Gordon Smyth <[EMAIL PROTECTED]> writes: > This is just a suggestion/wish that it would be nice for the > F-distribution functions to recognize limiting cases for infinite > degrees of freedom, as the t-distribution functions already do. > > The t-distribution functions recognize that df=Inf is equivalent to > the standard normal distribution: > > > pt(1,df=Inf) > [1] 0.8413447 > > pnorm(1) > [1] 0.8413447 > > On the other hand, pf() will accept Inf for df1, but returns the wrong result: > > > pf(1,df1=Inf,df2=1) > [1] 1 > > whereas the correct limiting value is > > > pchisq(1,df=1,lower.tail=FALSE) > [1] 0.3173105 > > pf() returns NaN when df2=Inf: > > > pf(1,df1=1,df2=Inf) > [1] NaN > Warning message: > NaNs produced in: pf(q, df1, df2, lower.tail, log.p) > > although the correct value is available as > > > pchisq(1,df=1) > [1] 0.6826895 > > > Gordon > > > version > _ > platform i386-pc-mingw32 > arch i386 > os mingw32 > system i386, mingw32 > status > major 2 > minor 1.0 > year 2005 > month 04 > day 18 > language R
This is actually a regression. It worked as you suggest in 2.0.1, at least on Linux. Also, somewhat disturbing, > pf(1,df1=1,df2=Inf) [1] NaN Warning message: NaNs produced in: pf(q, df1, df2, lower.tail, log.p) > pf(1,df1=1,df2=99999999) [1] 0.6826895 > pf(1,df1=1,df2=999999999999) [1] 0.6826841 > pf(1,df1=1,df2=99999999999999999999) [1] 0 (notice that the middle case has actually begun to diverge from the limiting value) -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ R-devel@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-devel