Hey Alex, You may want to take a look at NuVoc, the jwiki section that I think that Ian Clark organized just for the reason that you are describing. :)
http://www.jsoftware.com/jwiki/NuVoc Cheers, bob On Apr 23, 2014, at 10:52 AM, alexgian <alexg...@blueyonder.co.uk> wrote: >> The information and more are in the vocabulary page for %. > > Well, yes, but so tersely and compactly expressed that you have to know the > long answer before you understand it! I did look at the Vocab page, but > didn't "get it", that's why I posted. > > It needed Roger's somewhat more expanded explanation for those of us that > are somewhat slower on the uptake. That's why I said the Vocab could use a > touch up. It is NOT user friendly, more of an ultra-coded reference. Of > course, you might not see it this way, but I'd bet most newcomers would. > > And it's not as if there is a longer explanation somewhere else, is there? > Well, other than this thread, I mean... :) > > > > On 23 April 2014 18:17, Roger Hui <rogerhui.can...@gmail.com> wrote: > >> The information and more are in the vocabulary page for %. >> http://www.jsoftware.com/help/dictionary/d131.htm . >> >> >> On Wed, Apr 23, 2014 at 10:02 AM, alexgian <alexg...@blueyonder.co.uk >>> wrote: >> >>> Great info, thanks Roger. >>> If it was up to me, I'd DEFINITELY include that in the Vocabulary, is it >>> even documented anywhere else? >>> >>> >>> On 23 April 2014 17:33, Roger Hui <rogerhui.can...@gmail.com> wrote: >>> >>>> %. x for a vector x is the same as ($x)$%.,.x, and the key expression >> is >>>> %.,.x, the "matrix inverse" of a 1-column matrix. b=.y%.x on a tall >>> matrix >>>> x is solving a least-squares problem, the coefficients b that minimizes >>> the >>>> sum of squares of y - x +/ .* b . >>>> >>>> In addition, for a non-zero vector x, (%.x) +/ .* x is 1, a special >> case >>> of >>>> that (%.x)+/ .* x is an identity matrix, whence one can deduce that for >>>> vector x, %.x is x%+/x^2. >>>> >>>> ] x=: 7 ?.@$ 100 >>>> 94 56 8 6 85 48 66 >>>> %. x >>>> 0.00362137 0.00215741 0.000308202 0.000231152 0.00327465 0.00184921 >>>> 0.00254267 >>>> (%.x) +/ .* x >>>> 1 >>>> x % +/x^2 >>>> 0.00362137 0.00215741 0.000308202 0.000231152 0.00327465 0.00184921 >>>> 0.00254267 >>>> >>>> M=: 7 3 ?.@$ 100 >>>> (%.M) +/ .* M >>>> 1 5.55112e_17 _2.77556e_17 >>>> _1.21431e_16 1 1.11022e_16 >>>> _4.85723e_17 1.94289e_16 1 >>>> >>>> >>>> >>>> On Wed, Apr 23, 2014 at 9:13 AM, alexgian <alexg...@blueyonder.co.uk> >>>> wrote: >>>> >>>>> Just wondering: >>>>> %. 2 3 4 >>>>> 0.0689655 0.103448 0.137931 >>>>> >>>>> Which is fair enough enough at one level, I suppose, since the dot >>>> product >>>>> of the two arrays IS 1, but what system/equation is being solved >> here? >>>>> Obviously, there are infinite solutions. Why that one? >>>>> IOW, which "matrix" is being inverted here? >>>>> >>>>> Thanks >>>>> >> ---------------------------------------------------------------------- >>>>> For information about J forums see >> http://www.jsoftware.com/forums.htm >>>>> >>>> ---------------------------------------------------------------------- >>>> For information about J forums see http://www.jsoftware.com/forums.htm >>>> >>> ---------------------------------------------------------------------- >>> For information about J forums see http://www.jsoftware.com/forums.htm >>> >> ---------------------------------------------------------------------- >> For information about J forums see http://www.jsoftware.com/forums.htm >> > ---------------------------------------------------------------------- > For information about J forums see http://www.jsoftware.com/forums.htm ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm