glmscore: Score Value in Generalized Linear Model
In augSIMEX: Analysis of Data with Mixed Measurement Error and Misclassification in Covariates
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
This function can be used to calculate the value of score function. This function can serve as a tool to assist the users in debugging their self-defined score function.
Usage
1
Arguments
beta
a vector specifying the value of parameters.
Y
a vector specifying the response.
data
a matrix or data frame of covariates. If this is for score function debugging purpose, see detail for the rearrangement of the dataset.
weight
a vector of weight.
offset
a vector of offset.
family
a glm “family” object.
Details
In a general setting, Y can be treated as a response and data as covariates.
This function helps to debug the user specified score function. The data are needed to be specially arranged such that the score function output can be successfully passed into augSIMEX function in a correct order. The data should be a matrix or data frame of a combination with error-prone covariates (in the order of err.var as in augSIMEX), other covariates and binary variable that is prone to misclassification. The intercept, if considered, should be included the category of “other covariates”.
Value
A matrix of n times m, where n is the number of observations and m is the number of parameters. Each entry in the matrix represents the calculated score value for subject i on parameter j. The vector of row sum will be the score value vector.
Author(s)
Qihuang Zhang and Grace Y. Yi.
References
McCullagh P. Generalized linear models[J]. European Journal of Operational Research, 1984, 16(3): 285-292.
See Also
Examples
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### The user specified function to be checked. (logit link in binomial family)
scorefunction=function(beta,Y,data,weight,offset){
results<-lapply(1:dim(data)[2],
FUN=function(i){
S<-lapply(1:dim(data)[1],function(x){
eta<- matrix(beta,nrow=1)
return(weight[x]*Y[x]*data[x,i]-weight[x]*exp(eta)/(1+exp(eta))*data[x,i])})
return(S)}
)
return(matrix(unlist(results),ncol=dim(data)[2]))
}
data(ToyUni)
### Data need to rearranged. See detail.
nsize<-length(ToyUni$Main[,"Y"])
data.in.score<-data.frame(intercept=1,X=ToyUni$Main[,"Xstar"],
W=ToyUni$Main[,"W"],Z=ToyUni$Main[,"Zstar"])
## compare. The results should be identical.
glmscore(rep(0,4),ToyUni$Main[,"Y"],data.in.score,rep(1,nsize),
rep(0,nsize),family=binomial(link=logit))
scorefunction(rep(0,4),ToyUni$Main[,"Y"],data.in.score,rep(1,nsize),rep(0,nsize))
Example output
[,1] [,2] [,3] [,4]
[1,] 0.5 1.512671100 0.0 0.0
[2,] 0.5 -1.308160599 0.0 0.0
[3,] 0.5 0.976864185 0.5 0.5
[4,] -0.5 -0.716462534 -0.5 0.0
[5,] -0.5 -1.312486545 -0.5 -0.5
[6,] 0.5 -0.856213441 0.5 0.5
[7,] -0.5 -0.900267789 0.0 0.0
[8,] 0.5 -0.989180711 0.0 0.0
[9,] -0.5 -1.597225204 0.0 -0.5
[10,] 0.5 -1.313330990 0.5 0.0
[11,] -0.5 -1.835406721 -0.5 0.0
[12,] 0.5 -0.451210392 0.5 0.5
[13,] 0.5 -1.397192919 0.0 0.5
[14,] -0.5 -2.014523049 0.0 -0.5
[15,] 0.5 0.227403726 0.5 0.0
[16,] 0.5 -0.991263236 0.0 0.0
[17,] -0.5 -2.113179843 -0.5 -0.5
[18,] -0.5 -1.298308056 0.0 0.0
[19,] -0.5 0.362132412 0.0 0.0
[20,] -0.5 -1.421596001 -0.5 0.0
[21,] 0.5 1.350782227 0.5 0.5
[22,] -0.5 -0.446276735 0.0 0.0
[23,] -0.5 -0.629196736 -0.5 0.0
[24,] 0.5 0.230996034 0.0 0.0
[25,] 0.5 -1.820003918 0.5 0.5
[26,] 0.5 0.489025506 0.5 0.5
[27,] -0.5 -0.777998406 0.0 -0.5
[28,] 0.5 -1.232841916 0.0 0.5
[29,] -0.5 -2.035855036 0.0 -0.5
[30,] -0.5 -1.057268679 0.0 0.0
[31,] 0.5 -0.680822766 0.5 0.5
[32,] 0.5 -1.185730073 0.0 0.0
[33,] 0.5 1.125394845 0.0 0.5
[34,] -0.5 -0.707193613 0.0 0.0
[35,] 0.5 -0.308891461 0.0 0.0
[36,] -0.5 -1.180977370 0.0 -0.5
[37,] -0.5 -1.321708394 0.0 0.0
[38,] 0.5 -0.041669167 0.0 0.0
[39,] -0.5 -0.067369120 -0.5 0.0
[40,] 0.5 0.571101125 0.0 0.0
[41,] -0.5 -0.630090534 0.0 -0.5
[42,] 0.5 -1.284909200 0.5 0.5
[43,] 0.5 -0.588519290 0.5 0.5
[44,] 0.5 0.007801140 0.5 0.0
[45,] 0.5 0.075563407 0.0 0.5
[46,] 0.5 -0.612740118 0.0 0.5
[47,] 0.5 0.188242050 0.5 0.0
[48,] 0.5 -1.661288678 0.0 0.5
[49,] 0.5 -1.459654290 0.0 0.5
[50,] -0.5 -0.563279555 0.0 -0.5
[51,] -0.5 -1.797834838 -0.5 0.0
[52,] 0.5 0.030781369 0.0 0.5
[53,] -0.5 -0.178489841 0.0 0.0
[54,] 0.5 -1.904248730 0.0 0.0
[55,] 0.5 0.282446236 0.5 0.0
[56,] 0.5 -0.768001441 0.5 0.5
[57,] 0.5 -0.608985228 0.5 0.0
[58,] -0.5 -0.847188683 0.0 0.0
[59,] 0.5 -0.530786987 0.0 0.0
[60,] 0.5 0.463576854 0.5 0.5
[61,] -0.5 -1.226204463 0.0 0.0
[62,] -0.5 -1.660871539 0.0 0.0
[63,] -0.5 -0.980314283 0.0 0.0
[64,] 0.5 0.182096704 0.0 0.0
[65,] 0.5 0.915053100 0.5 0.5
[66,] -0.5 -1.808344723 0.0 0.0
[67,] 0.5 0.228853740 0.5 0.5
[68,] 0.5 0.150196770 0.5 0.0
[69,] -0.5 -1.467012912 0.0 0.0
[70,] 0.5 1.307313826 0.5 0.0
[71,] 0.5 -0.823600027 0.5 0.0
[72,] -0.5 1.126328323 -0.5 -0.5
[73,] 0.5 -1.116248718 0.5 0.0
[74,] 0.5 -0.945288123 0.0 0.0
[75,] 0.5 0.027397902 0.0 0.0
[76,] 0.5 -0.387963705 0.0 0.0
[77,] 0.5 0.180259388 0.0 0.0
[78,] 0.5 -0.962677089 0.5 0.5
[79,] 0.5 0.412441987 0.0 0.5
