cdf - Cumulative distribution functions

Syntax

Y = cdf(name,X,A) Y = cdf(name,X,A,B) Y = cdf(name,X,A,B,C)

Description

Y = cdf(name,X,A) computes the cumulative distribution function for the one-parameter family of distributions specified by name. A contains parameter values for the distribution. The cumulative distribution function is evaluated at the values in X and its values are returned in Y.

If X and A are arrays, they must be the same size. If X is a scalar, it is expanded to a constant matrix the same size as A. If A is a scalar, it is expanded to a constant matrix the same size as X.

Y is the common size of X and A after any necessary scalar expansion.

Y = cdf(name,X,A,B) computes the cumulative distribution function for two-parameter families of distributions, where parameter values are given in A and B.

If X, A, and B are arrays, they must be the same size. If X is a scalar, it is expanded to a constant matrix the same size as A and B. If either A or B are scalars, they are expanded to constant matrices the same size as X.

Y is the common size of X, A, and B after any necessary scalar expansion.

Y = cdf(name,X,A,B,C) computes the cumulative distribution function for three-parameter families of distributions, where parameter values are given in A, B, and C.

If X, A, B, and C are arrays, they must be the same size. If X is a scalar, it is expanded to a constant matrix the same size as A, B, and C. If any of A, B or C are scalars, they are expanded to constant matrices the same size as X.

Y is the common size of X, A, B, and C after any necessary scalar expansion.

Acceptable strings for name are:

'beta' (Beta distribution)
'bino' (Binomial distribution)
'chi2' (Chi-square distribution)
'exp' (Exponential distribution)
'ev' (Extreme value distribution)
'f' (F distribution)
'gam' (Gamma distribution)
'gev' (Generalized extreme value distribution)
'gp' (Generalized Pareto distribution)
'geo' (Geometric distribution)
'hyge' (Hypergeometric distribution)
'logn' (Lognormal distribution)
'nbin' (Negative binomial distribution)
'ncf' (Noncentral F distribution)
'nct' (Noncentral tdistribution)
'ncx2' (Noncentral chi-square distribution)
'norm' (Normal distribution)
'poiss' (Poisson distribution)
'rayl' (Rayleigh distribution)
't' (t distribution)
'unif' (Uniform distribution)
'unid' (Discrete uniform distribution)
'wbl' (Weibull distribution)

Examples

Compute the cdf of the normal distribution with mean 0 and standard deviation 1 at inputs –2, –1, 0, 1, 2:

p1 = cdf('Normal',-2:2,0,1)
p1 =
  0.0228  0.1587  0.5000  0.8413  0.9772

The order of the parameters is the same as for normcdf.

Compute the cdfs of Poisson distributions with rate parameters 0, 1, ..., 4 at inputs 1, 2, ..., 5, respectively:

p2 = cdf('Poisson',0:4,1:5)
p2 =
  0.3679  0.4060  0.4232  0.4335  0.4405

The order of the parameters is the same as for poisscdf.

cdf - Cumulative distribution functions

Syntax

Description

Examples

See Also

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