On Mon, Dec 14, 2009 at 06:10:16PM +0100, ber...@lycos.com wrote: > > > pnorm(1.35,0,1) > [1] 0.911492 > > pnorm(1.36,0,1) > [1] 0.913085 > > > options(digits=4) > > > pnorm(1.35,0,1) > [1] 0.9115 > > pnorm(1.36,0,1) > [1] 0.913 rounding error?
The technical explanation is as follows. If options(digits=k) is set, then the number of significant digits for printing a single number x is determined as min(k, d), where d is the minimum number of digits, for which the relative error of the printed number is less than 10^-k. If we have x <- 0.913085 y <- 0.913 then the relative error of y as an approximation of x is abs(y - x)/x # [1] 9.3091e-05 Since this is less than 10^-4, the 3 digit precision is chosen for printing x. A safer way of rounding is to use functions round() and signif(). For example, round(x, digits=4) # [1] 0.9131 I do not know the history of the R printing algorithm. It is designed primarily for printing vectors, where the rules are more complicated to achieve a good unified format for all numbers. May be, someone else can say more about it. The above analysis may be obtained by inspecting the R source code. Petr Savicky. ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