[80,] -0.5 -0.945959995 -0.5 -0.5
[81,] -0.5 -0.335040243 -0.5 0.0
[82,] 0.5 -1.041484079 0.5 0.0
[83,] -0.5 -1.410524988 0.0 0.0
[84,] 0.5 0.428679360 0.5 0.0
[85,] -0.5 -1.497908628 0.0 -0.5
[86,] 0.5 -0.279029630 0.5 0.0
[87,] -0.5 -1.130470597 -0.5 -0.5
[88,] 0.5 -2.749602068 0.0 0.0
[89,] -0.5 -1.575500271 0.0 -0.5
[90,] 0.5 -1.270883378 0.5 0.0
[91,] 0.5 0.524758979 0.5 0.5
[92,] -0.5 0.931464489 0.0 0.0
[93,] -0.5 -0.528800132 0.0 -0.5
[94,] 0.5 0.007294486 0.0 0.5
[95,] -0.5 -1.458259974 -0.5 0.0
[96,] 0.5 -0.565536010 0.5 0.5
[97,] -0.5 -0.565717765 -0.5 -0.5
[98,] -0.5 0.020759372 0.0 -0.5
[99,] -0.5 -0.994009173 -0.5 0.0
[100,] 0.5 0.083115004 0.5 0.0
[101,] 0.5 -1.746123866 0.5 0.5
[102,] 0.5 -0.441969943 0.0 0.0
[103,] 0.5 -0.910880738 0.0 0.0
[104,] 0.5 0.192680286 0.5 0.5
[105,] -0.5 2.363180032 0.0 0.0
[106,] 0.5 0.677621918 0.5 0.0
[107,] -0.5 -0.711225917 -0.5 -0.5
[108,] 0.5 -0.755660223 0.0 0.5
[109,] -0.5 0.696788728 -0.5 -0.5
[110,] -0.5 -1.156830550 -0.5 0.0
[111,] 0.5 -1.811309486 0.0 0.5
[112,] 0.5 -0.116596436 0.5 0.5
[113,] 0.5 -1.248319057 0.5 0.0
[114,] 0.5 -0.192447592 0.0 0.5
[115,] -0.5 -1.519770375 -0.5 -0.5
[116,] 0.5 0.074572814 0.5 0.5
[117,] 0.5 0.414035904 0.0 0.5
[118,] 0.5 -1.209303741 0.5 0.0
[119,] -0.5 -1.784689220 -0.5 0.0
[120,] 0.5 -1.699394004 0.0 0.5
[121,] -0.5 -1.263785633 -0.5 0.0
[122,] -0.5 -0.900490198 0.0 0.0
[123,] 0.5 -0.660905661 0.0 0.5
[124,] 0.5 0.384100109 0.5 0.0
[125,] 0.5 0.028344858 0.0 0.0
[126,] -0.5 0.078830903 0.0 -0.5
[127,] 0.5 -0.206411427 0.5 0.5
[128,] -0.5 -0.560459078 -0.5 -0.5
[129,] -0.5 -1.910202287 -0.5 0.0
[130,] -0.5 -1.457932604 -0.5 0.0
[131,] -0.5 -1.394943754 -0.5 0.0
[132,] 0.5 -1.723529970 0.0 0.5
[133,] 0.5 -0.999966369 0.5 0.0
[134,] 0.5 -1.490231999 0.0 0.0
[135,] 0.5 0.072378657 0.0 0.5
[136,] -0.5 0.030523876 0.0 0.0
[137,] -0.5 -1.327227884 0.0 0.0
[138,] -0.5 -0.385999586 0.0 -0.5
[139,] 0.5 1.648602228 0.5 0.5
[140,] -0.5 -2.776902681 -0.5 0.0
[141,] 0.5 -2.462703197 0.0 0.5
[142,] 0.5 0.263770028 0.5 0.5
[143,] -0.5 0.182434252 0.0 0.0
[144,] 0.5 -0.874095742 0.5 0.0
[145,] 0.5 -0.380779821 0.0 0.0
[146,] -0.5 -0.022061881 0.0 -0.5
[147,] 0.5 -2.275354230 0.0 0.0
[148,] -0.5 1.173527076 0.0 0.0
[149,] 0.5 1.470870496 0.0 0.0
[150,] 0.5 -0.112396529 0.0 0.0
[151,] 0.5 -0.244804468 0.5 0.0
[152,] 0.5 -0.013683593 0.0 0.0
[153,] 0.5 -0.627270375 0.5 0.5
[154,] -0.5 -1.705678651 0.0 0.0
[155,] 0.5 -1.030522625 0.0 0.5
[156,] -0.5 -1.629168586 -0.5 0.0
[157,] -0.5 -1.449039264 -0.5 0.0
[158,] 0.5 0.720090350 0.0 0.5
[159,] 0.5 0.180033689 0.5 0.0
[160,] 0.5 -1.047505475 0.0 0.0
[161,] -0.5 0.189845403 0.0 0.0
[162,] 0.5 -0.608448803 0.0 0.0
[163,] 0.5 1.028962277 0.0 0.0
[164,] 0.5 -0.220731538 0.5 0.0
[165,] -0.5 -0.132302144 -0.5 -0.5
[166,] 0.5 -1.696947248 0.0 0.0
[167,] -0.5 -1.335002668 0.0 0.0
[168,] 0.5 -1.335245761 0.5 0.0
[169,] -0.5 -0.814223139 0.0 0.0
[170,] -0.5 0.571722347 0.0 0.0
[171,] -0.5 -0.088795585 -0.5 0.0
[172,] 0.5 -0.316410233 0.0 0.5
[173,] 0.5 -1.153262282 0.0 0.5
[174,] 0.5 -0.363609022 0.5 0.5
[175,] -0.5 -1.970937663 -0.5 0.0
[176,] 0.5 2.276406292 0.0 0.0
[177,] -0.5 -0.509177597 0.0 -0.5
[178,] -0.5 -1.316627802 -0.5 0.0
[179,] -0.5 -0.958434816 0.0 0.0
[180,] 0.5 -2.465025995 0.0 0.5
[181,] 0.5 -0.026557125 0.0 0.0
[182,] 0.5 -0.324067994 0.0 0.5
[183,] 0.5 -0.111427760 0.0 0.0
[184,] 0.5 -1.808780820 0.0 0.0
[185,] -0.5 -2.400446853 0.0 0.0
[186,] 0.5 -0.716597448 0.5 0.0
[187,] -0.5 -0.643948176 0.0 -0.5
[188,] 0.5 -1.477066033 0.0 0.5
[189,] -0.5 -2.461151175 0.0 -0.5
[190,] 0.5 -1.255469960 0.0 0.0
[191,] -0.5 -0.619512468 -0.5 -0.5
[192,] 0.5 -0.826937551 0.0 0.5
[193,] 0.5 -0.339641997 0.0 0.0
[194,] -0.5 -1.486893621 -0.5 0.0
[195,] -0.5 -1.482252086 0.0 -0.5
[196,] -0.5 -0.717794471 0.0 0.0
[197,] -0.5 -0.597231469 -0.5 -0.5
[198,] 0.5 -0.010449902 0.0 0.0
[199,] -0.5 -0.350852331 -0.5 -0.5
[200,] 0.5 0.503196173 0.0 0.5
[201,] -0.5 -2.514963793 -0.5 -0.5
[202,] -0.5 -2.299804994 0.0 0.0
[203,] -0.5 -1.277761983 0.0 0.0
[204,] 0.5 0.192592018 0.0 0.5
[205,] 0.5 0.163675807 0.0 0.0
[206,] -0.5 -0.886201541 -0.5 0.0
[207,] 0.5 -0.119900852 0.5 0.0
[208,] 0.5 0.227738425 0.5 0.0
[209,] 0.5 0.931078781 0.5 0.0
[210,] -0.5 0.132259132 -0.5 0.0
[211,] 0.5 -0.510211778 0.5 0.5
[212,] 0.5 -0.865626668 0.5 0.0
[213,] 0.5 -1.539812123 0.5 0.0
[214,] -0.5 -0.753189607 -0.5 0.0
[215,] 0.5 -1.406646293 0.5 0.5
[216,] -0.5 -0.925210712 0.0 -0.5
[217,] 0.5 0.781581198 0.5 0.5
[218,] -0.5 -0.418105281 0.0 0.0
[219,] 0.5 -1.486926338 0.5 0.0
[220,] 0.5 -0.100626916 0.0 0.0
[221,] 0.5 0.921112693 0.5 0.5
[222,] 0.5 -0.160891519 0.5 0.0
[223,] 0.5 -1.416342523 0.5 0.5
[224,] 0.5 -1.258684387 0.0 0.0
[225,] 0.5 -1.023704605 0.0 0.5
[226,] -0.5 -1.604714078 -0.5 -0.5
[227,] 0.5 -0.731091438 0.5 0.5
[228,] -0.5 -1.687655715 -0.5 0.0
[229,] -0.5 -0.943174585 0.0 0.0
[230,] 0.5 0.133093673 0.5 0.5
[231,] -0.5 -0.160227200 0.0 0.0
[232,] 0.5 -0.060470602 0.0 0.5
[233,] -0.5 -0.398559958 -0.5 0.0
[234,] 0.5 0.467337635 0.5 0.0
[235,] 0.5 -1.392746641 0.0 0.0
[236,] 0.5 -0.574971549 0.5 0.0
