p = normcdf(x)
p = normcdf(x, mu, sigma)
p = normcdf(..., 'upper')
[p, pLo, pUp] = normcdf(x, mu, sigma, pCov)
[p, pLo, pUp] = normcdf(x, mu, sigma, pCov, alpha)
| Parameter | Description |
|---|---|
| x | real scalar or array: values where the distribution is evaluated. |
| mu | real scalar or array, 0 by default: mean. |
| sigma | positive real scalar or array, 1 by default: standard deviation. |
| pCov | 2-by-2 covariance matrix for the estimated parameters. |
| alpha | scalar in (0,1), 0.05 by default: significance level for confidence bounds. |
| Parameter | Description |
|---|---|
| p | scalar or array: cumulative probabilities. |
| pLo | lower confidence bound. |
| pUp | upper confidence bound. |
normcdf evaluates the cumulative distribution function of the normal distribution.
Scalar inputs are expanded to match array inputs. If any distribution input uses single precision, the result uses single precision.
x = [-2 -1 0 1 2];
p = normcdf(x);
upperTail = normcdf(x, 0, 1, 'upper');
[p, pLo, pUp] = normcdf(0, 0, 1, [0.04 0; 0 0.01]);| Version | Description |
|---|---|
| 2.0.0 | initial version |