Thanks Bally ....

 
Cycling on rolling basis ...

The random flow as we know it or the distribution does not come in perfect order.
Most of the time the flow comes in disorder or erratic flow.

Look at this simplicity or example.

1)
,,,''',,,''',,,''',,,''',,,''',,,''',,,''',,,''',,,''',,,''',,,

2)
,,'',,'',,'',,'',,'',,'',,'',,'',,'',,'',,'',,'',,'',,'',,'',,''

This above is typical of perfect symmetric order.
Erratic flow looks like this and are the most common one.

3)
,,''''',','',,,'',',,,'',,'''',,,',',','',,',',,,'',,,,,,'',',,,,,',',,''''',','',','',',,,'',,,',',,',,'

This is why i think cycling principles are superior toward any other in the short term.
Cycling on a rolling basis.

 
Do you have a link to the original method ?

 
Yes i have RX but is a crack version of it ...
Yes i like hand testing as it give a better understanding what going on with your method.
Actually i do both ,,, first hand testing then later i run RX ...

Cheers

 
Thanks
I need does real ones and not True RNG or Pesudo RNG ...
Because i am testing RWD ... playing one number.

The Ecart windows strength.

We deal with independent random flow where singles and series come in any combination.
As you can see with the simulation software above so does the Ecart grow and getting weaker in waves.
The nature of the game is chaos with tiny, medium and large waves of imbalance or some times even out.

Lets assume you would play this for real with real money.
Then you should know some rules that effect the strength behind the bias window of events.

Say that you search for 3.0 Ecart windows before you are ready to attack.
Then the minim window is 16 events or trails.

Then you have to set a limit that the 3.0 STD should appear during 16 to 30 events and not more or less.
Maybe you set your limit to 16 to 25 events / trails.

This is because if you have a stretch window with 50 events and a Ecart of 3.0.
Then parts of the events during this window is underrepresented events / trails.
That makes the weaker stretch of the window.

Then the likelihood with equilibrium to have some events / trails already been showed - can effect the future drop point to become weaker or with same weak stretch over length as the window with 50 events.
That makes it harder to catch.

So with other words so does the probability window being small give a more rapid drop point overall.
As none of the underrepresented events / trails had a show during the Ecart window.

This is about the length and how much you stretch the bias and limit with your Ecart window - that in the end effect what kind or regression towards the mean you can expect.

I once reach 3.0 STD flat betting and i know members who play upon same principals and make money each day on regular basis - but not flat betting, but who cares.
I won't mention names.

Study, explore, observe.

Quote from: Turner on November 27, 2013, 02:56:52 PM
Thanks....BTW....the whole post is excellant

Thanks Turner for your kind words.

Alternative March - Development ...

One other famous way is to only attack after +1 when using a march or algorithm.
Lets assume you would play singles contra larger series and your march is to attack after three in a row.
Then if it fails attack after a series of two show and if it fails again attack after a series of two show.

Then you would not attack until one of them show a positive result or +1.
Same with March 1 above if you prefer to be more careful.

Cheers

QuoteSputnik...I never quite get you when you say "you attack"


Attack what? Do what to attack 


I've seen RRRBBB. I am now attacking. By doing what?

You wait until two series chop after each other, then you play that the third will show.

R
R
B
B
B
R
R W

Now if you lose this first bet, then you bet you will win the second bet.

R
R
B
B
B
R
B L
B W

Now lets assume none of the bet wins then the STD start to grow again with out drop point after stop growing stronger.
So now you have to wait for this two betting signals again.
Two series to chop or the hovering state.

R
R
B
B
B

or

B
B
R
B
B

After 3.0 or strong imbalance and this two state start to show as drop point or indication that the bias stop growing stronger - then this two states start to chop or clustering in waves where you end up +1 unit or break even at +0.

If you follow the march above you should get similar results.
+1 +1 +0 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +0 +1 +1 +0 +1 -4 +1 +1 +1 +0 +1 +1 +1 +1 +0 +1 +1 +1 +1 +1 +1 +1
If i remember it correct i once reach 3.0 STD flat betting this way or was it another march, not sure ...

What you will see after 3.0 STD if it stop growing and go into the other direction is the two following states.

R
R
B
B
R
R
R

There will be many events that will become at least three series that chop after each other.
Tiny drop point and larger drop points.

The other common one is the hovering state follow by hovering state or series that chop.

R
R
B
R
R
B
B

Or

R
R
B
R
R
R
B
R
R
R
R

This creates two kinds of Loses and Winnings ...
Direct wins or break even W or LW chops.
When there is no correction you only end up with two loses LL.

I will show that how the regression towards the mean look like.
You can get very long strings of winnings before reaching a loss limit ...

LWWLWLWLWWLWWWWLWLWLWLL LWWLWLWLWWLWLWWLWWLWWLWLL LWLWWLL
All does are series that chop or hovering with out the STD to start growing again.
So if not flat betting, then i would suggest D'alambert as staking plan.

