Function Reference: wblcdf
- statistics: p = wblcdf (x)
- statistics: p = wblcdf (x, lambda)
- statistics: p = wblcdf (x, lambda, k)
- statistics: p = wblcdf (…,
"upper") - statistics: [p, plo, pup] = wblcdf (x, lambda, k, pcov)
- statistics: [p, plo, pup] = wblcdf (x, lambda, k, pcov, alpha)
- statistics: [p, plo, pup] = wblcdf (…,
"upper")
Weibull cumulative distribution function (CDF).
For each element of x, compute the cumulative distribution function (CDF) of the Weibull distribution with scale parameter lambda and shape parameter k. The size of p is the common size of x, lambda and k. A scalar input functions as a constant matrix of the same size as the other inputs.
Default values are lambda = 1, k = 1.
When called with three output arguments, [p, plo,
pup] it computes the confidence bounds for p when the input
parameters lambda and k are estimates. In such case, pcov,
a 2-by-2 matrix containing the covariance matrix of the estimated parameters,
is necessary. Optionally, alpha has a default value of 0.05, and
specifies 100 * (1 - alpha)% confidence bounds. plo and pup
are arrays of the same size as p containing the lower and upper
confidence bounds.
[…] = wblcdf (…, "upper") computes the upper tail
probability of the lognormal distribution.
Further information about the Weibull distribution can be found at https://en.wikipedia.org/wiki/Weibull_distribution
See also: wblinv, wblpdf, wblrnd, wblstat, wblplot
Source Code: wblcdf
Example: 1
## Plot various CDFs from the Weibull distribution
x = 0:0.001:2.5;
p1 = wblcdf (x, 1, 0.5);
p2 = wblcdf (x, 1, 1);
p3 = wblcdf (x, 1, 1.5);
p4 = wblcdf (x, 1, 5);
plot (x, p1, "-b", x, p2, "-r", x, p3, "-m", x, p4, "-g")
grid on
legend ({"λ = 1, k = 0.5", "λ = 1, k = 1", ...
"λ = 1, k = 1.5", "λ = 1, k = 5"}, "location", "southeast")
title ("Weibull CDF")
xlabel ("values in x")
ylabel ("probability")
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