ncfpdf
statistics: y = ncfpdf (x, df1, df2, lambda)
Noncentral -probability density function (PDF).
For each element of x, compute the probability density function (PDF) of the noncentral -distribution with df1 and df2 degrees of freedom and noncentrality parameter lambda. The size of y is the common size of x, df1, df2, and lambda. A scalar input functions as a constant matrix of the same size as the other inputs.
Further information about the noncentral -distribution can be found at https://en.wikipedia.org/wiki/Noncentral_F-distribution
See also: ncfcdf, ncfinv, ncfrnd, ncfstat, fpdf
Source Code: ncfpdf
Plot various PDFs from the noncentral F distribution
x = 0:0.01:5;
y1 = ncfpdf (x, 2, 5, 1);
y2 = ncfpdf (x, 2, 5, 2);
y3 = ncfpdf (x, 5, 10, 1);
y4 = ncfpdf (x, 10, 20, 10);
plot (x, y1, '-r', x, y2, '-g', x, y3, '-k', x, y4, '-m')
grid on
xlim ([0, 5])
ylim ([0, 0.8])
legend ({'df1 = 2, df2 = 5, λ = 1', 'df1 = 2, df2 = 5, λ = 2', ...
'df1 = 5, df2 = 10, λ = 1', 'df1 = 10, df2 = 20, λ = 10'}, ...
'location', 'northeast')
title ('Noncentral F PDF')
xlabel ('values in x')
ylabel ('density')
Compare the noncentral F PDF with LAMBDA = 10 to the F PDF with the same number of numerator and denominator degrees of freedom (5, 20)
x = 0.01:0.1:10.01;
y1 = ncfpdf (x, 5, 20, 10);
y2 = fpdf (x, 5, 20);
plot (x, y1, '-', x, y2, '-');
grid on
xlim ([0, 10])
ylim ([0, 0.8])
legend ({'Noncentral F(5,20,10)', 'F(5,20)'}, 'location', 'northeast')
title ('Noncentral F vs F PDFs')
xlabel ('values in x')
ylabel ('density')