This is the kind or similiear LW-Registry Bayes gets ( if i assume ) and others get with there methods when the use tendency play.
This is the real thing.

Quote@sputnik..i have question, is there any sign to know how big regression is going to be..because sometimes even chance reaches say std 4  and breaks back but it does not even very much...but sometimes even chance go to say lower std 3 and breaks back very nice...thanks

Sometimes it does not have to have a drop point or even out.
You win if it just stop growing stronger and stay at same level without getting stronger or weaker.
This is what i call or name the hovering state and i define it being part of the drop point or correction as it is present change.

I have simulation software where you can observe the values.
You can run 10.000 trails and look how the imbalance behave ( The ECART )

By this observations you can build a working march.
You can see what happens after 3 4 5 6 STD windows.

The software show the values on a rolling basis.
This way you can make statistical relevant observation of hundred thousand simulations.

It check R/B H/L O/E and measuring the ECART.
I attach the simulation software ecart and result file of one simulation.

You run the simulation software and load a spin file.
Then the software will convert the file into Ecart values.

This is also a good simulation software for deeper understanding of waves or Ecart play.
The simulation software indicate at right side when it reach 3.0 STD ...

Quote
B-0.94    E 1.57    H 1.00
B-0.94    E 1.57    H 1.50
B-0.94    E 1.57    L 1.50
B-0.94    O 1.57    H 1.21
B-0.94    E 1.37    L 1.00
R-0.94    O 1.18    H-0.85
R 1.00    O 1.33    H 0.94
R 1.00    O 1.33    H 0.94
B 1.00    O 1.33    H 0.94
B 1.15    E 1.33    H 0.94
R 1.15    E 1.48    L 0.94
B 0.97    E 1.48    H 0.69
B 1.12    O 1.48    L-0.73
B 1.12    O 1.62    L 0.65
B 1.12    O 1.62    H 0.65
B 1.12    E 1.62    L-1.00
R 1.12    E 1.76    L-1.00
R 1.26    E 1.76    L-1.00
B 1.26    E 1.76    L-1.00
B 1.41    O 1.76    L-1.00
B 1.41    E 1.58    H-1.00
B 1.41    E 1.72    L-1.21
R 1.41    O 1.72    H-1.50
B 1.23    O 1.85    H-1.21
R 1.07    O 1.85    L-1.21
B 0.90    E 1.85    H-1.50
B 1.04    E 1.98    L-1.70
B 1.04    O 1.98    L-1.41
R 1.04    O 2.11    H-1.41
B 1.00    E 2.11    L-1.61
R-0.73    E 2.24    L-1.34
B-0.90    O 2.24    L-1.34
R-1.06    O 2.50    H-1.34
B-1.22    O 2.50    L-1.53
R-1.50    E 2.50    H-1.71
B-1.70    E 2.67    H-1.46
B-1.50    O 2.67    H-1.46
R-1.50    E 2.36    H-1.46
B-2.00    O 2.14    L-1.46
R-2.18    O 2.26    H-1.63
B-3.00    E 2.26    H-1.40  */25
R-3.15    O 2.00    L-1.40  */25
R-2.83    O 2.18    H-1.57
B-2.83    O 2.18    H-1.35
R-2.98    E 2.18    H-1.35
B-3.13    E 2.36    L-1.35  */27
R-3.27    E 2.36    H-1.51  */28
B-3.41    E 2.36    L-1.67  */29
R-3.54    O 2.36    L-1.46  */30
B-3.67    E 2.06    L-1.46  */30
B-3.40    E 2.24    L-1.46  */30
R-3.40    O 2.24    L-1.46  */30
R-3.14    E 1.98    H-1.46  */30
R-3.14    O 1.73    L-1.62  */31
R-3.14    E 1.51    H-1.77  */32
B-3.14    E 1.67    H-1.57  */33
R-3.27    O 1.67    L-1.57  */33
B-3.40    E 1.46    L-1.37  */34
B-3.16    O 1.26    H-1.37  */34
B-3.16    E-1.21    L-1.52  */35
R-3.16    O-1.50    H-1.67  */36
B-3.29    E-1.70    H-1.48  */37
B-3.05    E-1.41    H-1.48  */37
R-3.05    O-1.41    H-1.48  */37
R-2.83    E-1.61    H-1.48
R-2.83    E-1.50    H-1.48
B-2.83    E-1.50    H-1.48
R-2.96    E-1.50    L-1.48
R-2.74    E-1.50    H-1.62
R-2.74    O-1.50    H-1.44
R-2.74    O-1.50    L-1.44
R-2.74    O-1.50    L-1.26
R-2.74    O-1.50    L-1.26
R-2.74    O-1.50    H-1.26
B-2.74    E-1.50    H-1.09
B-2.54    O-1.70    L-1.09
B-2.54    E-1.89    H-1.23
R-2.54    E-1.61    L-1.37
B-2.67    O-1.61    L-1.21
B-2.47    O-1.34    L-1.21
B-2.47    O-1.34    L-1.21
R-2.47    O-1.34    L-1.21
B-2.60    O-1.34    L-1.21
R-2.72    O-1.34    H-1.21
B-2.85    E-1.34    H-1.04
B-2.65    E-1.09    L-1.04
B-2.65    E-1.09    H-1.18
B-2.65    O-1.09    H-1.02
B-2.65    E-1.28    H-1.02
B-2.65    O-1.46    L-1.02
R-2.65    O-1.22    H-1.15
R-2.47    E-1.22    L-1.29
R-2.47    O-1.40    L-1.13
R-2.47    O-1.18    H-1.13
B-2.47    E-1.18    H-0.87
B-2.29    E 1.00    L-0.87