[237,] -0.5 -1.580685214 0.0 0.0
[238,] -0.5 -2.163284201 -0.5 -0.5
[239,] 0.5 -0.996445962 0.5 0.0
[240,] -0.5 -0.899190625 0.0 -0.5
[241,] 0.5 -0.437118522 0.5 0.0
[242,] 0.5 -0.105382428 0.5 0.5
[243,] -0.5 -1.804511889 -0.5 0.0
[244,] -0.5 -0.488280357 0.0 0.0
[245,] 0.5 -0.464515359 0.5 0.5
[246,] -0.5 0.124134181 0.0 0.0
[247,] 0.5 -0.937715594 0.0 0.5
[248,] -0.5 -1.248771354 -0.5 -0.5
[249,] -0.5 -0.952285984 0.0 0.0
[250,] -0.5 -1.523423319 -0.5 -0.5
[251,] -0.5 -1.794795790 0.0 0.0
[252,] 0.5 0.073433786 0.5 0.0
[253,] -0.5 -2.102145316 -0.5 -0.5
[254,] -0.5 -1.288501443 0.0 -0.5
[255,] -0.5 -1.959683653 -0.5 -0.5
[256,] 0.5 0.520700805 0.5 0.5
[257,] 0.5 -0.460008458 0.0 0.0
[258,] 0.5 -0.079356588 0.5 0.5
[259,] -0.5 -1.048714229 0.0 0.0
[260,] -0.5 -1.458841030 -0.5 -0.5
[261,] 0.5 -0.956842088 0.5 0.0
[262,] 0.5 0.349936971 0.5 0.0
[263,] 0.5 -0.518553180 0.5 0.0
[264,] 0.5 -0.905791948 0.0 0.0
[265,] -0.5 -1.317383019 -0.5 -0.5
[266,] 0.5 1.457067973 0.0 0.5
[267,] -0.5 -0.940982277 -0.5 -0.5
[268,] -0.5 -0.731425752 -0.5 0.0
[269,] 0.5 0.734525225 0.5 0.0
[270,] 0.5 0.244582481 0.0 0.5
[271,] 0.5 1.761855099 0.0 0.0
[272,] -0.5 -2.003586112 -0.5 -0.5
[273,] -0.5 -1.925190311 -0.5 0.0
[274,] -0.5 -0.655830438 0.0 0.0
[275,] -0.5 -2.201055123 0.0 -0.5
[276,] 0.5 0.796725230 0.5 0.0
[277,] 0.5 0.585816081 0.5 0.0
[278,] 0.5 0.850381322 0.5 0.5
[279,] -0.5 -1.673968163 0.0 0.0
[280,] -0.5 -2.084435452 -0.5 -0.5
[281,] 0.5 -2.252752471 0.5 0.0
[282,] 0.5 0.189841633 0.0 0.0
[283,] -0.5 -1.086412241 -0.5 -0.5
[284,] -0.5 0.880658764 -0.5 -0.5
[285,] 0.5 0.156605219 0.0 0.5
[286,] 0.5 1.432897452 0.0 0.5
[287,] -0.5 -0.652616088 -0.5 0.0
[288,] 0.5 0.955011752 0.0 0.5
[289,] 0.5 -0.121845511 0.0 0.0
[290,] 0.5 -1.058962733 0.5 0.0
[291,] 0.5 -0.644207952 0.5 0.5
[292,] 0.5 -0.314107018 0.0 0.5
[293,] -0.5 -1.579609634 -0.5 0.0
[294,] 0.5 -0.884837579 0.5 0.5
[295,] 0.5 -0.556215739 0.0 0.0
[296,] 0.5 -0.634022836 0.5 0.0
[297,] 0.5 -1.491365202 0.5 0.5
[298,] 0.5 -0.504705282 0.5 0.5
[299,] 0.5 -1.816528016 0.5 0.0
[300,] 0.5 -0.878423822 0.0 0.5
[301,] 0.5 -0.493989033 0.0 0.0
[302,] 0.5 -0.254969856 0.5 0.5
[303,] -0.5 -2.113611455 0.0 -0.5
[304,] 0.5 -0.304066579 0.0 0.5
[305,] 0.5 1.084685787 0.5 0.5
[306,] 0.5 1.444776686 0.5 0.0
[307,] 0.5 -0.816059378 0.5 0.0
[308,] 0.5 -1.099262929 0.0 0.0
[309,] -0.5 -2.915949449 0.0 -0.5
[310,] -0.5 -1.174522765 0.0 -0.5
[311,] 0.5 -0.193379327 0.0 0.5
[312,] -0.5 -1.204846382 -0.5 0.0
[313,] 0.5 0.183004671 0.0 0.0
[314,] 0.5 -0.908745129 0.0 0.5
[315,] -0.5 -1.480883377 -0.5 -0.5
[316,] 0.5 -1.466434574 0.5 0.5
[317,] 0.5 -1.294353257 0.5 0.5
[318,] 0.5 0.687835292 0.5 0.5
[319,] 0.5 -1.289219824 0.0 0.0
[320,] 0.5 -0.589563228 0.5 0.0
[321,] 0.5 0.170770467 0.5 0.5
[322,] 0.5 0.088151201 0.5 0.0
[323,] -0.5 -1.180618702 -0.5 0.0
[324,] -0.5 0.231063202 0.0 -0.5
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[1817,] -0.5 -0.980821943 0.0 0.0
[1818,] -0.5 -0.980821943 0.0 0.0
[1819,] -0.5 -0.980821943 0.0 0.0
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[1821,] -0.5 -1.640181315 0.0 -0.5
[1822,] -0.5 -1.640181315 0.0 -0.5
[1823,] -0.5 -1.640181315 0.0 -0.5
[1824,] -0.5 -1.640181315 0.0 -0.5
[1825,] -0.5 -0.963668463 0.0 -0.5
[1826,] -0.5 -0.963668463 0.0 -0.5
[1827,] -0.5 -0.963668463 0.0 -0.5
[1828,] -0.5 -0.963668463 0.0 -0.5
[1829,] -0.5 -0.983159232 0.0 -0.5
[1830,] -0.5 -0.983159232 0.0 -0.5
[1831,] -0.5 -0.983159232 0.0 -0.5
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[1833,] 0.5 -0.093740304 0.0 0.5
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[1835,] 0.5 -0.093740304 0.0 0.5
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[1837,] -0.5 -1.216024952 0.0 -0.5
[1838,] -0.5 -1.216024952 0.0 -0.5
[1839,] -0.5 -1.216024952 0.0 -0.5
[1840,] -0.5 -1.216024952 0.0 -0.5
[1841,] 0.5 -0.474374930 0.0 0.5
[1842,] 0.5 -0.474374930 0.0 0.5
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[1845,] 0.5 -1.303274453 0.5 0.5
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[1848,] 0.5 -1.303274453 0.5 0.5
[1849,] -0.5 -1.689983499 -0.5 0.0
[1850,] -0.5 -1.689983499 -0.5 0.0
[1851,] -0.5 -1.689983499 -0.5 0.0
[1852,] -0.5 -1.689983499 -0.5 0.0
[1853,] 0.5 -1.236186375 0.0 0.5
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[1855,] 0.5 -1.236186375 0.0 0.5
[1856,] 0.5 -1.236186375 0.0 0.5
[1857,] -0.5 -1.803604377 -0.5 0.0
[1858,] -0.5 -1.803604377 -0.5 0.0
[1859,] -0.5 -1.803604377 -0.5 0.0
[1860,] -0.5 -1.803604377 -0.5 0.0
[1861,] 0.5 0.755122702 0.5 0.0
[1862,] 0.5 0.755122702 0.5 0.0
[1863,] 0.5 0.755122702 0.5 0.0
[1864,] 0.5 0.755122702 0.5 0.0
[1865,] 0.5 -2.289087302 0.5 0.0
[1866,] 0.5 -2.289087302 0.5 0.0
[1867,] 0.5 -2.289087302 0.5 0.0
[1868,] 0.5 -2.289087302 0.5 0.0
[1869,] -0.5 -0.974101874 -0.5 -0.5
[1870,] -0.5 -0.974101874 -0.5 -0.5
[1871,] -0.5 -0.974101874 -0.5 -0.5
[1872,] -0.5 -0.974101874 -0.5 -0.5
[1873,] 0.5 -0.716826992 0.5 0.0
[1874,] 0.5 -0.716826992 0.5 0.0
[1875,] 0.5 -0.716826992 0.5 0.0
[1876,] 0.5 -0.716826992 0.5 0.0
[1877,] 0.5 -0.536320658 0.0 0.5
[1878,] 0.5 -0.536320658 0.0 0.5
