LukaszM G25 finally:)

[Lucas]

Yesterday I decided to buy coordinates...

[1] "distance%=8.2406"

Lukasz_scaled

Yamnaya_Samara,50.2
Barcin_N,33
WHG,16.8


G25 North Euro scaled

https://i.postimg.cc/Fz6KqHcX/G25-North-Euro-scaled.png


Nmonte ancient averages

Sunghir_Medieval 1.993991
Avar_Hungary_Szolad 2.210232
Kazakhstan_Golden_Horde_Euro 2.412903
Lithuania_BA 2.439851
Beaker_Czech_o 3.331006
Latvia_BA 3.350074
Slavic_Bohemia 3.516006
Sweden_Viking_Age_Sigtuna 3.694306
Varna_o 3.711873
Scythian_Ukraine 3.855022


Sunghir_Medieval,41.2
Lithuania_BA,26.4
Kazakhstan_Golden_Horde_Euro,12.6
Latvia_BA,5.2
Lithuania_Late_Antiquity_low_res,4.6
Varna_o,4.6
Kumtepe_LN4_low_res,0.8
Anatolia_MLBA_low_res,0.6
Hungary_Prescythian_IA,0.6
Anatolia_IA_low_res,0.4
Armenia_ChL,0.4
Beaker_Czech_o,0.4
Levant_BA_North,0.4
Armenian,0.2
Avar_Hungary_Szolad,0.2
Czech_MN,0.2
Hungary_BA,0.2
Iran_recent,0.2
Karakalpak,0.2
Kyrgyzstan_Nomad_Med,0.2
Nepal_Samdzong_1500BP,0.2
Starcevo_N,0.2


pen=0

Latvia_BA,32.8
Lithuania_BA,31.2
Lithuania_Late_Antiquity_low_res,10.2
Ukraine_N_o,9.8
Kumtepe_LN4_low_res,8.2
Anatolia_MLBA_low_res,4.4
Hovsgol_BA_low_res,1.6
Egypt_Hellenistic,1
South_Africa_2000BP,0.4
Morocco_Iberomaurusian,0.2
Satan_MLBA_Alakul,0.2

Baltid stronk!

[Celestia]

Oh Lukasz
Every time I see a new map of yours I just wanna throw my money your way.

[Gründig]

You didn't have it all this time???

[Lucas]

G25 ancient with individuals

Latvia_BA--Kivutkalns207,33.2
Latvia_BA--Kivutkalns215,19.6
Lithuania_BA--Turlojiske3,10.6
Ukraine_N_o--I3719,10.6
Kumtepe_LN4_low_res--kum4,6.6
Peloponnese_N--I2937,4
Lithuania_Late_Antiquity_low_res--DA171,3.4
CWC_Baltic_early--I4629,2.4
Saidu_Sharif_IA--S7721.E1.L1,1.6
CWC_Proto-Unetice_Poland--RISE431,1
Levant_ChL--I1165,1
Sappali_Tepe_BA--I7542,1
Sintashta_MLBA--I1008,0.8
Sweden_Viking_Age_Sigtuna--vik_kal009,0.8
Anatolia_MLBA_low_res--MA2208,0.6
Hovsgol_BA_low_res--ARS003,0.6
Hungary_Medieval_Szolad--SZ18,0.6
Sarmatian_West--DA144,0.4
Kazakhstan_Golden_Horde_Euro--DA29,0.2
Latvia_BA--Kivutkalns42,0.2
Levant_ChL--I1184,0.2
South_Africa_2000BP--I9028.SG,0.2
South_Africa_2000BP--I9133.SG,0.2
USA_Spirit_Cave_11000BP--AHUR770c,0.2

[Lucas]

You didn't have it all this time???

I was waiting for Polish Wielbark and early medieval samples to be added, but this probably never happen:)

[Lucas]

whole spreadsheet

Ukrainian:Ukrainian13 2.179401
Russian_Smolensk:Russia_Smol339 2.346090
Polish:Polish8 2.466745
Belarusian:Belarusian15 2.572511
Ukrainian:Ukrainian9 2.609571
Russian_Smolensk:Russia_Smol345 2.615775
Russian_Voronez:RussianVoron103 2.727884
Polish:Polish24 2.763679
Belarusian:Belarusian6 2.776531
Belarusian:Belarusian11 2.803468


Ukrainian,34
Polish,26.4
Belarusian,11.8
Russian_Smolensk,10.2
Russian_Voronez,5.8
Latvia_BA,4.6
Lithuanian,1.6
Macedonian,1
Latvian,0.6
Russian_Kursk,0.6
Sweden_Viking_Age_Sigtuna,0.6
Czech,0.4
Kazakhstan_Golden_Horde_Euro,0.4
Lithuania_BA,0.4
Serbian,0.4
Bulgarian,0.2
Croatian,0.2
German,0.2
Kumtepe_LN4_low_res,0.2
Poland_BKG_o2,0.2
Slovenian,0.2

[Dick]

I was waiting for Polish Wielbark and early medieval samples to be added, but this probably never happen:)

Why won’t they be? Which raw data did you use?

