I don't expect floating answers to be exact. However, most of my
use of computers begins with inexact numbers, so getting the floating
routines as good as possible seems like a worthy effort to me.
Unfortunately, I stopped my reseach when J's answers went very
wrong at H 9. Nars also supports
H=: % @: : @: (+/~) @: i.
det=: -/ .*
0j_6 : det@H0 i.3 5x
1.00e0 1.00e0 8.33e_2 4.629630e_4 1.653439e_7
3.749295e_12 5.367300e_18 4.835803e_25 2.737050e_33 9.720234e_43
2.164179e_53 3.019095e_65 2.637781e_78 1.442897e_92 4.940315e_108
The preceding computes the
I only raised it because it is so bad compared to everyone else I've
looked at, including mine. An original copy of my result and my
implementation code are available on request. Please note, I cannot
speak for others but I didn't take a Hilbert matrix into account in
writing mine.
Paul
Don't you become even a bit suspicious when the answers don't agree?
Consider the number on the lower right hand corner:
PLJsAPL: 2815820646.25489
Dyalog: 2815825985
NARS2000:2815820182
J Rational: 2815827300 (true answer).
If you are proud of implementation X, I can bring it down