[1879,] 0.5 -0.536320658 0.0 0.5
[1880,] 0.5 -0.536320658 0.0 0.5
[1881,] -0.5 -0.129797291 0.0 -0.5
[1882,] -0.5 -0.129797291 0.0 -0.5
[1883,] -0.5 -0.129797291 0.0 -0.5
[1884,] -0.5 -0.129797291 0.0 -0.5
[1885,] 0.5 -0.188693179 0.5 0.5
[1886,] 0.5 -0.188693179 0.5 0.5
[1887,] 0.5 -0.188693179 0.5 0.5
[1888,] 0.5 -0.188693179 0.5 0.5
[1889,] -0.5 -1.791106247 0.0 -0.5
[1890,] -0.5 -1.791106247 0.0 -0.5
[1891,] -0.5 -1.791106247 0.0 -0.5
[1892,] -0.5 -1.791106247 0.0 -0.5
[1893,] -0.5 -2.588709378 -0.5 0.0
[1894,] -0.5 -2.588709378 -0.5 0.0
[1895,] -0.5 -2.588709378 -0.5 0.0
[1896,] -0.5 -2.588709378 -0.5 0.0
[1897,] -0.5 -1.543780468 -0.5 0.0
[1898,] -0.5 -1.543780468 -0.5 0.0
[1899,] -0.5 -1.543780468 -0.5 0.0
[1900,] -0.5 -1.543780468 -0.5 0.0
[1901,] -0.5 -0.845871477 0.0 0.0
[1902,] -0.5 -0.845871477 0.0 0.0
[1903,] -0.5 -0.845871477 0.0 0.0
[1904,] -0.5 -0.845871477 0.0 0.0
[1905,] -0.5 -2.525324072 -0.5 0.0
[1906,] -0.5 -2.525324072 -0.5 0.0
[1907,] -0.5 -2.525324072 -0.5 0.0
[1908,] -0.5 -2.525324072 -0.5 0.0
[1909,] -0.5 -0.981387593 -0.5 0.0
[1910,] -0.5 -0.981387593 -0.5 0.0
[1911,] -0.5 -0.981387593 -0.5 0.0
[1912,] -0.5 -0.981387593 -0.5 0.0
[1913,] -0.5 -0.882485577 0.0 0.0
[1914,] -0.5 -0.882485577 0.0 0.0
[1915,] -0.5 -0.882485577 0.0 0.0
[1916,] -0.5 -0.882485577 0.0 0.0
[1917,] 0.5 -1.414062060 0.0 0.5
[1918,] 0.5 -1.414062060 0.0 0.5
[1919,] 0.5 -1.414062060 0.0 0.5
[1920,] 0.5 -1.414062060 0.0 0.5
[1921,] 0.5 0.196100550 0.5 0.5
[1922,] 0.5 0.196100550 0.5 0.5
[1923,] 0.5 0.196100550 0.5 0.5
[1924,] 0.5 0.196100550 0.5 0.5
[1925,] -0.5 -0.793622360 -0.5 0.0
[1926,] -0.5 -0.793622360 -0.5 0.0
[1927,] -0.5 -0.793622360 -0.5 0.0
[1928,] -0.5 -0.793622360 -0.5 0.0
[1929,] 0.5 1.164949930 0.0 0.5
[1930,] 0.5 1.164949930 0.0 0.5
[1931,] 0.5 1.164949930 0.0 0.5
[1932,] 0.5 1.164949930 0.0 0.5
[1933,] -0.5 -1.731847770 -0.5 -0.5
[1934,] -0.5 -1.731847770 -0.5 -0.5
[1935,] -0.5 -1.731847770 -0.5 -0.5
[1936,] -0.5 -1.731847770 -0.5 -0.5
[1937,] -0.5 -1.536291302 -0.5 0.0
[1938,] -0.5 -1.536291302 -0.5 0.0
[1939,] -0.5 -1.536291302 -0.5 0.0
[1940,] -0.5 -1.536291302 -0.5 0.0
[1941,] -0.5 -1.022097158 -0.5 0.0
[1942,] -0.5 -1.022097158 -0.5 0.0
[1943,] -0.5 -1.022097158 -0.5 0.0
[1944,] -0.5 -1.022097158 -0.5 0.0
[1945,] -0.5 0.096985806 0.0 0.0
[1946,] -0.5 0.096985806 0.0 0.0
[1947,] -0.5 0.096985806 0.0 0.0
[1948,] -0.5 0.096985806 0.0 0.0
[1949,] -0.5 -0.066118458 -0.5 -0.5
[1950,] -0.5 -0.066118458 -0.5 -0.5
[1951,] -0.5 -0.066118458 -0.5 -0.5
[1952,] -0.5 -0.066118458 -0.5 -0.5
[1953,] -0.5 -1.615027843 0.0 0.0
[1954,] -0.5 -1.615027843 0.0 0.0
[1955,] -0.5 -1.615027843 0.0 0.0
[1956,] -0.5 -1.615027843 0.0 0.0
[1957,] 0.5 -2.076469515 0.0 0.5
[1958,] 0.5 -2.076469515 0.0 0.5
[1959,] 0.5 -2.076469515 0.0 0.5
[1960,] 0.5 -2.076469515 0.0 0.5
[1961,] -0.5 -1.809619913 -0.5 -0.5
[1962,] -0.5 -1.809619913 -0.5 -0.5
[1963,] -0.5 -1.809619913 -0.5 -0.5
[1964,] -0.5 -1.809619913 -0.5 -0.5
[1965,] -0.5 -1.343003867 0.0 0.0
[1966,] -0.5 -1.343003867 0.0 0.0
[1967,] -0.5 -1.343003867 0.0 0.0
[1968,] -0.5 -1.343003867 0.0 0.0
[1969,] 0.5 0.119009412 0.0 0.0
[1970,] 0.5 0.119009412 0.0 0.0
[1971,] 0.5 0.119009412 0.0 0.0
[1972,] 0.5 0.119009412 0.0 0.0
[1973,] 0.5 0.281073421 0.5 0.5
[1974,] 0.5 0.281073421 0.5 0.5
[1975,] 0.5 0.281073421 0.5 0.5
[1976,] 0.5 0.281073421 0.5 0.5
[1977,] 0.5 -1.235349552 0.0 0.5
[1978,] 0.5 -1.235349552 0.0 0.5
[1979,] 0.5 -1.235349552 0.0 0.5
[1980,] 0.5 -1.235349552 0.0 0.5
[1981,] -0.5 -2.332344561 -0.5 0.0
[1982,] -0.5 -2.332344561 -0.5 0.0
[1983,] -0.5 -2.332344561 -0.5 0.0
[1984,] -0.5 -2.332344561 -0.5 0.0
[1985,] 0.5 -1.762860801 0.5 0.5
[1986,] 0.5 -1.762860801 0.5 0.5
[1987,] 0.5 -1.762860801 0.5 0.5
[1988,] 0.5 -1.762860801 0.5 0.5
[1989,] -0.5 -0.527498165 -0.5 0.0
[1990,] -0.5 -0.527498165 -0.5 0.0
[1991,] -0.5 -0.527498165 -0.5 0.0
[1992,] -0.5 -0.527498165 -0.5 0.0
[1993,] 0.5 0.162255269 0.0 0.5
[1994,] 0.5 0.162255269 0.0 0.5
[1995,] 0.5 0.162255269 0.0 0.5
[1996,] 0.5 0.162255269 0.0 0.5
[1997,] 0.5 -1.108242265 0.0 0.5
[1998,] 0.5 -1.108242265 0.0 0.5
[1999,] 0.5 -1.108242265 0.0 0.5
[2000,] 0.5 -1.108242265 0.0 0.5
[2001,] 0.5 -1.183580711 0.0 0.0
[2002,] 0.5 -1.183580711 0.0 0.0
[2003,] 0.5 -1.183580711 0.0 0.0
[2004,] 0.5 -1.183580711 0.0 0.0
[2005,] -0.5 -0.574506979 -0.5 -0.5
[2006,] -0.5 -0.574506979 -0.5 -0.5
[2007,] -0.5 -0.574506979 -0.5 -0.5
[2008,] -0.5 -0.574506979 -0.5 -0.5
[2009,] -0.5 -0.552101557 0.0 0.0
[2010,] -0.5 -0.552101557 0.0 0.0
[2011,] -0.5 -0.552101557 0.0 0.0
[2012,] -0.5 -0.552101557 0.0 0.0
[2013,] 0.5 -1.937590449 0.0 0.5
[2014,] 0.5 -1.937590449 0.0 0.5
[2015,] 0.5 -1.937590449 0.0 0.5
[2016,] 0.5 -1.937590449 0.0 0.5
[2017,] 0.5 -0.642074790 0.0 0.0
[2018,] 0.5 -0.642074790 0.0 0.0
[2019,] 0.5 -0.642074790 0.0 0.0
[2020,] 0.5 -0.642074790 0.0 0.0
[2021,] -0.5 -1.116122563 -0.5 -0.5
[2022,] -0.5 -1.116122563 -0.5 -0.5
[2023,] -0.5 -1.116122563 -0.5 -0.5
[2024,] -0.5 -1.116122563 -0.5 -0.5
[2025,] 0.5 -1.010519741 0.0 0.0
[2026,] 0.5 -1.010519741 0.0 0.0
[2027,] 0.5 -1.010519741 0.0 0.0
[2028,] 0.5 -1.010519741 0.0 0.0