[Lucas]

nMonte modern scaled pen=0.001

Ukrainian,39.2
Polish,22.2
Belarusian,16
Russian_Smolensk,12.6
Russian_Voronez,4.8
Lithuanian,3.4
Latvian,0.8
Russian_Kursk,0.4
Austrian,0.2
Macedonian,0.2
Slovenian,0.2

unscaled

Ukrainian,24.2
Russian_Voronez,18.4
Belarusian,17.2
Polish,14
Russian_Smolensk,13.2
Lithuanian,4.4
Latvian,4
Russian_Kursk,1.8
Estonian,1.6
Russian_Tver,0.4
Vepsian,0.4
Mordovian,0.2
Russian_Orel,0.2

[Lucas]

Why won’t they be? Which raw data did you use?

I have only FTDNA so far, I sent Davidski 37build variant.

[Lucas]

Mixed Mode oracle with moderns



[1,] "Russian_Voronez:RussianVoron103" "0.0126"
[2,] "Russian_Smolensk:Russia_Smol339" "0.0126"
[3,] "Belarusian:Belarusian15" "0.0128"
[4,] "Polish:Polish8" "0.0131"
[5,] "Ukrainian:Ukrainian13" "0.0135"
[6,] "Russian_Smolensk:Russia_Smol349" "0.014"
[7,] "Russian_Smolensk:Russia_Smol350" "0.0143"
[8,] "Ukrainian:Ukrainian9" "0.0143"
[9,] "Russian_Kursk:RussianKursk15" "0.0145"
[10,] "Russian_Smolensk:Russia_Smol345" "0.0145"
[11,] "Russian_Orel:russianOrjol1" "0.0146"
[12,] "Belarusian:Belarusian1" "0.0147"
[13,] "Russian_Tver:Russia_Tver442" "0.0147"
[14,] "Russian_Kursk:RussianKursk18" "0.015"
[15,] "Ukrainian:Ukrainian4" "0.0152"
[16,] "Ukrainian:Ukrainian19" "0.0153"
[17,] "Lithuanian:LithuanianA1" "0.0154"
[18,] "Belarusian:Belarusian9" "0.0154"
[19,] "Polish:Polish24" "0.0156"
[20,] "Belarusian:Belarusian6" "0.0158"
[21,] "Vepsian:vepsa19" "0.0162"
[22,] "Belarusian:Belarusian10" "0.0163"
[23,] "Polish:Polish2" "0.0165"
[24,] "Ukrainian:Ukrainian5" "0.0165"
[25,] "Ukrainian:Ukrainian16" "0.0165"
[26,] "Ukrainian:Ukrainian14" "0.0166"
[27,] "Russian_Orel:russianOrjol100" "0.0173"
[28,] "Ukrainian:Ukrainian6" "0.0174"
[29,] "Ukrainian:Ukrainian21" "0.0174"
[30,] "Russian_Smolensk:SM256_russian_Smolensk" "0.0177"
[31,] "Belarusian:Belarusian12" "0.0182"
[32,] "Russian_Smolensk:Russia_Smol303" "0.0182"
[33,] "Belarusian:Belarusian2" "0.0182"
[34,] "Russian_Smolensk:Russia_Smol304" "0.0184"
[35,] "Latvian:latvian22J5" "0.0186"
[36,] "Belarusian:Belarusian11" "0.0188"
[37,] "Lithuanian:LithuanianD1" "0.0188"
[38,] "Cossack_Ukrainian:GS000035238" "0.019"
[39,] "Ukrainian:Ukrainian23" "0.0191"
[40,] "Russian_Voronez:RussianVoron107" "0.0192"
[41,] "Russian_Orel:russianOrjol56" "0.0193"
[42,] "Russian_Orel:russianOrjol89" "0.0194"
[43,] "Ukrainian:Ukrainian2" "0.0199"
[44,] "Ukrainian:Ukrainian11" "0.02"
[45,] "Belarusian:Belarusian4" "0.02"
[46,] "Polish:Polish37" "0.0201"
[47,] "Estonian:Est393" "0.0202"
[48,] "Polish:Polish7" "0.0203"
[49,] "Lithuanian:LithuanianE2" "0.0205"
[50,] "Polish:Polish25" "0.0206"
[51,] "Polish:Polish31" "0.0207"
[52,] "Mordovian:Mordovian11" "0.0207"
[53,] "Russian_Voronez:RussianVoron105" "0.0207"
[54,] "Estonian:Est375" "0.0208"
[55,] "Mordovian:Mordovian23" "0.0209"
[56,] "Polish:Polish32" "0.021"
[57,] "Ukrainian:Ukrainian7" "0.0211"
[58,] "Slovenian:Slovenian147" "0.0212"
[59,] "Mordovian:Mordovian9" "0.0214"
[60,] "Latvian:latvian54H7" "0.0215"




