**[FN] Random-number functions**

__Function__

**rnormal()**
Description: standard normal (Gaussian) random variates, that is,
variates from a normal distribution with a mean of 0 and
a standard deviation of 1
Range: **c(mindouble)** to **c(maxdouble)**

**rnormal(***m***)**
Description: normal(*m*,1) (Gaussian) random variates, where *m* is the
mean and the standard deviation is 1
Domain *m*: **c(mindouble)** to **c(maxdouble)**
Range: **c(mindouble)** to **c(maxdouble)**

**rnormal(***m***,*** s***)**
Description: normal(*m*,*s*) (Gaussian) random variates, where *m* is the
mean and *s* is the standard deviation

The methods for generating normal (Gaussian) random
variates are taken from Knuth (1998, 122-128);
Marsaglia, MacLaren, and Bray (1964); and Walker (1977).
Domain *m*: **c(mindouble)** to **c(maxdouble)**
Domain *s*: 0 to **c(maxdouble)**
Range: **c(mindouble)** to **c(maxdouble)**

__References__

Knuth, D. 1998. *The Art of Computer Programming, Volume 2:*
*Seminumerical Algorithms*. 3rd ed. Reading, MA: Addison Wesley.

Marsaglia, G., M. D. MacLaren, and T. A. Bray. 1964. A fast procedure
for generating normal random variables. *Communications of the ACM* 7:
4-10.

Walker, A. J. 1977. An efficient method for generating discrete random
variables with general distributions. *ACM Transactions on*
*Mathematical Software* 3: 253-256.