers in the system
% Calculate lambda_loss and lambda_eff
lambda_loss = lambda * p_state(Nwait +1);
lambda_eff = lambda - lambda_loss;
% Calculate Lq (average number of customers in the queue)
Lq = sum((0:Nwait).* p_state);
% Calculate Ls (average number of customers in the system)
Ls = Lq + lambda_eff / mu;
% Calculate the utilization
c_bar = Ls - Lq;
c_util = c_bar / c;
% Calculate p_drop (probability of a customer being dropped)
p_drop = p_state(Nwait +1);
% Calculate Ws and Wq
Ws = Ls / lambda_eff;
Wq = Lq / lambda_eff;
end% c = Total service time / Total time
lambda =2; % arrival rate
mu =5; % service rate
c =3; % number of servers
Nwait =15
% Call the MMCQ function with the given parameters
%[Ws, Wq, c_util, p_drop, p_state]= MMCQ(lambda, mu, c, Nwait);
[Ws, Wq, c_util, p_drop, p_state]= MMCQ(1,0.5,4,5);
% Define a relative error function
rel_error = @(x, y) abs(x - y)/ y;
% Validate the results and print "PASS" or "FAIL" for each metric
if rel_error(Ws,2.1557)<0.005
fprintf('Ws =%6.3f PASS
', Ws);
else
fprintf('Ws =%6.3f FAIL
', Ws);
end
if rel_error(Wq,0.1557)<0.005
fprintf('Wq =%6.3f PASS
', Wq);
else
fprintf('Wq =%6.3f FAIL
', Wq);
end
if rel_error(c_util, 0.4986)<0.005
fprintf('c_util =%6.3f PASS
', c_util);
else
fprintf('c_util =%6.3f FAIL
', c_util);
end
if rel_error(p_drop, 0.00272)<0.005
fprintf('p_drop =%8.5f PASS
', p_drop);
else
fprintf('p_drop =%8.5f FAIL
', p_drop);
end
fprintf('p_state: %s
', num2str(p_state));
fprintf('sum(p_state): %f
', sum(p_state));
% Extra Tests: p_state
% p_state should have Nwait+1 probabilities
% disp(['The probability of being in state ', num2str(Nwait),' is ', num2str(p_state(Nwait +1))]);
disp(['The probability of being in state ',' is ', num2str(p_state)]);
% Check that the probabilities sum to 1
if abs(sum(p_state)-1)<1e-5
disp('The probabilities sum to 1. Test PASSED.');
else
disp('The probabilities do not sum to 1. Test FAILED.');
end

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