[2029,] 0.5 0.570182462 0.5 0.0
[2030,] 0.5 0.570182462 0.5 0.0
[2031,] 0.5 0.570182462 0.5 0.0
[2032,] 0.5 0.570182462 0.5 0.0
[2033,] 0.5 -0.047055124 0.0 0.0
[2034,] 0.5 -0.047055124 0.0 0.0
[2035,] 0.5 -0.047055124 0.0 0.0
[2036,] 0.5 -0.047055124 0.0 0.0
[2037,] 0.5 2.145147973 0.5 0.5
[2038,] 0.5 2.145147973 0.5 0.5
[2039,] 0.5 2.145147973 0.5 0.5
[2040,] 0.5 2.145147973 0.5 0.5
[2041,] -0.5 -0.814304394 -0.5 0.0
[2042,] -0.5 -0.814304394 -0.5 0.0
[2043,] -0.5 -0.814304394 -0.5 0.0
[2044,] -0.5 -0.814304394 -0.5 0.0
[2045,] 0.5 0.728328560 0.0 0.0
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[2047,] 0.5 0.728328560 0.0 0.0
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[2049,] 0.5 0.947683535 0.5 0.5
[2050,] 0.5 0.947683535 0.5 0.5
[2051,] 0.5 0.947683535 0.5 0.5
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[2053,] -0.5 -1.334702786 -0.5 0.0
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[2055,] -0.5 -1.334702786 -0.5 0.0
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[2057,] 0.5 1.211531117 0.5 0.0
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[2059,] 0.5 1.211531117 0.5 0.0
[2060,] 0.5 1.211531117 0.5 0.0
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[2157,] -0.5 -1.108149325 -0.5 -0.5
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[2163,] 0.5 0.268772260 0.5 0.5
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[3893,] 0.5 0.025270538 0.0 0.5
[3894,] 0.5 0.025270538 0.0 0.5
[3895,] 0.5 0.025270538 0.0 0.5
[3896,] 0.5 0.025270538 0.0 0.5
[3897,] 0.5 -0.805552807 0.0 0.0
[3898,] 0.5 -0.805552807 0.0 0.0
[3899,] 0.5 -0.805552807 0.0 0.0
[3900,] 0.5 -0.805552807 0.0 0.0
[3901,] 0.5 -0.744156066 0.5 0.0
[3902,] 0.5 -0.744156066 0.5 0.0
[3903,] 0.5 -0.744156066 0.5 0.0
[3904,] 0.5 -0.744156066 0.5 0.0
[3905,] 0.5 -0.712681140 0.5 0.5
[3906,] 0.5 -0.712681140 0.5 0.5
[3907,] 0.5 -0.712681140 0.5 0.5
[3908,] 0.5 -0.712681140 0.5 0.5
[3909,] -0.5 -0.813210235 0.0 0.0
[3910,] -0.5 -0.813210235 0.0 0.0
[3911,] -0.5 -0.813210235 0.0 0.0
[3912,] -0.5 -0.813210235 0.0 0.0
[3913,] -0.5 -0.358889006 -0.5 -0.5
[3914,] -0.5 -0.358889006 -0.5 -0.5
[3915,] -0.5 -0.358889006 -0.5 -0.5
[3916,] -0.5 -0.358889006 -0.5 -0.5
[3917,] 0.5 0.142958676 0.0 0.5
[3918,] 0.5 0.142958676 0.0 0.5
[3919,] 0.5 0.142958676 0.0 0.5
[3920,] 0.5 0.142958676 0.0 0.5
[3921,] 0.5 3.228934684 0.0 0.5
[3922,] 0.5 3.228934684 0.0 0.5
[3923,] 0.5 3.228934684 0.0 0.5
[3924,] 0.5 3.228934684 0.0 0.5
[3925,] 0.5 0.168244381 0.0 0.5
[3926,] 0.5 0.168244381 0.0 0.5
[3927,] 0.5 0.168244381 0.0 0.5
[3928,] 0.5 0.168244381 0.0 0.5
[3929,] 0.5 -0.825500733 0.0 0.5
[3930,] 0.5 -0.825500733 0.0 0.5
[3931,] 0.5 -0.825500733 0.0 0.5
[3932,] 0.5 -0.825500733 0.0 0.5
[3933,] 0.5 -0.416807302 0.5 0.5
[3934,] 0.5 -0.416807302 0.5 0.5
[3935,] 0.5 -0.416807302 0.5 0.5
[3936,] 0.5 -0.416807302 0.5 0.5
[3937,] -0.5 -1.030265174 -0.5 0.0
[3938,] -0.5 -1.030265174 -0.5 0.0
[3939,] -0.5 -1.030265174 -0.5 0.0
[3940,] -0.5 -1.030265174 -0.5 0.0
[3941,] 0.5 -0.424412535 0.5 0.5
[3942,] 0.5 -0.424412535 0.5 0.5
[3943,] 0.5 -0.424412535 0.5 0.5
[3944,] 0.5 -0.424412535 0.5 0.5
[3945,] -0.5 -1.395126210 0.0 -0.5
[3946,] -0.5 -1.395126210 0.0 -0.5
[3947,] -0.5 -1.395126210 0.0 -0.5
[3948,] -0.5 -1.395126210 0.0 -0.5
[3949,] 0.5 -0.631934113 0.5 0.5
[3950,] 0.5 -0.631934113 0.5 0.5
[3951,] 0.5 -0.631934113 0.5 0.5
[3952,] 0.5 -0.631934113 0.5 0.5
[3953,] 0.5 -0.956021421 0.5 0.0
[3954,] 0.5 -0.956021421 0.5 0.0
[3955,] 0.5 -0.956021421 0.5 0.0
[3956,] 0.5 -0.956021421 0.5 0.0
[3957,] 0.5 -0.709418081 0.0 0.0
[3958,] 0.5 -0.709418081 0.0 0.0
[3959,] 0.5 -0.709418081 0.0 0.0
[3960,] 0.5 -0.709418081 0.0 0.0
[3961,] -0.5 -1.561898145 0.0 -0.5
[3962,] -0.5 -1.561898145 0.0 -0.5
[3963,] -0.5 -1.561898145 0.0 -0.5
[3964,] -0.5 -1.561898145 0.0 -0.5
[3965,] -0.5 -1.959899975 -0.5 -0.5
[3966,] -0.5 -1.959899975 -0.5 -0.5
[3967,] -0.5 -1.959899975 -0.5 -0.5
[3968,] -0.5 -1.959899975 -0.5 -0.5
[3969,] -0.5 -1.679251217 0.0 0.0
[3970,] -0.5 -1.679251217 0.0 0.0
[3971,] -0.5 -1.679251217 0.0 0.0
[3972,] -0.5 -1.679251217 0.0 0.0
[3973,] 0.5 -1.022079328 0.5 0.5
[3974,] 0.5 -1.022079328 0.5 0.5
[3975,] 0.5 -1.022079328 0.5 0.5
[3976,] 0.5 -1.022079328 0.5 0.5
[3977,] 0.5 -0.476246093 0.5 0.5
[3978,] 0.5 -0.476246093 0.5 0.5
[3979,] 0.5 -0.476246093 0.5 0.5
[3980,] 0.5 -0.476246093 0.5 0.5
[3981,] 0.5 0.227252590 0.5 0.5
[3982,] 0.5 0.227252590 0.5 0.5
[3983,] 0.5 0.227252590 0.5 0.5
[3984,] 0.5 0.227252590 0.5 0.5
[3985,] 0.5 -1.225519331 0.0 0.0
[3986,] 0.5 -1.225519331 0.0 0.0
[3987,] 0.5 -1.225519331 0.0 0.0
[3988,] 0.5 -1.225519331 0.0 0.0
[3989,] -0.5 -1.475767060 0.0 0.0
[3990,] -0.5 -1.475767060 0.0 0.0
[3991,] -0.5 -1.475767060 0.0 0.0
[3992,] -0.5 -1.475767060 0.0 0.0
[3993,] -0.5 -1.862087333 0.0 0.0
[3994,] -0.5 -1.862087333 0.0 0.0
[3995,] -0.5 -1.862087333 0.0 0.0
[3996,] -0.5 -1.862087333 0.0 0.0
[3997,] -0.5 -1.686905342 -0.5 0.0
[3998,] -0.5 -1.686905342 -0.5 0.0
[3999,] -0.5 -1.686905342 -0.5 0.0
[4000,] -0.5 -1.686905342 -0.5 0.0
augSIMEX documentation built on April 23, 2020, 5:08 p.m.