[1,] "45.8% Latvian:latvian22J5 + 54.2% Ukrainian:Ukrainian5" "0.0093"
[2,] "49.6% Russian_Smolensk:Russia_Smol339 + 50.4% Russian_Voronez:RussianVoron103" "0.0096"
[3,] "49% Belarusian:Belarusian15 + 51% Russian_Voronez:RussianVoron103" "0.0097"
[4,] "59.6% Belarusian:Belarusian15 + 40.4% Polish:Polish24" "0.0098"
[5,] "33.6% Estonian:Est375 + 66.4% Ukrainian:Ukrainian13" "0.0098"
[6,] "43.8% Russian_Smolensk:Russia_Smol349 + 56.2% Russian_Voronez:RussianVoron103" "0.0098"
[7,] "57.1% Russian_Voronez:RussianVoron103 + 42.9% Ukrainian:Ukrainian9" "0.0098"
[8,] "32.9% Latvian:latvian22J5 + 67.1% Russian_Voronez:RussianVoron103" "0.0099"
[9,] "42.7% Russian_Smolensk:Russia_Smol350 + 57.3% Russian_Voronez:RussianVoron103" "0.01"
[10,] "29.3% Estonian:Est375 + 70.7% Russian_Voronez:RussianVoron103" "0.01"
[11,] "39.4% Lithuanian:LithuanianA1 + 60.6% Russian_Voronez:RussianVoron103" "0.01"
[12,] "53% Lithuanian:LithuanianA1 + 47% Ukrainian:Ukrainian5" "0.01"
[13,] "57% Belarusian:Belarusian15 + 43% Russian_Smolensk:Russia_Smol345" "0.0101"
[14,] "28.5% Belarusian:Belarusian7 + 71.5% Ukrainian:Ukrainian13" "0.0101"
[15,] "46.3% Russian_Smolensk:Russia_Smol345 + 53.7% Ukrainian:Ukrainian13" "0.0101"
[16,] "28% Latvian:latvian54H7 + 72% Russian_Voronez:RussianVoron103" "0.0102"
[17,] "52% Belarusian:Belarusian6 + 48% Ukrainian:Ukrainian5" "0.0102"
[18,] "35.3% Latvian:latvian54H7 + 64.7% Russian_Smolensk:Russia_Smol345" "0.0102"
[19,] "37.9% Belarusian:Belarusian6 + 62.1% Russian_Voronez:RussianVoron103" "0.0102"
[20,] "50.7% Belarusian:Belarusian10 + 49.3% Ukrainian:Ukrainian16" "0.0102"
[21,] "64.8% Belarusian:Belarusian15 + 35.2% Ukrainian:Ukrainian6" "0.0103"
[22,] "41.5% Russian_Smolensk:Russia_Smol345 + 58.5% Russian_Voronez:RussianVoron103" "0.0103"
[23,] "31.4% Lithuanian:LithuanianD1 + 68.6% Russian_Voronez:RussianVoron103" "0.0103"
[24,] "42.2% Belarusian:Belarusian6 + 57.8% Ukrainian:Ukrainian13" "0.0103"
[25,] "36.3% Russian_Smolensk:Russia_Smol304 + 63.7% Ukrainian:Ukrainian13" "0.0103"
[26,] "49.9% Lithuanian:LithuanianA1 + 50.1% Ukrainian:Ukrainian19" "0.0103"
[27,] "44.1% Polish:Polish2 + 55.9% Russian_Smolensk:Russia_Smol345" "0.0103"
[28,] "39.6% Russian_Kursk:RussianKursk18 + 60.4% Russian_Voronez:RussianVoron103" "0.0103"
[29,] "52% Belarusian:Belarusian15 + 48% Polish:Polish8" "0.0103"
[30,] "72.1% Russian_Voronez:RussianVoron103 + 27.9% Ukrainian:Ukrainian7" "0.0104"
