Computes cumulative distribution functions
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CDF ('dist',quantile,parm-1, . . . ,parm-k)
|
-
'dist'
-
is a character string that identifies the
distribution. Valid distributions are
Note:
Except for T and F, any distribution can be minimally identified by its first four
characters. ![[cautend]](../common/images/cautend.gif)
-
quantile
-
is a numeric random variable.
-
parm-1, . . . ,parm-k
-
are shape, location, or scale parameters appropriate for the specific distribution.
See the description for each distribution in "Details" for complete
information about these parameters.
where
-
x
-
is a numeric random variable.
-
p
-
is a numeric probability of success.
The CDF function for the Bernoulli distribution returns
the probability that an observation from a Bernoulli distribution, with probability
of success equal to p, is less than or equal to x.
The equation follows:.
Note:
There are
no location or scale parameters for this distribution.
where
-
x
-
is a numeric random variable.
-
a
-
is a numeric shape parameter.
-
b
-
is a numeric shape parameter, with b > 0.
-
l
-
is an optional numeric left location parameter.
-
r
-
is an optional right location parameter.
The CDF function for the beta
distribution returns the
probability that an observation from a beta distribution, with shape parameters a and b, is less than or equal to x. The
following equation describes the CDF function of the Beta distribution,
where
and
Note:
The default values for l and r are 0 and 1, respectively.
where
-
m
-
is an integer random variable that counts
the number of successes.
-
p
-
is a numeric parameter that is the probability
of success.
-
n
-
is an integer parameter that counts the
number of independent Bernoulli trials.
The CDF function for the binomial distribution
returns
the probability that an observation from a binomial distribution, with parameters p and n, is less than or equal to m. The
equation follows:
Note:
There are
no location or scale parameters for the binomial distribution.
CDF('CAUCHY',x<, , >)
|
where
-
x
-
is a numeric random variable.
-
![[thetas]](../common/images/thetal.gif)
-
is an optional numeric location parameter.
-
![[lambda]](../common/images/lambdal.gif)
-
is an optional numeric scale parameter.
The CDF function for the Cauchy distribution returns
the probability that an observation from a Cauchy distribution, with location
parameter
and scale parameter
, is less than or equal to x. The equation follows:
Note:
The default values for
and
are
0 and 1, respectively.
|
CDF('CHISQUARED',x,df
<,nc>)
|
where
-
x
-
is a numeric random variable.
-
df
-
is a numeric degrees of freedom parameter.
-
nc
-
is an optional numeric noncentrality parameter.
The CDF function for the chi-squared
distribution returns
the probability that an observation from a chi-squared distribution, with df degrees of freedom and noncentrality parameter nc,
is less than or equal to x. This function accepts noninteger
degrees of freedom. If nc is omitted or equal to zero, the value
returned is from the central chi-squared distribution. The following equation
describes the CDF function of the chi-squared distribution,
where Pc(.,.) denotes the
probability from the central chi-squared distribution:
and
where Pg(y,b) is the probability from the Gamma distribution given
by
CDF('EXPONENTIAL',x
<, >)
|
where
-
x
-
is a numeric random variable.
-
![[lambda]](../common/images/lambdal.gif)
-
is an optional scale parameter.
The CDF function for the exponential distribution returns
the probability that an observation from an exponential distribution, with
scale parameter
, is less than or equal to x. The equation
follows:
Note:
The default
value for
is 1.
where
-
x
-
is a numeric random variable.
-
ndf
-
is a numeric numerator degrees of freedom
parameter.
-
ddf
-
is a numeric denominator degrees of freedom
parameter.
-
nc
-
is a numeric noncentrality parameter.
The CDF function for the F
distribution
returns the probability that an observation from an F distribution,
with ndf numerator degrees of freedom, ddf denominator
degrees of freedom, and noncentrality parameter nc, is less than
or equal to x. This function accepts noninteger degrees of freedom
for ndf and ddf. If nc is omitted or
equal to zero, the value returned is from a central F distribution.
The following equation describes the CDF function of the F distribution
where Pf(f,u1,u2) is
the probability from the central F distribution with
and PB(x,a,b) is the probability from the standard Beta distribution.
Note:
There are no
location or scale parameters for the F distribution.
CDF('GAMMA',x,a<, >)
|
where
-
x
-
is a numeric random variable.
-
a
-
is a numeric shape parameter.
-
![[lambda]](../common/images/lambdal.gif)
-
is an optional numeric scale parameter.
The CDF function for the Gamma distribution returns
the probability that an observation from a Gamma distribution, with shape
parameter a and scale parameter
, is less than or equal
to x. The equation follows:
Note:
The default value for
is1.
where
-
m
-
is a numeric random variable that denotes
the number of failures.
-
p
-
is a numeric probability.
The CDF function for the geometric distribution returns
the probability that an obervation from a geometric distribution, with parameter p, is less than or equal to m. The equation
follows:
Note:
There are
no location or scale parameters for this distribution.
where
-
x
-
is an integer random variable.
-
m
-
is an integer population size parameter,
with m
1.
-
k
-
is an integer number of items in the category
of interest.
-
n
-
is an integer sample size parameter.
-
r
-
is an optional numeric odds ratio parameter.
The CDF function for the hypergeometric
distribution
returns the probability that an observation from an extended hypergeometric
distribution, with population size m, number of items k, sample size n, and odds ratio r, is less
than or equal to x. If r is omitted or equal to
1, the value returned is from the usual hypergeometric distribution. The
equation follows:
CDF('LAPLACE',x<, , >)
|
where
-
x
-
is a numeric random variable.
-
![[thetas]](../common/images/thetal.gif)
-
is an optional numeric location parameter.
