unifit
Estimate parameter and confidence intervals for the continuous uniform distribution.
paramhat = unifit (x) returns the maximum likelihood
estimate (MLE) of the parameters a and b of the continuous
uniform distribution given the data in x. x must be a vector.
[paramhat, paramci] = unifit (x, alpha) also
returns the 100 * (1 - alpha) percent confidence intervals of
the estimated parameter. By default, the optional argument alpha is
0.05 corresponding to 95% confidence intervals. Pass in [] for
alpha to use the default values.
[…] = unifit (x, alpha, freq) accepts a
frequency vector, freq, of the same size as x. freq
typically contains integer frequencies for the corresponding elements in
x, but it can contain any non-integer non-negative values. By default,
or if left empty, freq = ones (size (x)).
Further information about the continuous uniform distribution can be found at https://en.wikipedia.org/wiki/Discrete_uniform_distribution
See also: unifcdf, unifinv, unifpdf, unifrnd, unifstat
Source Code: unifit
## Sample 2 populations from different continuous uniform distibutions
rand ("seed", 5); # for reproducibility
r1 = unifrnd (2, 5, 2000, 1);
rand ("seed", 6); # for reproducibility
r2 = unifrnd (3, 9, 2000, 1);
r = [r1, r2];
## Plot them normalized and fix their colors
hist (r, 0:0.5:10, 2);
h = findobj (gca, "Type", "patch");
set (h(1), "facecolor", "c");
set (h(2), "facecolor", "g");
hold on
## Estimate their probability of success
a_bA = unifit (r(:,1));
a_bB = unifit (r(:,2));
## Plot their estimated PDFs
x = [0:10];
y = unifpdf (x, a_bA(1), a_bA(2));
plot (x, y, "-pg");
y = unifpdf (x, a_bB(1), a_bB(2));
plot (x, y, "-sc");
xlim ([1, 10])
ylim ([0, 0.5])
legend ({"Normalized HIST of sample 1 with a=2 and b=5", ...
"Normalized HIST of sample 2 with a=3 and b=9", ...
sprintf("PDF for sample 1 with estimated a=%0.2f and b=%0.2f", ...
a_bA(1), a_bA(2)), ...
sprintf("PDF for sample 2 with estimated a=%0.2f and b=%0.2f", ...
a_bB(1), a_bB(2))})
title ("Two population samples from different continuous uniform distibutions")
hold off
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