I don’t see how rounding errors could accumulate, if you keep the sum and not 
the average.

The rounding errors should be neutral, because each element is added once and 
subtracted once. 

If + and – is symmetrical in this respect, rounding inaccuracies should balance 
out.

 

Cheers,

                Christian

 

Von: Pharo-users <pharo-users-boun...@lists.pharo.org> Im Auftrag von Richard 
O'Keefe
Gesendet: Donnerstag, 9. April 2020 05:26
An: Any question about pharo is welcome <pharo-users@lists.pharo.org>
Betreff: Re: [Pharo-users] Moving/rolling average implementations ?

 

I note that "self species ofSize: n" is not generally a good idea.

Consider ByteArray, ShortIntegerArray, WordArray.

Computing rolling means of these is perfectly sensible,

but the results will not fit into an array of the same species.

I'd stick with Array.

 

The suggestion about subtracting an old element and adding a new

one is great for integers, but for floating-point numbers risks

accumulating errors.

 

The

 

On Wed, 8 Apr 2020 at 20:07, Cédrick Béler <cdric...@gmail.com 
<mailto:cdric...@gmail.com> > wrote:

Hi,

 

I wanted to do a moving/rolling average on raw data [1]. 

I haven’t find code for that (maybe this is done in polymath though).

 

So I ended writing that (I thing this is SMA):

 

SequenceableCollection>>movingAverage: anOrder     
"Answer the moving or rolling average for anOrder window"

 

    | retval size x y |

        anOrder <= 0 ifTrue: [ Error signal: 'the order must be positive'].

    size := self  size - anOrder.

    size negative  ifTrue: [ Error signal: 'the collection size is too small'].

    retval := self species ofSize: size + 1.

 

    x := 1.

y := anOrder.

    [y <=  self  size ] whileTrue: [           

 retval at: x put: (self copyFrom: x to: y) average           

 x := x + 1. y := y + 1

 ].

    ^retval

 

Not perfect but seems to works quite well (that’s probably better to remove 
copyFrom: and use some kind of buffer instead).

 

Any interest in that ? If any existing code too, I’ll be interested especially 
for other implementation (weighted, exponential) ?

 



 

(#(118 113 105 105 103 99 98 101 100 107) movingAverage: 3) collect: [:v | v 
asScaledDecimal: 1 ] .

 

 "an Array(112.0s1 107.7s1 104.3s1 102.3s1 100.0s1 99.3s1 99.7s1 102.7s1)"

 

Cheers,

Cédrick 

 

 

 

[1] 
https://www.meilleursbrokers.com/techniques-de-trading/moyennes-mobiles.html 
(in French but is understandable)

 

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