normcdf
Normal cumulative distribution function (CDF).
For each element of x, compute the cumulative distribution function (CDF) at x of the normal distribution with mean mu and standard deviation sigma. The size of p is the common size of x, mu and sigma. A scalar input functions as a constant matrix of the same size as the other inputs.
Default values are mu = 0, sigma = 1.
When called with three output arguments, [p, plo,
pup]
it computes the confidence bounds for p when the input
parameters mu and sigma 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.
[…] = normcdf (…, "upper")
computes the upper tail
probability of the normal distribution. This can be used to compute a
right-tailed p-value. To compute a two-tailed p-value, use
2 * normcdf (-abs (x), mu, sigma)
.
See also: norminv, normpdf, normrnd, normfit, normlike, normstat
Source Code: normcdf