Statistics: invgcdf

### Function Reference: `invgcdf`

statistics: p = invgcdf (x, mu, lambda)
statistics: p = invgcdf (x, mu, lambda, `"upper"`)

Inverse Gaussian cumulative distribution function (CDF).

For each element of x, compute the cumulative distribution function (CDF) of the inverse Gaussian distribution with scale parameter mu and shape parameter lambda. The size of p is the common size of x, mu and lambda. A scalar input functions as a constant matrix of the same size as the other inputs.

`p = invgcdf (x, mu, lambda, "upper")` computes the upper tail probability of the inverse Gaussian distribution with parameters mu and lambda, at the values in x.

The inverse Gaussian CDF is only defined for `mu > 0` and `lambda > 0`.

Further information about the inverse Gaussian distribution can be found at https://en.wikipedia.org/wiki/Inverse_Gaussian_distribution

See also: invginv, invgpdf, invgrnd, invgfit, invglike

Source Code: invgcdf

### Example: 1

     ## Plot various CDFs from the inverse Gaussian distribution
     x = 0:0.001:3;
     p1 = invgcdf (x, 1, 0.2);
     p2 = invgcdf (x, 1, 1);
     p3 = invgcdf (x, 1, 3);
     p4 = invgcdf (x, 3, 0.2);
     p5 = invgcdf (x, 3, 1);
     plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-y")
     grid on
     xlim ([0, 3])
     legend ({"μ = 1, σ = 0.2", "μ = 1, σ = 1", "μ = 1, σ = 3", ...
              "μ = 3, σ = 0.2", "μ = 3, σ = 1"}, "location", "southeast")
     title ("Inverse Gaussian CDF")
     xlabel ("values in x")
     ylabel ("probability")