[31,] "54.9% Russian_Voronez:RussianVoron103 + 45.1% Ukrainian:Ukrainian13" "0.0104"
[32,] "41.5% Belarusian:Belarusian9 + 58.5% Polish:Polish8" "0.0104"
[33,] "67% Lithuanian:LithuanianA1 + 33% Slovenian:Slovenian137" "0.0104"
[34,] "63.8% Russian_Voronez:RussianVoron103 + 36.2% Vepsian:vepsa19" "0.0104"
[35,] "64.1% Russian_Smolensk:Russia_Smol339 + 35.9% Ukrainian:Ukrainian5" "0.0104"
[36,] "46.7% Polish:Polish8 + 53.3% Russian_Voronez:RussianVoron103" "0.0104"
[37,] "37.6% Polish:Polish24 + 62.4% Russian_Voronez:RussianVoron103" "0.0105"
[38,] "49.3% Belarusian:Belarusian15 + 50.7% Russian_Smolensk:Russia_Smol339" "0.0105"
[39,] "27.6% Mordovian:Mordovian23 + 72.4% Russian_Voronez:RussianVoron103" "0.0105"
[40,] "55.8% Polish:Polish8 + 44.2% Russian_Smolensk:Russia_Smol345" "0.0105"
[41,] "60.2% Lithuanian:LithuanianA1 + 39.8% Ukrainian:Ukrainian2" "0.0105"
[42,] "53.9% Belarusian:Belarusian15 + 46.1% Ukrainian:Ukrainian13" "0.0105"
[43,] "46.4% Polish:Polish24 + 53.6% Russian_Kursk:RussianKursk15" "0.0105"
[44,] "43.3% Polish:Polish2 + 56.7% Ukrainian:Ukrainian9" "0.0106"
[45,] "56.4% Russian_Smolensk:Russia_Smol345 + 43.6% Ukrainian:Ukrainian16" "0.0106"
[46,] "57.6% Belarusian:Belarusian15 + 42.4% Ukrainian:Ukrainian9" "0.0107"
[47,] "39.6% Russian_Tver:Russia_Tver442 + 60.4% Russian_Voronez:RussianVoron103" "0.0107"
[48,] "72.2% Belarusian:Belarusian15 + 27.8% Ukrainian:Ukrainian7" "0.0107"
[49,] "46.9% Polish:Polish8 + 53.1% Russian_Smolensk:Russia_Smol339" "0.0107"
[50,] "61.2% Belarusian:Belarusian15 + 38.8% Ukrainian:Ukrainian19" "0.0107"
[51,] "34.9% Belarusian:Belarusian10 + 65.1% Russian_Voronez:RussianVoron103" "0.0107"
[52,] "20.7% Mordovian:Mordovian1 + 79.3% Ukrainian:Ukrainian13" "0.0107"
[53,] "61.5% Belarusian:Belarusian15 + 38.5% Belarusian:Belarusian9" "0.0107"
[54,] "62.5% Russian_Voronez:RussianVoron103 + 37.5% Ukrainian:Ukrainian4" "0.0107"
[55,] "53% Russian_Smolensk:Russia_Smol345 + 47% Ukrainian:Ukrainian19" "0.0108"
[56,] "22.3% Karelian:karelia7 + 77.7% Ukrainian:Ukrainian13" "0.0108"
[57,] "59.5% Belarusian:Belarusian15 + 40.5% Russian_Tver:Russia_Tver442" "0.0108"
[58,] "57.3% Russian_Smolensk:Russia_Smol350 + 42.7% Ukrainian:Ukrainian5" "0.0108"
[59,] "56.3% Polish:Polish8 + 43.7% Russian_Kursk:RussianKursk15" "0.0108"
[60,] "22% Karelian:karelia5 + 78% Russian_Voronez:RussianVoron103" "0.0108"

