(This article was first published on

**Heuristic Andrew**, and kindly contributed to R-bloggers)Because the Fibonacci sequence is simply defined by recursion, it makes for an elegant programming exercise. Here is one way to do it in SAS, and another way to do it in R. I’ve also included unit testing code to check that it works.

Fibonacci sequence in SAS using a recursive macro:

%macro fib(n);

%if &n = 1 %then 1; * first seed value;

%else %if &n = 2 %then 1; * second seed value;

%else %eval(%fib(%eval(&n-1))+%fib(%eval(&n-2))); * use recursion;

%mend;

* show values 1-5;

%put %fib(1);

%put %fib(2);

%put %fib(3);

%put %fib(4);

%put %fib(5);

* check values 1-10;

%macro check_fib;

%if %fib(1) ne 1 %then %abort;

%if %fib(2) ne 1 %then %abort;

%if %fib(3) ne 2 %then %abort;

%if %fib(4) ne 3 %then %abort;

%if %fib(5) ne 5 %then %abort;

%if %fib(6) ne 8 %then %abort;

%if %fib(7) ne 13 %then %abort;

%if %fib(8) ne 21 %then %abort;

%if %fib(9) ne 34 %then %abort;

%if %fib(10) ne 55 %then %abort;

%put NOTE: OK!;

%mend;

%check_fib;

Fibonacci sequence in R using a recursive function that supports either single integers or a vector of integers:

fib <- function(n)

{

if (length(n) > 1) return(sapply(n, fib)) # accept a numeric vector

if (n == 1) return(1) # first seed value

if (n == 2) return(1) # second seed value

return(fib(n-1)+fib(n-2)) # use recursion

}

# print first five Fibonacci numbers

fib(1)

fib(2)

fib(3)

fib(4)

fib(5)

# verify the Fibonacci sequence 1 through 10

(actual <- fib(1:10))

(expected <- c(1,1,2,3,5,8,13,21,34,55))

all.equal(actual,expected)

For alternative implements, see SAS and R: Example 7.1: Create a Fibonacci sequence. In SAS, Nick Horton calculates the Fibonacci sequence using a DATA STEP, and in R he uses a FOR loop.

**This post first appeared on Heuristic Andrew.**

To

**leave a comment**for the author, please follow the link and comment on their blog:**Heuristic Andrew**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...