The MCMC Procedure
 Some Useful SAS Functions
Table 52.32 Some Useful SAS Functions

SAS Function

Definition

abs(x)

airy(x)

returns the value of the AIRY function.

beta(x1, x2)

call logistic(x)

call softmax(x1,...,xn)

each element is replaced by

call stdize(x1,...,xn)

standardize values

cdf

cumulative distribution function

cdf(’normal’, x, 0, 1)

standard normal cumulative distribution function

comb(x1, x2)

constant(’.’)

calculate commonly used constants

cos(x)

cosine(x)

css(x1, ..., xn)

cv(x1, ..., xn)

std(x) / mean(x) * 100

dairy(x)

derivative of the AIRY function

dimN(m)

returns the numbers of elements in the Nth dim of array

(x1 eq x2)

returns 1 if x1 = x2; 0 otherwise

x1**x2

geomean(x1, ..., xn)

difN(x)

returns differences between the argument and its Nth lag

digamma(x1)

erf(x)

erfc(x)

1 - erf(x)

fact(x)

floor(x)

greatest integer

gamma(x)

harmean(x1, ..., xn)

ibessel(nu, x, kode)

modified Bessel function of order nu evaluated at

jbessel(nu, x)

Bessel function of order nu evaluated at

lagN(x)

returns values from a queue

largest(k, x1, ..., xn)

the largest element

lgamma(x)

lgamma(x+1)

log(x), logN(x)

logbeta(x1, x2)

lgamma() + lgamma() - lgamma()

logcdf

log of a left cumulative distribution function

logpdf

log of a probability density (mass) function

logsdf

log of a survival function

max(x1, x2)

returns if ; otherwise

mean(of x1-xn)

median(of x1-xn)

returns the median of nonmissing values

min(x1, x2)

returns if ; otherwise

missing(x)

returns 1 if is missing; 0 otherwise

mod(x1, x2)

returns the remainder from

n(x1, ..., xn)

returns number of nonmissing values

nmiss(of y1-yn)

number of missing values

quantile

computes the quantile from a specific distribution

pdf

probability density (mass) functions

perm(n, r)

put

returns a value that uses a specified format

round(x)

rounds x

rms(of x1-xn)

sdf

survival function

sign(x)

returns if ; if ; if

sin(x)

sine()

smallest(, x1, ..., en )

the smallest component of

sortn(of x1-xn)

sorts the values of the variables

sqrt(x)

std(x1, ..., xn)

standard deviation of (n-1 in denominator)

sum(of x:)

trigamma(x)

derivative of the DIGAMMA() function

uss(of x1-xn)

uncorrected sum of squares

Here are examples of some commonly used transformations:

• logit

```mu = beta0 + beta1 * z1;
call logistic(mu);
```
• log

```w = beta0 + beta1 * z1;
mu = exp(w);
```
• probit

```w = beta0 + beta1 * z1;
mu = cdf(`normal', w, 0, 1);
```
• cloglog

```w = beta0 + beta1 * z1;
mu = 1 - exp(-exp(w));
```
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