[Not a Cop]

nMonte modern scaled pen=0.001

Ukrainian,39.2
Polish,22.2
Belarusian,16
Russian_Smolensk,12.6
Russian_Voronez,4.8
Lithuanian,3.4
Latvian,0.8
Russian_Kursk,0.4
Austrian,0.2
Macedonian,0.2
Slovenian,0.2

unscaled

Ukrainian,24.2
Russian_Voronez,18.4
Belarusian,17.2
Polish,14
Russian_Smolensk,13.2
Lithuanian,4.4
Latvian,4
Russian_Kursk,1.8
Estonian,1.6
Russian_Tver,0.4
Vepsian,0.4
Mordovian,0.2
Russian_Orel,0.2

How have you done this?

[Lucas]

How have you done this?

Here are G25 ancient unscaled: https://www.dropbox.com/s/34jvqkongg9ts8t/AncientAprilUnscaled.txt?dl=0
Ancient scaled: https://www.dropbox.com/s/v8l8wz36tb792js/AncientAprilScaled.txt?dl=0

Modern unscaled: https://www.dropbox.com/s/8e8y21npedi15cf/ModernAprilUnscaled.txt?dl=0
Modern scaled: https://www.dropbox.com/s/0ogmhpuu06g3zxj/ModernAprilScaled.txt?dl=0[/QUOTE]

[Lucas]

G25 custom calcs

Anglesqueville K7 pen=0.01

fit: 2.5614,

NE-Euro_K7: 73.33,
Central-Euro_K7: 21.67,
South-Euro_K7: 5,


Capitalis modern Europe K16 pen=0.01

fit: 1.3738,

Polish_Belarusian_Ukrainian_K18: 94.17,
Estonian_Latvian_Lithuanian_K18: 5.83,
,

[Lucas]

Dorkymon only Euro pen=0.01

fit: 1.4291,

"Eastern European_": 100, :)

Finnangle K8 pen=0

fit": 2.2557,
Central-East_K8": 85.83,
South_Med_K8": 14.17,

ltg European K8 pen=0

fit: 1.9031,

Baltic_K8: 81.67,
West_Mediterranean_K8: 8.33,
East_Mediterranean_K8: 7.5,
North_Africa_K8: 1.67,
North_Sea_K8: 0.83,

[Lucas]

Michal K 50 pen=0.01
fit: 2.4289,

K50_Balto_Slavic_North: 69.17,
K50_Polish_Ukrainian: 27.5,
K50_Balkan: 3.33,


Michal K25 pen=0

fit: 2.8559,

Balto_Slavic_K25: 97.5,
Arabic_K25: 1.67,
Neolithic_Farmers_K25: 0.83,

Michal K8 pen=0

fit: 2.7605,
Baltic_K8: 75.83,
Mediterranean_K8: 24.17,

ph2ter K12 pen=0.01

fit: 3.2297,

Baltic_K12: 79.17,
Atlantic_K12: 10.83,
Caucasian_K12: 6.67,
Mediterranean_K12: 3.33,

[Lucas]

Randwulf Iron Age Europe K26[/B] pen=0.01

fit: 1.9701,

Baltic: 69.17,
CentEurope: 10,
WMed: 8.33,
SAtlantic: 5.83,
NEurope: 2.5,
Caucasian: 1.67,
EMed: 1.67,
SWAsian: 0.83,

pen=0

fit: 1.5034,

Baltic: 70.83,
EMed: 10.83,
SAtlantic: 8.33,
CentEurope: 4.17,
SWAsian: 4.17,
WMed: 1.67,


Randwulf K15 pen=0

fit: 1.8027,

NEEurope_K15: 87.5,
EastMed_K15: 5,
WAsian_K15: 5,
WestMed_K15: 1.67,
ArchaicAfrican_K15: 0.83,

pen=0.01

NEEurope_K15: 88.33,
SWEurope_K15: 4.17,
EastMed_K15: 3.33,
NWEurope_K15: 2.5,
WAsian_K15: 0.83,
WestMed_K15: 0.83,



Phter ancient IA pen=0.01

fit: 2.8595,

BALTIC: 58.33,
PANNONIAN: 19.17,
CELTIC-SOUTHEAST: 8.33,
MACEDONIAN-THRACIAN: 5,
ILLYRIAN: 3.33,
PANNONIAN-PONTIC: 3.33,
ALANIC: 1.67,
GREEK: 0.83,

[Joso]

Nice

[Not a Cop]

Here are G25 ancient unscaled: https://www.dropbox.com/s/34jvqkongg9ts8t/AncientAprilUnscaled.txt?dl=0
Ancient scaled: https://www.dropbox.com/s/v8l8wz36tb792js/AncientAprilScaled.txt?dl=0

Modern unscaled: https://www.dropbox.com/s/8e8y21npedi15cf/ModernAprilUnscaled.txt?dl=0
Modern scaled: https://www.dropbox.com/s/0ogmhpuu06g3zxj/ModernAprilScaled.txt?dl=0[/QUOTE]

Can you share pop averages?

[Lucas]

Can you share pop averages?

