How can I plot this kind of smoothed probability distribution in Matlab?

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If you have the equation to the PDF, you can simply plot it for specified values of x. For example,

Normal distribution

pNormal=@(x)1/sqrt(2*pi)*exp(-(x.^2)/2);
x=linspace(-4,4,1e3);
plot(x,pNormal(x));

Log-Normal distribution

pLogNormal=@(mu,sigma,x)1./(x*sigma*sqrt(2*pi)).*exp(-((log(x)-mu)./(sqrt(2)*sigma)).^2);
x=linspace(0,10,1e3);
mu=0;sigma=1;
plot(x,pLogNormal(mu,sigma,x));

You can vary sigma, mu and x according to your needs. The log-normal distribution is defined for x>0.

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Here is an example that uses a kernel smoother. (Just in case you don't know what distribution describes your data sample)

% generate some random data
X1 = 10 + randn(100,1);
X2 = 15 + 2*randn(75,1);
X3 = 25 + 3*randn(125,1);
X = vertcat(X1,X2,X3);

% use a kernel smoother to model X
foo = fitdist(X,'kernel')

% inspect the methods of foo
methods(foo)

% Plot the pdf of foo
range = linspace(min(X), max(X), 100);
bar = pdf(foo, range)
plot(range, bar)