# Thread: Davidski's Global 25 nMonte results

1. Hi Łukasz, you would do me NMonte calculations

,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC1 2,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC2 2,PC23,PC24,PC25
Lugius,0.0116,0.0128,0.018,0.0181,0.0119,0.0101,0. 0023,0.0057,-0.0005,-0.0124,-0.0043,-0.0041,0.0076,0.015,-0.0079,-0.0019,0.00

2. Originally Posted by lukaszM
(...)
Basque French is lower because you used nMonte3 or rather because you used scaled averages?

I was using non-scaled averages before. Later today I will do some runs with scaled averages.

3. David just sent me this morning the G25 of my parents, and will kindly do mine, but before posting anything I would like to know which "nMonte" is going to become the "official", or "canonical" tool on this thread. nMonte2, or 3? scaled, or not scaled?

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5. Originally Posted by anglesqueville
David just sent me this morning the G25 of my parents, and will kindly do mine, but before posting anything I would like to know which "nMonte" is going to become the "official", or "canonical" tool on this thread. nMonte2, or 3? scaled, or not scaled?
My understanding is that nMonte2 is better for people with mixed ancestry, while 3 might be slightly better for people with ancestry from one region (because it prefers populations which appear in "closest single item distances" also in "mixed mode").*

And scaled averages are probably universally better than not scaled.

*If someone is for example 50% Russian + 50% British, he will get East German 1st in single items. But when it comes to mixed mode, nMonte2 will show a mix of East Euro + NW Euro, while nMonte3 will show a mix of various Central Euro populations.

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7. Ancients nMonte3:

Slav_Bohemia
4.920053

Alberstedt_LN
6.216791

Hungary_BA
6.709232

Code:
```[1] "distance%=2.2071"

Slav_Bohemia,63.4
Hungary_BA,8.8
Baltic_BA,2.8
Hungary_IA,2
Armenia_ChL,1.8
Anatolia_BA,1.6
Vinca_MN,1.4
Boncuklu_N,1.2
Armenia_EBA,1
Armenia_MLBA,1
Barcin_N,1
Levant_BA,1
Anatolia_ChL,0.8
Iran_LN,0.8
Mentese_N,0.8
Tisza_LN,0.8
ALPc_MN,0.6
Greece_N,0.6
Greece_Peloponnese_N,0.6
Iran_ChL,0.6
Iran_IA,0.6
LBK_EN,0.6
Levant_N,0.6
Tepecik_Ciftlik_N,0.6
Tiszapolgar_ECA,0.6
Balaton_Lasinja_CA,0.4
Iran_N,0.4
Koros_EN,0.4
LBKT_MN,0.4
Minoan_Lasithi,0.4
Mycenaean,0.4
Protoboleraz_LCA,0.4
CHG,0.2
England_Roman_outlier,0.2
Natufian,0.2
Scythian_AldyBel,0.2
Starcevo_EN,0.2
TDLN,0.2```
Ancients nMonte2:

Code:
```[1] "distance%=1.2184 / distance=0.012184"

Baltic_BA                 37.85
Anatolia_BA               14.55
LBKT_MN                    9.65
Slav_Bohemia               6.00
Mentese_N                  5.90
Vinca_MN                   5.90
Srubnaya_outlier           4.85
Poltavka                   4.60
Koros_EN                   3.45
Armenia_EBA                2.65
Iran_IA                    2.00
Scythian_AldyBel           1.60
Mycenaean                  1.00```
Randwulf's model(nMonte3):

Lithuanian
9.535399

Sardinian
14.113083

Georgian_Imer
16.610687

Code:
```[1] "distance%=2.5771"

Lithuanian,55.4
Sardinian,22.8
Georgian_Imer,10.8
BedouinB,2.4
Mari,2.4
Yemenite_Jew,2.4
Saudi,2
Makrani,1.6
Ket,0.2```
nMonte2:

Code:
```[1] "distance%=2.3513 / distance=0.023513"

Lithuanian    53.4
Sardinian     23.0
Georgian_Imer 17.4
Saudi          4.2
Ket            2.0```

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9. nMonte1 nMonte2 nMonte3.....scaled or not scaled
are all experimental. How to know what is the best, what we prefer to see ?
If we accept the idea that the qpAdm program is today the most accurate, we must compare our results with Them

In my case my results posted in a previous post are very similar.

Below, results for Tuscans
a mix of Etruscan, coming from Anatolia and Celto-Italic IE

[1] "distance%=1.4283"

Italian_Tuscan

Anatolia_ChL,43.2
England_Roman,41.6
Remedello_BA,15.2

[1] "distance%=1.4909"

Anatolia_ChL,44
Bell_Beaker_Germany,41
Remedello_BA,15

Edit : Data not scaled (idem for my previous post)

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11. ...........

12. Originally Posted by Tomenable

*If someone is for example 50% Russian + 50% British, he will get East German 1st in single items. But when it comes to mixed mode, nMonte2 will show a mix of East Euro + NW Euro, while nMonte3 will show a mix of various Central Euro populations.
But if somebody is Eastern German nMonte2 still show him as 50% British + 50% Russian. Because it always seek for distant combinations similar to Dodecad oracle in mixed mode on Gedmatch.

My understanding is that nMonte2 is better for people with mixed ancestry, while 3 might be slightly better for people with ancestry from one region (because it prefers populations which appear in "closest single item distances" also in "mixed mode").*

At least in k36 it isn't true regarding Euro mixes. Only with continental mixes nMonte2 could be better sometimes (because of what I said above). I made hundred or more runs for various users in last weeks so this is from my experience.

13. Originally Posted by slowian88
Hi Łukasz, you would do me NMonte calculations

,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC1 2,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC2 2,PC23,PC24,PC25
Lugius,0.0116,0.0128,0.018,0.0181,0.0119,0.0101,0. 0023,0.0057,-0.0005,-0.0124,-0.0043,-0.0041,0.0076,0.015,-0.0079,-0.0019,0.00
You have 17 values not 25

14. Originally Posted by lukaszM
But if somebody is Eastern German nMonte2 still show him as 50% British + 50% Russian.
Which is not at all inaccurate, considering that Eastern Germans did not exist as a population before 1200 AD.

If it models an East German as 50% Dutch + 50% Slavic, it just shows his ancestry from the last ~900 years.

Origins of settlers in Mecklenburg & Pommern based on Helmold (mainly from Holland, Utrecht and Flanders):

http://www.feudalismus.de/bauern.jpg

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