SQUANTILE Function

Returns the quantile from a distribution when you specify the right probability (SDF).

Category:	Quantile
Restriction:	This function is not valid on the CAS server.
See:	SDF Function

Table of Contents

Example 1: Using the LOGISTIC Distribution

Example 2: Using the Conway-Maxwell-Poisson Distribution

Syntax

SQUANTILE(distribution, probability, parameter-1, ..., parameter-k)

Required Arguments

distribution

is a character constant, variable, or expression that identifies the distribution. Valid distributions are as follows:

Distribution	Argument
Bernoulli	`BERNOULLI`
Beta	`BETA`
Binomial	`BINOMIAL`
Cauchy	`CAUCHY`
Chi-Square	`CHISQUARE`
Conway-Maxwell-Poisson	`CONMAXPOI`
Exponential	`EXPONENTIAL`
F	`F`
Gamma	`GAMMA`
Generalized Poisson	`GENPOISSON`
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`
Tweedie	`TWEEDIE`
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.

probability

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

parameter-1, …, parameter-k

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

Details

The SQUANTILE function computes the quantile from the specified continuous or discrete distribution, based on the probability value that is provided. For more information, see Details in the CDF function.

The Conway-Maxwell-Poisson distribution of the SQUANTILE function returns the counts value y that is the smallest integer whose SDF value is less than p. The syntax for the Conway-Maxwell-Poisson distribution in the SQUANTILE function has the following form:

SQUANTILE('CONMAXPOI',p,λ,ν)

is a real number between 0 and 1, inclusively.

is similar to the mean, as in the Poisson distribution.

is a dispersion parameter.

For more information, see “Conway-Maxwell-Poisson” distribution in the PDF function.

For more information about the distributions that are listed in the table, see PDF Function.

Examples

Example 1: Using the LOGISTIC Distribution

data;
   dist='logistic';
   sdf=squantile(dist, 1.e-20);
   put sdf=;
   p=sdf(dist, sdf);
   put p=/* p will be 1.e-20 */;
run;

SAS writes the following results to the log:

sdf=46.05170186
p=1E-20

Example 2: Using the Conway-Maxwell-Poisson Distribution

data _null_;
   y=squantile('conmaxpoi',.2,2.3,.4);
   put y=;
run;

SAS writes the following results to the log:

y=12

SQUANTILE Function

Syntax

Required Arguments

distribution

probability

parameter-1, …, parameter-k

Details

Examples

Example 1: Using the LOGISTIC Distribution

Example 2: Using the Conway-Maxwell-Poisson Distribution

See Also