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
>>>>> 
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