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

Input arguments must be double or single; integer, logical, and character arrays are rejected. MATLAB accepts a character array and evaluates it at the character codes, which Octave deliberately does not, since a character array is an integer type and integers are refused too.

The prob.WeibullDistribution class names these same two parameters A and B, after MATLAB. lambda is its A and k is its B.

See also: wblinv, wblpdf, wblrnd, wblstat, wblplot

Source Code: wblcdf