[R-sig-Geo] Problem with moran.mc() in spdep package

[Leandro Roser]

Hello everyone. I'm new in this group. I will appreciate any
suggestion for solving the following problem.
I am using the package spdep, with the purpose computing bootstraped
values of  Moran's I over a range of geographical distances.  The
weighing matrix for each range was obtained with the package adegenet:

library(adegenet)
library(spdep)


xy<-c(381739,383080,396833,397637,379144,379347,379488,379543,380018,380064,380085,380138,380277,380334,380404,380968,381037,399015,399029,398980,399013,399083,399209,399285,399351,399389,399427,399485,399526,399545,399590,399545,399528,399350,399348,399300,399222,399127,399119,399087,399063,399024,399154,399193,399187,399185,399173,399124,399082,399122,399081,399003,398982,398946,398900,398893,398860,398908,398897,398908,398941,398924,398972,399043,399034,399015,399048,402002,402120,401403,399127,398471,398196,397346,396927,396472,394941,411075,410840,410705,410602,410321,410364,410233,410230,410209,410217,410221,410266,410364,410444,410401,410431,410513,410480,410414,410347,410385,410417,410430,410465,410367,410259,410268,410334,410328,410344,410341,410398,410408,410352,410498,410315,410233,410183,410210,410215,410246,410481,410494,390915,395462,378616,378898,378972,379005,379024,379055,379080,379122,379199,379254,379404,379402,404070,403921,403531,403027,414950,414867,414685,414587,414454,414011,413896,413804,413597,413513,413474,413414,413473,413217,413099,412908,412837,410570,378883,379124,379330,384327,384735,385000,385116,387763,385189,385298,385419,387738,387935,393172,394798,377709,377633,377478,377469,377486,377498,377523,377541,377562,377592,377620,377664,377683,377737,377773,377838,377883,378099,378135,378208,378516,6925207,6923900,6904017,6903938,6899689,6898704,6897820,6897673,6895093,6894715,6894596,6894417,6893664,6893358,6892984,6891698,6891385,6908553,6908485,6908457,6908424,6908510,6908558,6908540,6908537,6908522,6908562,6908557,6908533,6908484,6908587,6908630,6908688,6908649,6908583,6908675,6908720,6908546,6908592,6908651,6908703,6908824,6908684,6908731,6908775,6908831,6908882,6908884,6908907,6908955,6908994,6909005,6908881,6908964,6909071,6909110,6909215,6909170,6909087,6908999,6908918,6909204,6909196,6909165,6909115,6909066,6909028,6918317,6918254,6918655,6919937,6920385,6920528,6921056,6921354,6921611,6922552,6910046,6909714,6909495,6909328,6910006,6910111,6910101,6910064,6909673,6909630,6909439,6909368,6909345,6909339,6909237,6909517,6909536,6909604,6909616,6909791,6909902,6909985,6910059,6910096,6910151,6909876,6910196,6909415,6909504,6909554,6909591,6909603,6909702,6909858,6910075,6910067,6909747,6909774,6909922,6909968,6910150,6909847,6909943,6910899,6906497,6912776,6912329,6911976,6911662,6911381,6911210,6911059,6910730,6910494,6910306,6909713,6909620,6917160,6917244,6917468,6917746,6909363,6909406,6909513,6909567,6909647,6910024,6910181,6910330,6910584,6910708,6910822,6910898,6911012,6911214,6911321,6911614,6911690,6913180,6927706,6927573,6927499,6922144,6921488,6921083,6920895,6916349,6920789,6920632,6920453,6916581,6915727,6903415,6903553,6918153,6917985,6917619,6917449,6917261,6917044,6916877,6916742,6916548,6916181,6915971,6915724,6915572,6915110,6914943,6914747,6914650,6914112,6913978,6913765,6912930)

xy<-matrix(xy,192,2)

VAR<-c(0.39,0.38,0.39,0.28,0.32,0.29,0.46,0.32,0.33,0.29,0.33,0.31,0.35,0.36,0.39,0.48,0.42,0.47,0.34,0.38,0.42,0.42,0.71,0.71,0.57,0.55,0.56,0.6,0.59,0.58,0.65,0.66,0.6,0.58,0.57,0.57,0.56,0.65,0.68,0.69,0.67,0.66,0.63,0.6,0.61,0.63,0.62,0.63,0.64,0.64,0.63,0.61,0.67,0.66,0.68,0.68,0.62,0.65,0.68,0.66,0.66,0.6,0.54,0.58,0.58,0.59,0.58,0.22,0.38,0.38,0.35,0.35,0.26,0.33,0.45,0.44,0.24,0.29,0.37,0.34,0.4,0.47,0.5,0.52,0.51,0.42,0.44,0.6,0.46,0.36,0.32,0.58,0.42,0.27,0.24,0.41,0.3,0.43,0.46,0.48,0.52,0.54,0.34,0.6,0.55,0.63,0.59,0.58,0.41,0.29,0.33,0.5,0.49,0.29,0.32,0.4,0.5,0.56,0.42,0.48,0.27,0.27,0.33,0.32,0.38,0.36,0.37,0.44,0.47,0.33,0.34,0.37,0.34,0.41,0.53,0.47,0.41,0.5,0.35,0.41,0.38,0.42,0.36,0.35,0.35,0.36,0.28,0.26,0.26,0.3,0.32,0.23,0.32,0.45,0.35,0.31,0.48,0.38,0.5,0.42,0.31,0.38,0.42,0.53,0.37,0.44,0.49,0.49,0.48,0.3,0.6,0.29,0.32,0.3,0.33,0.26,0.33,0.43,0.37,0.29,0.27,0.32,0.27,0.32,0.36,0.37,0.32,0.36,0.3,0.39,0.34,0.29)


lista<-chooseCN(xy,type=5,d1=5,d2=50, result.type = "listw",plot.nb = F)
#listw object obtained with adegenet


moran.mc(VAR,lista,999,na.action = na.exclude, zero.policy = T)

# Monte-Carlo simulation of Moran's I

#data:  VAR
#weights: lista
#number of simulations + 1: 1000
#
#*statistic = 1.2597*, observed rank = 1000, p-value = 0.001
#alternative hypothesis: greater


#How can I intepret this result (Moran >1)?  Extracting the values in the
object "lista", I obtained:

print(lista,zero.policy=TRUE)
#n   nn S0 S1  S2
#W 39 1521 39 69 162

#And using these parameters in the function moran():

moran(VAR,lista,39,39, zero.policy =T)
#$I
#[1] *0.2558731*
#
#$K
#[1] 1.911139

#The result of moran() is different of the obtained with moran.mc (and is
not higher than 1). Might be a problem in the moran.mc() function?

Thanks in advance,

  Leandro.







-- 
Lic. Leandro Gabriel Roser
 Laboratorio de Genética
 Dto. de Ecología, Genética y Evolución,
 F.C.E.N., U.B.A.,
 Ciudad Universitaria, PB II, 4to piso,
 Nuñez, Cdad. Autónoma de Buenos Aires,
 Argentina.
 tel ++54 +11 4576-3300 (ext 219)
 fax ++54 +11 4576-3384

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