mu=1; 
sigma=2;  % dispersion parameter
left=-0.5; % Lower limit
right=5; % Upper limit
% Generate a random number from the distribution above
x=tobitrnd(mu,sigma,left,right);
disp(x)

mu=1; 
% dispersion parameter
sigma=2;  
left=-0.5; % Lower limit
right=5; % Upper limit
% Generate an array of size 2x3x5 of random numbers from the distribution above
mm=2;   nn=3;
X=tobitrnd(mu,sigma,left,right, mm,nn);
disp(X)

mu=1; 
sigma=2;  % dispersion parameter
left=-0.5; % Lower limit
right=5; % Upper limit
% Generate an array of size 2x3x5 of random numbers from the distribution above
mm=2;   nn=3; oo=5;
X=tobitrnd(mu,sigma,left,right, mm,nn,oo);
disp(X)

mu=3; sigma=1;  left=2; right=4.2;
% Generate n observations
n=10000;
x=tobitrnd(mu,sigma,left,right,n);
% Classes are close to the left and open to the right that is [ ), except
% for the last one which is closed to the left and to the right,
%  that is [ ]
edges=[left linspace(left+1e-10, right-1e-10,10) right];
% First class goes from left (included) to left+1e-10
% ...
% Last class goes from right-1e-10 to right (right is included in the last class)
% The length of edges is 12 so there are 11 classes
% Set up string for the title of the figures
para=['with parameters \mu,\sigma,left,right= (' num2str(mu) ',' num2str(sigma) ',' num2str(left) ',' num2str(right) ')']; 
h= histogram(x,edges,'Normalization','probability');
title('Histogram of relative frequencies from Tobit distribution',para)
xlabel('Classes')
freq=h.Values;
% Create a new figure to compare theoretical and empirical frequencies
figure
% Compute the probabilities for each class in vector yy
y=tobitcdf(edges,mu,sigma,left,right);
yy=(y(2:end)-y(1:end-1)); 
% First element of yy is the probability of tobit distribution is equal to left
yy(1)=tobitcdf(left,mu,sigma,left,right); 
% set the labels for the classes
% From MATLAB 2023b the  x coordinates of bar can be a string array
lab=string(edges(1:end-1))+"-"+string(edges(2:end));
% The instruction below is just for compatibility with older versions of
% MATLAB
lab=categorical(lab,lab);
hold('on')
bar(lab,[freq' yy'])
legend(["Emprical relative frequencies" "Theoretical probabilities"])
title(['Data from Tobit distribution', para])
xlabel('Classes')