I had this results using modern spreadsheet which you quoted.
Simply nMonte (in R) will average individual samples for populations (in this spreadsheet) because there have such format Belarussian123:Belarussian or German001:East-German. Just try.
So no need to use real averages. According to Ger Huibregts it has even better accuracy.

[rothaer]

I had this results using modern spreadsheet which you quoted.
Simply nMonte (in R) will average individual samples for populations (in this spreadsheet) because there have such format Belarussian123:Belarussian or German001:East-German. Just try.
So no need to use real averages. According to Ger Huibregts it has even better accuracy.

Ok, here are my results with the modern pops table and all scaled:

> getMonte('ModernAprilScaled.txt', 'target.txt', pen=0)
[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
German:German76 Swedish:Sweden9 Swedish:Sweden13
2.191621 2.392999 2.483858
German:German40 Czech:NA15726 Swedish:Sweden7
2.643757 2.692387 2.742271
Czech:NA15729 Slovenian:Slovenian90
2.805730 2.840886

[1] "2. FULL TABLE nMONTE"
[1] "penalty= 0"
[1] "Ncycles= 1000"
[1] "distance%=0.4353"

JK_scaled

Dutch,31.8
German,21.8
Estonian,13.8
Russian_Smolensk,7.4
Polish,5.2
Latvian,4.4
Irish,3.6
French,3.2
Belgian,2.8
Belarusian,1.4
Lithuanian,1.4
Sardinian,1.4
Austrian,0.4
Spanish_Pais_Vasco,0.4
Czech,0.2
Karelian,0.2
Spanish_Galicia,0.2
Ukrainian,0.2
Yemenite_Mahra,0.2

[Lucas]

Ok, here are my results with the modern pops table and all scaled:

> getMonte('ModernAprilScaled.txt', 'target.txt', pen=0)
[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
German:German76 Swedish:Sweden9 Swedish:Sweden13
2.191621 2.392999 2.483858
German:German40 Czech:NA15726 Swedish:Sweden7
2.643757 2.692387 2.742271
Czech:NA15729 Slovenian:Slovenian90
2.805730 2.840886

[1] "2. FULL TABLE nMONTE"
[1] "penalty= 0"
[1] "Ncycles= 1000"
[1] "distance%=0.4353"

JK_scaled

Dutch,31.8
German,21.8
Estonian,13.8
Russian_Smolensk,7.4
Polish,5.2
Latvian,4.4
Irish,3.6
French,3.2
Belgian,2.8
Belarusian,1.4
Lithuanian,1.4
Sardinian,1.4
Austrian,0.4
Spanish_Pais_Vasco,0.4
Czech,0.2
Karelian,0.2
Spanish_Galicia,0.2
Ukrainian,0.2
Yemenite_Mahra,0.2

Hi Rothaer, nice to see you on this forum.

Can you post results with penalization=0.01?

[Not a Cop]

I had this results using modern spreadsheet which you quoted.
Simply nMonte (in R) will average individual samples for populations (in this spreadsheet) because there have such format Belarussian123:Belarussian or German001:East-German. Just try.
So no need to use real averages. According to Ger Huibregts it has even better accuracy.

Thanks, i somehow still get problems in R, probably because i don't yet have propper Excel software on new laptop and using google docs, can i please ask you to run my coordinates.

,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
Rutger_scaled,0.129758,0.105615,0.073539,0.07106,0 .030159,0.025658,0.00752,0.011307,-0.006954,-0.027153,-0.004384,-0.008842,0.017393,0.01445,-0.0057,0.004641,0.00339,-0.004941,-0.00088,0.003752,0.002371,-0.000742,0.004807,0.003012,-0.003832

,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
Rutger,0.0114,0.0104,0.0195,0.022,0.0098,0.0092,0. 0032,0.0049,-0.0034,-0.0149,-0.0027,-0.0059,0.0117,0.0105,-0.0042,0.0035,0.0026,-0.0039,-0.0007,0.003,0.0019,-0.0006,0.0039,0.0025,-0.0032

[rothaer]

Hi Rothaer, nice to see you on this forum.

Can you post results with penalization=0.01?