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
This function can be used to calculate the value of score function. This function can serve as a tool to assist the users in debugging their self-defined score function.
Usage
1 |
Arguments
beta |
a vector specifying the value of parameters. |
Y |
a vector specifying the response. |
data |
a matrix or data frame of covariates. If this is for score function debugging purpose, see detail for the rearrangement of the dataset. |
weight |
a vector of weight. |
offset |
a vector of offset. |
family |
a |
Details
In a general setting, Y can be treated as a response and data as covariates.
This function helps to debug the user specified score function. The data are needed to be specially arranged such that the score function output can be successfully passed into augSIMEX function in a correct order. The data should be a matrix or data frame of a combination with error-prone covariates (in the order of err.var as in augSIMEX), other covariates and binary variable that is prone to misclassification. The intercept, if considered, should be included the category of “other covariates”.
Value
A matrix of n times m, where n is the number of observations and m is the number of parameters. Each entry in the matrix represents the calculated score value for subject i on parameter j. The vector of row sum will be the score value vector.
Author(s)
Qihuang Zhang and Grace Y. Yi.
References
McCullagh P. Generalized linear models[J]. European Journal of Operational Research, 1984, 16(3): 285-292.
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ### The user specified function to be checked. (logit link in binomial family)
scorefunction=function(beta,Y,data,weight,offset){
results<-lapply(1:dim(data)[2],
FUN=function(i){
S<-lapply(1:dim(data)[1],function(x){
eta<- matrix(beta,nrow=1)
return(weight[x]*Y[x]*data[x,i]-weight[x]*exp(eta)/(1+exp(eta))*data[x,i])})
return(S)}
)
return(matrix(unlist(results),ncol=dim(data)[2]))
}
data(ToyUni)
### Data need to rearranged. See detail.
nsize<-length(ToyUni$Main[,"Y"])
data.in.score<-data.frame(intercept=1,X=ToyUni$Main[,"Xstar"],
W=ToyUni$Main[,"W"],Z=ToyUni$Main[,"Zstar"])
## compare. The results should be identical.
glmscore(rep(0,4),ToyUni$Main[,"Y"],data.in.score,rep(1,nsize),
rep(0,nsize),family=binomial(link=logit))
scorefunction(rep(0,4),ToyUni$Main[,"Y"],data.in.score,rep(1,nsize),rep(0,nsize))
|
Example output
[,1] [,2] [,3] [,4]
[1,] 0.5 1.512671100 0.0 0.0
[2,] 0.5 -1.308160599 0.0 0.0
[3,] 0.5 0.976864185 0.5 0.5
[4,] -0.5 -0.716462534 -0.5 0.0
[5,] -0.5 -1.312486545 -0.5 -0.5
[6,] 0.5 -0.856213441 0.5 0.5
[7,] -0.5 -0.900267789 0.0 0.0
[8,] 0.5 -0.989180711 0.0 0.0
[9,] -0.5 -1.597225204 0.0 -0.5
[10,] 0.5 -1.313330990 0.5 0.0
[11,] -0.5 -1.835406721 -0.5 0.0
[12,] 0.5 -0.451210392 0.5 0.5
[13,] 0.5 -1.397192919 0.0 0.5
[14,] -0.5 -2.014523049 0.0 -0.5
[15,] 0.5 0.227403726 0.5 0.0
[16,] 0.5 -0.991263236 0.0 0.0
[17,] -0.5 -2.113179843 -0.5 -0.5
[18,] -0.5 -1.298308056 0.0 0.0
[19,] -0.5 0.362132412 0.0 0.0
[20,] -0.5 -1.421596001 -0.5 0.0
[21,] 0.5 1.350782227 0.5 0.5
[22,] -0.5 -0.446276735 0.0 0.0
[23,] -0.5 -0.629196736 -0.5 0.0
[24,] 0.5 0.230996034 0.0 0.0
[25,] 0.5 -1.820003918 0.5 0.5
[26,] 0.5 0.489025506 0.5 0.5
[27,] -0.5 -0.777998406 0.0 -0.5
[28,] 0.5 -1.232841916 0.0 0.5
[29,] -0.5 -2.035855036 0.0 -0.5
[30,] -0.5 -1.057268679 0.0 0.0
[31,] 0.5 -0.680822766 0.5 0.5
[32,] 0.5 -1.185730073 0.0 0.0
[33,] 0.5 1.125394845 0.0 0.5
[34,] -0.5 -0.707193613 0.0 0.0
[35,] 0.5 -0.308891461 0.0 0.0
[36,] -0.5 -1.180977370 0.0 -0.5
[37,] -0.5 -1.321708394 0.0 0.0
[38,] 0.5 -0.041669167 0.0 0.0
[39,] -0.5 -0.067369120 -0.5 0.0
[40,] 0.5 0.571101125 0.0 0.0
[41,] -0.5 -0.630090534 0.0 -0.5
[42,] 0.5 -1.284909200 0.5 0.5
[43,] 0.5 -0.588519290 0.5 0.5
[44,] 0.5 0.007801140 0.5 0.0
[45,] 0.5 0.075563407 0.0 0.5
[46,] 0.5 -0.612740118 0.0 0.5
[47,] 0.5 0.188242050 0.5 0.0
[48,] 0.5 -1.661288678 0.0 0.5
[49,] 0.5 -1.459654290 0.0 0.5
[50,] -0.5 -0.563279555 0.0 -0.5
[51,] -0.5 -1.797834838 -0.5 0.0
[52,] 0.5 0.030781369 0.0 0.5
[53,] -0.5 -0.178489841 0.0 0.0
[54,] 0.5 -1.904248730 0.0 0.0
[55,] 0.5 0.282446236 0.5 0.0
[56,] 0.5 -0.768001441 0.5 0.5
[57,] 0.5 -0.608985228 0.5 0.0
[58,] -0.5 -0.847188683 0.0 0.0
[59,] 0.5 -0.530786987 0.0 0.0
[60,] 0.5 0.463576854 0.5 0.5
[61,] -0.5 -1.226204463 0.0 0.0
[62,] -0.5 -1.660871539 0.0 0.0
[63,] -0.5 -0.980314283 0.0 0.0
[64,] 0.5 0.182096704 0.0 0.0
[65,] 0.5 0.915053100 0.5 0.5
[66,] -0.5 -1.808344723 0.0 0.0
[67,] 0.5 0.228853740 0.5 0.5
[68,] 0.5 0.150196770 0.5 0.0
[69,] -0.5 -1.467012912 0.0 0.0
[70,] 0.5 1.307313826 0.5 0.0
[71,] 0.5 -0.823600027 0.5 0.0
[72,] -0.5 1.126328323 -0.5 -0.5
[73,] 0.5 -1.116248718 0.5 0.0
[74,] 0.5 -0.945288123 0.0 0.0
[75,] 0.5 0.027397902 0.0 0.0
[76,] 0.5 -0.387963705 0.0 0.0
[77,] 0.5 0.180259388 0.0 0.0
[78,] 0.5 -0.962677089 0.5 0.5
[79,] 0.5 0.412441987 0.0 0.5
[80,] -0.5 -0.945959995 -0.5 -0.5