Quote from: Bayes on November 26, 2013, 04:39:33 PM
Best if you stick to the default settings, this is old software and it has a few bugs!

Yes that is a old simulation software 0.7 Ecart - but it works like clock-work - had no issue with it ...
Can even save results into separate text file.

Here is a later simulation software 1.1 Ecart - It has both Singles contra series and Series contra singles (pick your own settings).
I also test this simulation software and it works great.
See attach file.

You run the software and load your spin file.
I prefer running 10.000 trails from random org.

Click on the next button and the software will find you a window of 3.0 STD.
After that you can click on the spin button and see how the drop point behave.

Here is the simulation software, see attach file.
Thanks to Bayes.

You run the software and load your spin file.
I prefer running 10.000 trails from random org.

Click on the next button and the software will find you a window of 3.0 STD.
After that you can click on the spin button and see how the drop point behave or testing the march above.

Cheers

singles contra series - March 1

This is flat betting with a total of four attempts.

1) Rule number one is to wait for two series to chop, the formation of two series look like this RRRBBB and after that formation appears you attack twice and gain +1 unit.

If you don´t get a straight hit with three series in a row like this RRRBBRR you will have the following formation RRRBBR and aim for it to hovering with your secound bet RRRBBRBBBB if at zero you just follow the betting behavior, the march, until +1 or -2 being your first attack.

2) If you don't get two series to chop as I mention above you make your first attack when a state of hovering appears and it looks like this RRRBRRR and play that next formation will be followed with a serie like this RRRBRRRBB if not you will have the following formation RRRBRRRBR and would play it will continue to hovering and ride it out until +1 or -2 being your first attack.

3) If first attack fail you would repeat the betting signals above for one more attack with the difference that you don't aim to win +1 and now aim to break even because that would give you one less formation of correction to appers more (variance)  regulary then an longer correction to end up with +1 and this is a way to make the play more stabel with good results.

Result:

+1 +1 +0 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +0 +1 +1 +0 +1 -4 +1 +1 +1 +0 +1 +1 +1 +1 +0 +1 +1 +1 +1 +1 +1 +1

31 won
4 loss
27 total gain

In the old days i did many hundred thousands simulations and will end this topic about algorithms or march with money management.
Here i will go deep into how you can measuring the random flow or distribution.
Its based upon taking advantage of the law of series in all existing aspects.

This is the values and existing playing models based upon pure math and probability.
This is how you find you windows of bias or overrepresented events.

Series contra Singles.
Series has the value of 1 and Singles has the value of 1.
There is as many singles as existing series no matter length.

Singles contra series.
Singles has the value of 1 and Series has the value of 1.
there's is as many singles as existing series no matter length.

Singles contra larger series.
Singles has the value of 1
Series of two has the value of 0
Series of three has the value of 1
Series of four has the value of 2
Series of five has the value of 3
Series of six has the value of 4
And so it continues

Series of two contra larger series.
Singles has the value of 0 (you just skip them as none existing)
Series of two has the value of 1
Series of three has the value of 0
Series of four has the value of 1
Series of five has the value of 2
Series of six has the value of 3
Series of seven has the value of 4
And so it continues ...

Series of three contra larger series
Singles has the value of 0 (you just skip them as none existing)
Series of two has the value of 0 (you just skip them as none existing)
Series of three has the value of 1
Series of four has the value of 0
Series of five has the value of 1
Series of six has the value of 2
Series of seven has the value of 3
Series of eight has the value of 4
And so it continues.

Now to the underlying dimension.
You can divide singles only into singles of singles and series of singles.
And you can divide singles series versus series of series.
With the same math and probability measuring the random flow.

Here is an simple chart that I did a long time ago with some values that you can use as reference.



The french word for STD is Ecart

First you have to get the Absolute Ecart when you calculate.
So lets assume you have an sequence with 14 series alternating with two singles present.

Then you take 14 - 2 = 12

Now we want to get the statistical ecart so we continue with...

14 + 2 = 16

Now we take the sqr of 16 = 4

And finally we divide the absolute ecart whit the sqr

12 sqr 4 = 3,00

The Statistical Ecart 3,00