Functions and CALL Routines

# SDF Function

Returns a survival function.
 Category: Probability See: CDF Function

## Syntax

 SDF(dist, quantile, parm-1,...,parm-k)

### Arguments

dist

is a character string that identifies the distribution. Valid distributions are as follows:

Distribution Argument
Bernoulli BERNOULLI
Beta BETA
Binomial BINOMIAL
Cauchy CAUCHY
Chi-Square CHISQUARE
Exponential EXPONENTIAL
F F
Gamma GAMMA
Geometric GEOMETRIC
Hypergeometric HYPERGEOMETRIC
Laplace LAPLACE
Logistic LOGISTIC
Lognormal LOGNORMAL
Negative binomial NEGBINOMIAL
Normal NORMAL|GAUSS
Normal mixture NORMALMIX
Pareto PARETO
Poisson POISSON
T T
Uniform UNIFORM
Wald (inverse Gaussian) WALD|IGAUSS
Weibull WEIBULL

Note:   Except for T, F, and NORMALMIX, you can minimally identify any distribution by its first four characters.

quantile

is a numeric constant, variable or expression that specifies the value of a random variable.

parm-1,...,parm-k

are optional shape, location, or scale parameters appropriate for the specific distribution.

The SDF function computes the survival function (upper tail) from various continuous and discrete distributions. For more information, see the Details.

SAS Statements Results
`y=sdf('BERN',0,.25);`
`0.25`
`y=sdf('BETA',0.2,3,4);`
`0.09011`
`y=sdf('BINOM',4,.5,10);`
`0.62305`
`y=sdf('CAUCHY',2);`
`0.14758`
`y=sdf('CHISQ',11.264,11);`
`0.42142`
`y=sdf('EXPO',1);`
`0.36788`
`y=sdf('F',3.32,2,3);`
`0.17361`
`y=sdf('GAMMA',1,3);`
`0.91970`
`y=sdf('HYPER',2,200,50,10);`
`0.47633`
`y=sdf('LAPLACE',1);`
`0.18394`
`y=sdf('LOGISTIC',1);`
`0.26894`
`y=sdf('LOGNORMAL',1);`
`0.5`
`y=sdf('NEGB',1,.5,2);`
`0.5`
`y=sdf('NORMAL',1.96);`
`0.025`
```y=pdf('NORMALMIX',2.3,3,.33,.33,.34,
.5,1.5,2.5,.79,1.6,4.3);```
```
0.2819```
`y=sdf('PARETO',1,1);`
`1`
`y=sdf('POISSON',2,1);`
`0.08030`
`y=sdf('T',.9,5);`
`0.20469`
`y=sdf('UNIFORM',0.25);`
`0.75`
`y=sdf('WALD',1,2);`
`0.37230`
`y=sdf('WEIBULL',1,2);`
`0.36788`

 Functions:

 Previous Page | Next Page | Top of Page