-
![[lambda]](../common/images/lambdal.gif)
-
is an optional numeric scale parameter.
The CDF function for the Laplace distribution returns
the probability that an observation from the Laplace distribution, with location
parameter
and scale parameter
, is less than or equal to x. The equation follows:
Note:
The default
values for
and
are
0 and 1, respectively.
CDF('LOGISTIC',x<, , >)
|
where
-
x
-
is a numeric random variable.
-
-
is an optional numeric location parameter
-
![[lambda]](../common/images/lambdal.gif)
-
is an optional numeric scale parameter.
The CDF function for the logistic distribution returns
the probability that an observation from a logistic distribution, with a location
parameter
and a scale parameter
, is less than or equal
to x. The equation follows:
Note:
The default values for
and
are
0 and 1, respectively.
CDF('LOGNORMAL',x<, , >)
|
where
-
x
-
is a numeric random variable.
-
-
is an optional numeric location parameter
-
![[lambda]](../common/images/lambdal.gif)
-
is an optional numeric scale parameter.
The CDF function for the lognormal distribution returns
the probability that an observation from a lognormal distribution, with location
parameter
and scale parameter
, is less than or equal to x. The equation follows:
Note:
The default values for
and
are
0 and 1, respectively.
where
-
m
-
is a positive integer random variable that
counts the number of failures.
-
p
-
is a numeric probability of success parameter.
-
n
-
is an integer parameter that counts the
number of successes.
The CDF function for the negative binomial
distribution
returns the probability that an observation from a negative binomial distribution,
with probability of success p and number of successes n, is less than or equal to m. The equation
follows:
Note:
There are
no location or scale parameters for the negative binomial distribution.
CDF('NORMAL',x<, , >)
|
where
-
x
-
is a numeric random variable.
-
-
is an optional numeric location parameter.
-
![[lambda]](../common/images/lambdal.gif)
-
is an optional numeric scale parameter.
The CDF function for the normal distribution returns
the probability that an observation from the normal distribution, with location
parameter
and scale parameter
, is less than or equal to x. The equation follows:
Note:
The default values for
and
are 0 and 1, respectively.
where
-
x
-
is a numeric random variable.
-
a
-
is a numeric shape parameter.
-
k
-
is an optional numeric scale parameter.
The CDF function for the Pareto distribution
returns
the probability that an observation from a Pareto distribution, with shape
parameter a and scale parameter k, is less than
or equal to x. The equation follows:
Note:
The default
value for k is 1.
where
-
n
-
is an integer random variable.
-
m
-
is a numeric mean parameter.
The CDF function for the Poisson distribution
returns
the probability that an observation from a Poisson distribution, with mean
m, is less than or equal to n. The equation follows:
Note:
There are no location or scale parameters
for the Poisson distribution.
where
-
t
-
is a numeric random variable.
-
df
-
is a numeric degrees of freedom parameter
-
nc
-
is an optional numeric noncentrality parameter.
The CDF function for the T distribution
returns the probability that an observation from a T distribution,
with degrees of freedom df and noncentrality parameter nc, is less than or equal to x. This function accepts
noninteger degrees of freedom. If nc is omitted or equal to zero,
the value returned is from the central T distribution. The equation
follows:
Note:
There are
no location or scale parameters for the T distribution.
where
-
x
-
is a numeric random variable.
-
l
-
is an optional numeric left location parameter.
-
r
-
is an optional numeric right location parameter.
The CDF function for the uniform
distribution returns
the probability that an observation from a uniform distribution, with left
location parameter l and right location parameter r,
is less than or equal to x. The equation follows:
Note:
The default
values for l and r are 0 and 1, respectively.
where
-
x
-
is a numeric random variable.
-
d
-
is a numeric shape parameter.
The CDF function for the Wald distribution returns
the
probability that an observation from a Wald distribution, with shape parameter d, is less than or equal to x. The equation
follows:
where
(.) denotes the probability from
the standard
normal distribution.
Note:
There are no location or scale parameters for the Wald distribution.
CDF('WEIBULL',x,a<, >)
|
where
-
x
-
is a numeric random variable.
-
a
-
is a numeric shape parameter.
-
-
is an optional numeric scale parameter.
The CDF function for the Weibull distribution returns
the probability that an observation from a Weibull distribution, with shape
parameter a and scale parameter
is less than or equal
to x. The equation follows:
Note:
The default
value for
is 1.
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SAS Statements |
Results |
y=cdf('BERN',0,.25);
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0.75
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y=cdf('BERN',1,.25);
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y=cdf('BETA',0.2,3,4);
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0.09888
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y=cdf('BINOM',4,.5,10);
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0.37695
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y=cdf('CAUCHY',2);
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0.85242
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y=cdf('CHISQ',11.264,11);
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0.57858
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y=cdf('EXPO',1);
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0.63212
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y=cdf('F',3.32,2,3);
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0.82639
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y=cdf('GAMMA',1,3);
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0.080301
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y=cdf('HYPER',2,200,50,10);
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0.52367
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y=cdf('LAPLACE',1);
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0.81606
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y=cdf('LOGISTIC',1);
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0.73106
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y=cdf('LOGNORMAL',1);
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0.5
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y=cdf('NEGB',1,.5,2);
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0.5
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y=cdf('NORMAL',1.96);
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0.97500
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y=cdf('PARETO',1,1);
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0
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y=cdf('POISSON',2,1);
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0.91970
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y=cdf('T',.9,5);
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0.79531
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y=cdf('UNIFORM',0.25);
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0.25
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y=cdf('WALD',1,2);
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0.62770
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y=cdf('WEIBULL',1,2);
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0.63212
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Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.