[81,] -0.5 -0.335040243 -0.5 0.0
[82,] 0.5 -1.041484079 0.5 0.0
[83,] -0.5 -1.410524988 0.0 0.0
[84,] 0.5 0.428679360 0.5 0.0
[85,] -0.5 -1.497908628 0.0 -0.5
[86,] 0.5 -0.279029630 0.5 0.0
[87,] -0.5 -1.130470597 -0.5 -0.5
[88,] 0.5 -2.749602068 0.0 0.0
[89,] -0.5 -1.575500271 0.0 -0.5
[90,] 0.5 -1.270883378 0.5 0.0
[91,] 0.5 0.524758979 0.5 0.5
[92,] -0.5 0.931464489 0.0 0.0
[93,] -0.5 -0.528800132 0.0 -0.5
[94,] 0.5 0.007294486 0.0 0.5
[95,] -0.5 -1.458259974 -0.5 0.0
[96,] 0.5 -0.565536010 0.5 0.5
[97,] -0.5 -0.565717765 -0.5 -0.5
[98,] -0.5 0.020759372 0.0 -0.5
[99,] -0.5 -0.994009173 -0.5 0.0
[100,] 0.5 0.083115004 0.5 0.0
[101,] 0.5 -1.746123866 0.5 0.5
[102,] 0.5 -0.441969943 0.0 0.0
[103,] 0.5 -0.910880738 0.0 0.0
[104,] 0.5 0.192680286 0.5 0.5
[105,] -0.5 2.363180032 0.0 0.0
[106,] 0.5 0.677621918 0.5 0.0
[107,] -0.5 -0.711225917 -0.5 -0.5
[108,] 0.5 -0.755660223 0.0 0.5
[109,] -0.5 0.696788728 -0.5 -0.5
[110,] -0.5 -1.156830550 -0.5 0.0
[111,] 0.5 -1.811309486 0.0 0.5
[112,] 0.5 -0.116596436 0.5 0.5
[113,] 0.5 -1.248319057 0.5 0.0
[114,] 0.5 -0.192447592 0.0 0.5
[115,] -0.5 -1.519770375 -0.5 -0.5
[116,] 0.5 0.074572814 0.5 0.5
[117,] 0.5 0.414035904 0.0 0.5
[118,] 0.5 -1.209303741 0.5 0.0
[119,] -0.5 -1.784689220 -0.5 0.0
[120,] 0.5 -1.699394004 0.0 0.5
[121,] -0.5 -1.263785633 -0.5 0.0
[122,] -0.5 -0.900490198 0.0 0.0
[123,] 0.5 -0.660905661 0.0 0.5
[124,] 0.5 0.384100109 0.5 0.0
[125,] 0.5 0.028344858 0.0 0.0
[126,] -0.5 0.078830903 0.0 -0.5
[127,] 0.5 -0.206411427 0.5 0.5
[128,] -0.5 -0.560459078 -0.5 -0.5
[129,] -0.5 -1.910202287 -0.5 0.0
[130,] -0.5 -1.457932604 -0.5 0.0
[131,] -0.5 -1.394943754 -0.5 0.0
[132,] 0.5 -1.723529970 0.0 0.5
[133,] 0.5 -0.999966369 0.5 0.0
[134,] 0.5 -1.490231999 0.0 0.0
[135,] 0.5 0.072378657 0.0 0.5
[136,] -0.5 0.030523876 0.0 0.0
[137,] -0.5 -1.327227884 0.0 0.0
[138,] -0.5 -0.385999586 0.0 -0.5
[139,] 0.5 1.648602228 0.5 0.5
[140,] -0.5 -2.776902681 -0.5 0.0
[141,] 0.5 -2.462703197 0.0 0.5
[142,] 0.5 0.263770028 0.5 0.5
[143,] -0.5 0.182434252 0.0 0.0
[144,] 0.5 -0.874095742 0.5 0.0
[145,] 0.5 -0.380779821 0.0 0.0
[146,] -0.5 -0.022061881 0.0 -0.5
[147,] 0.5 -2.275354230 0.0 0.0
[148,] -0.5 1.173527076 0.0 0.0
[149,] 0.5 1.470870496 0.0 0.0
[150,] 0.5 -0.112396529 0.0 0.0
[151,] 0.5 -0.244804468 0.5 0.0
[152,] 0.5 -0.013683593 0.0 0.0
[153,] 0.5 -0.627270375 0.5 0.5
[154,] -0.5 -1.705678651 0.0 0.0
[155,] 0.5 -1.030522625 0.0 0.5
[156,] -0.5 -1.629168586 -0.5 0.0
[157,] -0.5 -1.449039264 -0.5 0.0
[158,] 0.5 0.720090350 0.0 0.5
[159,] 0.5 0.180033689 0.5 0.0
[160,] 0.5 -1.047505475 0.0 0.0
[161,] -0.5 0.189845403 0.0 0.0
[162,] 0.5 -0.608448803 0.0 0.0
[163,] 0.5 1.028962277 0.0 0.0
[164,] 0.5 -0.220731538 0.5 0.0
[165,] -0.5 -0.132302144 -0.5 -0.5
[166,] 0.5 -1.696947248 0.0 0.0
[167,] -0.5 -1.335002668 0.0 0.0
[168,] 0.5 -1.335245761 0.5 0.0
[169,] -0.5 -0.814223139 0.0 0.0
[170,] -0.5 0.571722347 0.0 0.0
[171,] -0.5 -0.088795585 -0.5 0.0
[172,] 0.5 -0.316410233 0.0 0.5
[173,] 0.5 -1.153262282 0.0 0.5
[174,] 0.5 -0.363609022 0.5 0.5
[175,] -0.5 -1.970937663 -0.5 0.0
[176,] 0.5 2.276406292 0.0 0.0
[177,] -0.5 -0.509177597 0.0 -0.5
[178,] -0.5 -1.316627802 -0.5 0.0
[179,] -0.5 -0.958434816 0.0 0.0
[180,] 0.5 -2.465025995 0.0 0.5
[181,] 0.5 -0.026557125 0.0 0.0
[182,] 0.5 -0.324067994 0.0 0.5
[183,] 0.5 -0.111427760 0.0 0.0
[184,] 0.5 -1.808780820 0.0 0.0
[185,] -0.5 -2.400446853 0.0 0.0
[186,] 0.5 -0.716597448 0.5 0.0
[187,] -0.5 -0.643948176 0.0 -0.5
[188,] 0.5 -1.477066033 0.0 0.5
[189,] -0.5 -2.461151175 0.0 -0.5
[190,] 0.5 -1.255469960 0.0 0.0
[191,] -0.5 -0.619512468 -0.5 -0.5
[192,] 0.5 -0.826937551 0.0 0.5
[193,] 0.5 -0.339641997 0.0 0.0
[194,] -0.5 -1.486893621 -0.5 0.0
[195,] -0.5 -1.482252086 0.0 -0.5
[196,] -0.5 -0.717794471 0.0 0.0
[197,] -0.5 -0.597231469 -0.5 -0.5
[198,] 0.5 -0.010449902 0.0 0.0
[199,] -0.5 -0.350852331 -0.5 -0.5
[200,] 0.5 0.503196173 0.0 0.5
[201,] -0.5 -2.514963793 -0.5 -0.5
[202,] -0.5 -2.299804994 0.0 0.0
[203,] -0.5 -1.277761983 0.0 0.0
[204,] 0.5 0.192592018 0.0 0.5
[205,] 0.5 0.163675807 0.0 0.0
[206,] -0.5 -0.886201541 -0.5 0.0
[207,] 0.5 -0.119900852 0.5 0.0
[208,] 0.5 0.227738425 0.5 0.0
[209,] 0.5 0.931078781 0.5 0.0
[210,] -0.5 0.132259132 -0.5 0.0
[211,] 0.5 -0.510211778 0.5 0.5
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[1891,] -0.5 -1.791106247 0.0 -0.5
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[1893,] -0.5 -2.588709378 -0.5 0.0
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[1895,] -0.5 -2.588709378 -0.5 0.0
[1896,] -0.5 -2.588709378 -0.5 0.0
[1897,] -0.5 -1.543780468 -0.5 0.0
[1898,] -0.5 -1.543780468 -0.5 0.0
[1899,] -0.5 -1.543780468 -0.5 0.0
[1900,] -0.5 -1.543780468 -0.5 0.0
[1901,] -0.5 -0.845871477 0.0 0.0
[1902,] -0.5 -0.845871477 0.0 0.0
[1903,] -0.5 -0.845871477 0.0 0.0
[1904,] -0.5 -0.845871477 0.0 0.0
[1905,] -0.5 -2.525324072 -0.5 0.0
[1906,] -0.5 -2.525324072 -0.5 0.0
[1907,] -0.5 -2.525324072 -0.5 0.0
[1908,] -0.5 -2.525324072 -0.5 0.0