Hi Lukasz, thanks, here it is (incredible different in respect to Dutch):

[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
German:German76 Swedish:Sweden9 Swedish:Sweden13
2.191621 2.392999 2.483858
German:German40 Czech:NA15726 Swedish:Sweden7
2.643757 2.692387 2.742271
Czech:NA15729 Slovenian:Slovenian90
2.805730 2.840886

[1] "2. FULL TABLE nMONTE"
[1] "penalty= 0.01"
[1] "Ncycles= 1000"
[1] "distance%=1.3405"

JK_scaled

German,30
Swedish,12.2
Polish,6.6
Czech,5.4
Dutch,4.6
Austrian,3
Irish,2.8
Finnish,2.2
German_East,2.2
Scottish,2
English,1.8
English_Cornwall,1.8
French,1.8
Hungarian,1.8
Belarusian,1.6
Russian_Orel,1.6
Slovenian,1.6
Icelandic,1.4
Karelian,1.2
Finnish_East,1
Russian_Smolensk,1
Ukrainian,1
Croatian,0.8
Norwegian,0.8
Russian_Pinega,0.8
Russian_Tver,0.8
Slovakian,0.8
Belgian,0.6
Romanian,0.6
Basque_French,0.4
French_East,0.4
Lithuanian,0.4
Moldovan,0.4
Montenegrin,0.4
Mordovian,0.4
Orcadian,0.4
Russian_Kostroma,0.4
Russian_Kursk,0.4
Russian_Voronez,0.4
Shetlandic,0.4
Cossack_Kuban,0.2
Cossack_Ukrainian,0.2
French_South,0.2
Greek,0.2
Italian_Jew,0.2
Komi,0.2
Serbian,0.2
Tatar,0.2
Udmurt,0.2

[Lucas]

Hi Lukasz, thanks, here it is (incredible different in respect to Dutch):

[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
German:German76 Swedish:Sweden9 Swedish:Sweden13
2.191621 2.392999 2.483858
German:German40 Czech:NA15726 Swedish:Sweden7
2.643757 2.692387 2.742271
Czech:NA15729 Slovenian:Slovenian90
2.805730 2.840886

[1] "2. FULL TABLE nMONTE"
[1] "penalty= 0.01"
[1] "Ncycles= 1000"
[1] "distance%=1.3405"

JK_scaled

German,30
Swedish,12.2
Polish,6.6
Czech,5.4
Dutch,4.6
Austrian,3
Irish,2.8
Finnish,2.2
German_East,2.2
Scottish,2
English,1.8
English_Cornwall,1.8
French,1.8
Hungarian,1.8
Belarusian,1.6
Russian_Orel,1.6
Slovenian,1.6
Icelandic,1.4
Karelian,1.2
Finnish_East,1
Russian_Smolensk,1
Ukrainian,1
Croatian,0.8
Norwegian,0.8
Russian_Pinega,0.8
Russian_Tver,0.8
Slovakian,0.8
Belgian,0.6
Romanian,0.6
Basque_French,0.4
French_East,0.4
Lithuanian,0.4
Moldovan,0.4
Montenegrin,0.4
Mordovian,0.4
Orcadian,0.4
Russian_Kostroma,0.4
Russian_Kursk,0.4
Russian_Voronez,0.4
Shetlandic,0.4
Cossack_Kuban,0.2
Cossack_Ukrainian,0.2
French_South,0.2
Greek,0.2
Italian_Jew,0.2
Komi,0.2
Serbian,0.2
Tatar,0.2
Udmurt,0.2

Remember your Sigtuna archaic matches. Here you have Sweden still. Although not in pen=0 variant.

[rothaer]

Hi Rothaer, nice to see you on this forum.

Can you post results with penalization=0.01?

Can you tell in one sentence the functional difference between pen = 0 and pen = 0.01?

[Lucas]

Thanks, i somehow still get problems in R, probably because i don't yet have propper Excel software on new laptop and using google docs, can i please ask you to run my coordinates.

,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
Rutger_scaled,0.129758,0.105615,0.073539,0.07106,0 .030159,0.025658,0.00752,0.011307,-0.006954,-0.027153,-0.004384,-0.008842,0.017393,0.01445,-0.0057,0.004641,0.00339,-0.004941,-0.00088,0.003752,0.002371,-0.000742,0.004807,0.003012,-0.003832

,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
Rutger,0.0114,0.0104,0.0195,0.022,0.0098,0.0092,0. 0032,0.0049,-0.0034,-0.0149,-0.0027,-0.0059,0.0117,0.0105,-0.0042,0.0035,0.0026,-0.0039,-0.0007,0.003,0.0019,-0.0006,0.0039,0.0025,-0.0032

unscaled modern

Chuvash:559_R01C01 0.1157843
Ingrian:GS000016896 0.1257219
Russian_Kostroma:Russia_Kostr149 0.1303150
Mordovian:Mordovian15 0.1349444
Russian_Tver:Russia_Tver472 0.1369781
Russian_Voronez:russianVoron101 0.1520954
Russian_Tver:Russia_Tver418 0.1530229
Russian_Pinega:RusPinega1 0.1544442
Mordovian:Mordovian2 0.1549258
Mordovian:Mordovian17 0.1555185


