logncdf
"upper"
)"upper"
)Log-normal cumulative distribution function (CDF).
For each element of x, compute the cumulative distribution function (CDF) of the log-normal distribution with mean mu and standard deviation sigma corresponding to the associated normal distribution. 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.
If a random variable follows this distribution, its logarithm is normally distributed with mean mu and standard deviation sigma.
Default parameter values are mu = 0
and
sigma = 1
. Both parameters must be reals and
sigma > 0
. For sigma <= 0
, NaN
is
returned.
When called with three output arguments, i.e. [p, plo,
pup]
, logncdf
computes the confidence bounds for p when
the input parameters mu and sigma are estimates. In such case,
pcov, a matrix containing the covariance matrix of the
estimated parameters, is necessary. Optionally, alpha, which has a
default value of 0.05, specifies the 100 * (1 - alpha)
percent
confidence bounds. plo and pup are arrays of the same size as
p containing the lower and upper confidence bounds.
[…] = logncdf (…, "upper")
computes the upper tail
probability of the log-normal distribution with parameters mu and
sigma, at the values in x.
Further information about the log-normal distribution can be found at https://en.wikipedia.org/wiki/Log-normal_distribution
See also: logninv, lognpdf, lognrnd, lognfit, lognlike, lognstat
Source Code: logncdf
## Plot various CDFs from the log-normal distribution x = 0:0.01:3; p1 = logncdf (x, 0, 1); p2 = logncdf (x, 0, 0.5); p3 = logncdf (x, 0, 0.25); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r") grid on legend ({"μ = 0, σ = 1", "μ = 0, σ = 0.5", "μ = 0, σ = 0.25"}, ... "location", "southeast") title ("Log-normal CDF") xlabel ("values in x") ylabel ("probability") |