[1909,] -0.5 -0.981387593 -0.5 0.0
[1910,] -0.5 -0.981387593 -0.5 0.0
[1911,] -0.5 -0.981387593 -0.5 0.0
[1912,] -0.5 -0.981387593 -0.5 0.0
[1913,] -0.5 -0.882485577 0.0 0.0
[1914,] -0.5 -0.882485577 0.0 0.0
[1915,] -0.5 -0.882485577 0.0 0.0
[1916,] -0.5 -0.882485577 0.0 0.0
[1917,] 0.5 -1.414062060 0.0 0.5
[1918,] 0.5 -1.414062060 0.0 0.5
[1919,] 0.5 -1.414062060 0.0 0.5
[1920,] 0.5 -1.414062060 0.0 0.5
[1921,] 0.5 0.196100550 0.5 0.5
[1922,] 0.5 0.196100550 0.5 0.5
[1923,] 0.5 0.196100550 0.5 0.5
[1924,] 0.5 0.196100550 0.5 0.5
[1925,] -0.5 -0.793622360 -0.5 0.0
[1926,] -0.5 -0.793622360 -0.5 0.0
[1927,] -0.5 -0.793622360 -0.5 0.0
[1928,] -0.5 -0.793622360 -0.5 0.0
[1929,] 0.5 1.164949930 0.0 0.5
[1930,] 0.5 1.164949930 0.0 0.5
[1931,] 0.5 1.164949930 0.0 0.5
[1932,] 0.5 1.164949930 0.0 0.5
[1933,] -0.5 -1.731847770 -0.5 -0.5
[1934,] -0.5 -1.731847770 -0.5 -0.5
[1935,] -0.5 -1.731847770 -0.5 -0.5
[1936,] -0.5 -1.731847770 -0.5 -0.5
[1937,] -0.5 -1.536291302 -0.5 0.0
[1938,] -0.5 -1.536291302 -0.5 0.0
[1939,] -0.5 -1.536291302 -0.5 0.0
[1940,] -0.5 -1.536291302 -0.5 0.0
[1941,] -0.5 -1.022097158 -0.5 0.0
[1942,] -0.5 -1.022097158 -0.5 0.0
[1943,] -0.5 -1.022097158 -0.5 0.0
[1944,] -0.5 -1.022097158 -0.5 0.0
[1945,] -0.5 0.096985806 0.0 0.0
[1946,] -0.5 0.096985806 0.0 0.0
[1947,] -0.5 0.096985806 0.0 0.0
[1948,] -0.5 0.096985806 0.0 0.0
[1949,] -0.5 -0.066118458 -0.5 -0.5
[1950,] -0.5 -0.066118458 -0.5 -0.5
[1951,] -0.5 -0.066118458 -0.5 -0.5
[1952,] -0.5 -0.066118458 -0.5 -0.5
[1953,] -0.5 -1.615027843 0.0 0.0
[1954,] -0.5 -1.615027843 0.0 0.0
[1955,] -0.5 -1.615027843 0.0 0.0
[1956,] -0.5 -1.615027843 0.0 0.0
[1957,] 0.5 -2.076469515 0.0 0.5
[1958,] 0.5 -2.076469515 0.0 0.5
[1959,] 0.5 -2.076469515 0.0 0.5
[1960,] 0.5 -2.076469515 0.0 0.5
[1961,] -0.5 -1.809619913 -0.5 -0.5
[1962,] -0.5 -1.809619913 -0.5 -0.5
[1963,] -0.5 -1.809619913 -0.5 -0.5
[1964,] -0.5 -1.809619913 -0.5 -0.5
[1965,] -0.5 -1.343003867 0.0 0.0
[1966,] -0.5 -1.343003867 0.0 0.0
[1967,] -0.5 -1.343003867 0.0 0.0
[1968,] -0.5 -1.343003867 0.0 0.0
[1969,] 0.5 0.119009412 0.0 0.0
[1970,] 0.5 0.119009412 0.0 0.0
[1971,] 0.5 0.119009412 0.0 0.0
[1972,] 0.5 0.119009412 0.0 0.0
[1973,] 0.5 0.281073421 0.5 0.5
[1974,] 0.5 0.281073421 0.5 0.5
[1975,] 0.5 0.281073421 0.5 0.5
[1976,] 0.5 0.281073421 0.5 0.5
[1977,] 0.5 -1.235349552 0.0 0.5
[1978,] 0.5 -1.235349552 0.0 0.5
[1979,] 0.5 -1.235349552 0.0 0.5
[1980,] 0.5 -1.235349552 0.0 0.5
[1981,] -0.5 -2.332344561 -0.5 0.0
[1982,] -0.5 -2.332344561 -0.5 0.0
[1983,] -0.5 -2.332344561 -0.5 0.0
[1984,] -0.5 -2.332344561 -0.5 0.0
[1985,] 0.5 -1.762860801 0.5 0.5
[1986,] 0.5 -1.762860801 0.5 0.5
[1987,] 0.5 -1.762860801 0.5 0.5
[1988,] 0.5 -1.762860801 0.5 0.5
[1989,] -0.5 -0.527498165 -0.5 0.0
[1990,] -0.5 -0.527498165 -0.5 0.0
[1991,] -0.5 -0.527498165 -0.5 0.0
[1992,] -0.5 -0.527498165 -0.5 0.0
[1993,] 0.5 0.162255269 0.0 0.5
[1994,] 0.5 0.162255269 0.0 0.5
[1995,] 0.5 0.162255269 0.0 0.5
[1996,] 0.5 0.162255269 0.0 0.5
[1997,] 0.5 -1.108242265 0.0 0.5
[1998,] 0.5 -1.108242265 0.0 0.5
[1999,] 0.5 -1.108242265 0.0 0.5
[2000,] 0.5 -1.108242265 0.0 0.5
[2001,] 0.5 -1.183580711 0.0 0.0
[2002,] 0.5 -1.183580711 0.0 0.0
[2003,] 0.5 -1.183580711 0.0 0.0
[2004,] 0.5 -1.183580711 0.0 0.0
[2005,] -0.5 -0.574506979 -0.5 -0.5
[2006,] -0.5 -0.574506979 -0.5 -0.5
[2007,] -0.5 -0.574506979 -0.5 -0.5
[2008,] -0.5 -0.574506979 -0.5 -0.5
[2009,] -0.5 -0.552101557 0.0 0.0
[2010,] -0.5 -0.552101557 0.0 0.0
[2011,] -0.5 -0.552101557 0.0 0.0
[2012,] -0.5 -0.552101557 0.0 0.0
[2013,] 0.5 -1.937590449 0.0 0.5
[2014,] 0.5 -1.937590449 0.0 0.5
[2015,] 0.5 -1.937590449 0.0 0.5
[2016,] 0.5 -1.937590449 0.0 0.5
[2017,] 0.5 -0.642074790 0.0 0.0
[2018,] 0.5 -0.642074790 0.0 0.0
[2019,] 0.5 -0.642074790 0.0 0.0
[2020,] 0.5 -0.642074790 0.0 0.0
[2021,] -0.5 -1.116122563 -0.5 -0.5
[2022,] -0.5 -1.116122563 -0.5 -0.5
[2023,] -0.5 -1.116122563 -0.5 -0.5
[2024,] -0.5 -1.116122563 -0.5 -0.5
[2025,] 0.5 -1.010519741 0.0 0.0
[2026,] 0.5 -1.010519741 0.0 0.0
[2027,] 0.5 -1.010519741 0.0 0.0
[2028,] 0.5 -1.010519741 0.0 0.0
[2029,] 0.5 0.570182462 0.5 0.0
[2030,] 0.5 0.570182462 0.5 0.0
[2031,] 0.5 0.570182462 0.5 0.0
[2032,] 0.5 0.570182462 0.5 0.0
[2033,] 0.5 -0.047055124 0.0 0.0
[2034,] 0.5 -0.047055124 0.0 0.0
[2035,] 0.5 -0.047055124 0.0 0.0
[2036,] 0.5 -0.047055124 0.0 0.0
[2037,] 0.5 2.145147973 0.5 0.5
[2038,] 0.5 2.145147973 0.5 0.5
[2039,] 0.5 2.145147973 0.5 0.5
[2040,] 0.5 2.145147973 0.5 0.5
[2041,] -0.5 -0.814304394 -0.5 0.0
[2042,] -0.5 -0.814304394 -0.5 0.0
[2043,] -0.5 -0.814304394 -0.5 0.0
[2044,] -0.5 -0.814304394 -0.5 0.0
[2045,] 0.5 0.728328560 0.0 0.0
[2046,] 0.5 0.728328560 0.0 0.0
[2047,] 0.5 0.728328560 0.0 0.0
[2048,] 0.5 0.728328560 0.0 0.0
[2049,] 0.5 0.947683535 0.5 0.5
[2050,] 0.5 0.947683535 0.5 0.5
[2051,] 0.5 0.947683535 0.5 0.5
[2052,] 0.5 0.947683535 0.5 0.5
[2053,] -0.5 -1.334702786 -0.5 0.0
[2054,] -0.5 -1.334702786 -0.5 0.0
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