Polish,14.2
Russian_Tver,11.6
Mordovian,11.2
Chuvash,10.8
Estonian,7.6
Finnish,7.2
Karelian,6.4
Russian_Kostroma,5
Russian_Voronez,4
Russian_Orel,3
Ingrian,2.8
Finnish_East,2.6
Belarusian,2.2
Dutch,1.2
Lithuanian,1.2
Czech,1
German,1
Cossack_Kuban,0.8
Latvian,0.8
Russian_Pinega,0.6
Slovakian,0.6
Russian_Kursk,0.4
Russian_Smolensk,0.4
Swedish,0.4
Ukrainian,0.4
Austrian,0.2
Belgian,0.2
Han,0.2
Hungarian,0.2
Icelandic,0.2
Irish,0.2
Kabardin,0.2
Khatri,0.2
Ror,0.2
Tajik_Rushan,0.2
Tatar_Lipka,0.2
Uthmankhel,0.2
Vepsian,0.2


pen=0

Estonian,19.8
Latvian,16.4
Karelian,14.6
Polish,14.2
Dutch,6.2
Lithuanian,5.6
German,4.6
Avar,4.2
Mordovian,3.6
Belarusian,2
Chechen,2
Japanese,1.2
Russian_Orel,1
Tabasaran,1
Kamboj,0.6
Tajik_Yagnobi,0.6
Brahmin_Uttar_Pradesh,0.4
Finnish,0.4
Kalash,0.2
Luhya_Kenya,0.2
Mari,0.2
Quechua,0.2
Russian_Kostroma,0.2
Russian_Smolensk,0.2
Russian_Voronez,0.2
Surui,0.2


scaled

Russian_Tver,22.4
Chuvash,12.6
Polish,8.8
Mordovian,8.2
Russian_Orel,7.2
Russian_Kursk,4.4
Finnish,4.2
Karelian,4.2
Estonian,3.8
Russian_Kostroma,3
Russian_Smolensk,2.8
Finnish_East,2.4
Ingrian,2.2
Belarusian,1.8
German,1.6
Russian_Voronez,1.6
Lithuanian,1.4
Irish,1.2
Latvian,0.6
Swedish,0.6
Ukrainian,0.6
Icelandic,0.4
Slovakian,0.4
Udmurt,0.4
Vepsian,0.4
Austrian,0.2
Balochi,0.2
Cossack_Kuban,0.2
Czech,0.2
Dutch,0.2
English,0.2
Gujarati,0.2
Hungarian,0.2
Iranian_Fars,0.2
Mayan,0.2
Moldovan,0.2
Russian_Pinega,0.2
Scottish,0.2
Tabasaran,0.2


pen=0

Estonian,17.6
Karelian,15
Latvian,14.2
Polish,14.2
Dutch,8.4
Mordovian,7.6
Lithuanian,5
German,3
Belarusian,2.4
Chechen,2
Russian_Orel,1.8
Avar,1.2
Yusufzai,1.2
Balkar,0.8
Kamboj,0.6
Russian_Tver,0.6
Tajik_Yagnobi,0.6
Ukrainian,0.6
Mari,0.4
Tabasaran,0.4
Tajik_Rushan,0.4
Brahmin_Uttar_Pradesh,0.2
Burusho,0.2
Cherkes,0.2
Komi,0.2
Quechua,0.2
Ror,0.2
Russian_Kostroma,0.2
Russian_Smolensk,0.2
Surui,0.2
Tarkalani,0.2

[Not a Cop]

unscaled modern

Chuvash:559_R01C01 0.1157843


Thanks, something is wrong however with that Chuvash sample i guess.

[Lucas]

Thanks, something is wrong however with that Chuvash sample i guess.
It is both in scaled and unscaled version. I guess he is mixed with Russian.

[Not a Cop]

It is both in scaled and unscaled version. I guess he is mixed with Russian.

Rather just Russian i guess, i ran him.

[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
Chuvash:559_R01C011 Mordovian:Mordovian2
0.000000 1.358676
Polish:Polish35 Polish:Polish5
1.363745 1.487582
Russian_Voronez:russianVoron101 Ingrian:GS000016896
1.487582 1.518486
Russian_Kostroma:Russia_Kostr149 Polish:Polish34
1.522498 1.524434