installingpackages.R

datos = read.table("/home/liberato/3PL/LMay/Test_10_1_1000.csv",sep=" ",header=T);
1030000-5000-325000-5000-11000-50000-20000-20000+60000-2000-10000-5500-10000-2000
cuads
install.packages("mirt")
remove.packages("IRTpp")
install.packages("/home/liberato/git/rmongodbHelper_0.0.0.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/Downloads//rjson_0.2.15.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/Downloads//rmongodb_1.8.0.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/git/IRTpp_1.0.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/git/lineprof_0.1.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/Downloads/shiny_0.12.1.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/Downloads/httpuv_1.3.2.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/Downloads/xtable_1.7-4.tar.gz", repos=NULL, type = "source")
install.packages("/home/liberato/knitr_1.10.5.tar.gz", repos=NULL, type = "source")
library(IRTpp)
?IRTpp
library(Rcpp)
setwd("/home/liberato/git/IRTpp/")
compileAttributes()

library(roxygen2)
library(IRTpp)
roxygenise()
cuads
irtpp()
ls("package:IRTpp")
system.file("extdata","Cuads.csv",package="IRTpp")

data = as.matrix(read.table("small.csv",sep=",",header=T))
data = as.matrix(read.table("/home//liberato/Downloads/Test_10_1_1000(1).csv",sep=" ",header=T))
irtpp(data,2)
##############################LOGLIKELIHOOD##############

t = simulateTest(model="2PL",items=10,individuals=1000,threshold=0.05,verbose=F,reps=200)
t$itempars
t$latentTraits
te=t$test[[1]]
te
irtpp(te,2)
te[2,]*probability.3pl(z=t$itempars,theta=0)+((1-te[2,])*(1-probability.3pl(z=t$itempars,theta=0)))
te[2,]
probability.3pl(z=t$itempars,theta=t$latentTraits[[1]])
#prob matrix
pm = lapply(t$latentTraits,function(x)log(probability.3pl(z=t$itempars,theta=x)))
#flatten it and flatten the test, then do the if.
lm=mapply(function(x,y){
  ifelse(y,x,1-x)
},unlist(pm),c(te))
#Sumall
Reduce("+",lm)

matrix(unlist(loglik(test=t$test[[1]],traits=t$latentTraits,z=t$itempars)),ncol=5)-m
loglik(test=t$test[[1]],traits=t$latentTraits,z=t$itempars)
m
result = 0;
for (i in 1:length(t$itempars[[1]]))
{
  for(j in 1:length(t$latentTraits))
  {
    p = (probability.3pl(a=t$itempars$a[i],b=t$itempars$b[i],c=t$itempars$c[i], theta=t$latentTraits[j]));
    result = result + (t$test[[1]][j,i]*log(p))+((1-t$test[[1]][j,i])*log(1-p))
  }
}
result
m = matrix(seq(length(t$itempars[[1]])*length(t$latentTraits)),ncol=5)
m
for (i in 1:length(t$itempars[[1]]))
{
  for(j in 1:length(t$latentTraits))
  {
    m[j,i] = (probability.3pl(a=t$itempars$a[i],b=t$itempars$b[i],c=t$itempars$c[i], theta=t$latentTraits[j]));
  }
}

probability.3pl(z=list(a=1,b=1,c=0.1),theta=t$latentTraits[[1]])
cuads
irtpp(data,2)
colSums(data)
t = simulateTest(model="3PL",items=1,individuals=1000,threshold=0.1)
t$test[[1]]
write.csv(t$test[[1]],file="small.csv",row.names=F)
t = simulateTest(model="3PL",items=10,individuals=1000,reps=500,threshold=0.05,boundaries=bound)
t$itempars
bound = list()
bound$c_lower=0.1
ip=lapply(t$test,function(x)irtpp(x,3))
mn=Reduce("+",ip)/500
mn
hist(pa,breaks=30);rug(pa);
hist(pb,breaks=30);rug(pb);
hist(pc,breaks=30);rug(pc);
rug(pa)

plot(density(pa));rug(pa);
plot(density(pb));rug(pb);
plot(density(pc));rug(pc);
ip
flat = lapply(ip,c)
pa = unlist(lapply(flat,function(x)x[1:10]))
pb = unlist(lapply(flat,function(x)x[11:20]))
pc = unlist(lapply(flat,function(x)x[21:30]))

Reduce(function(x,y){c(x[1:10],y[1:10])},flat)
par(mfrow=c(1,3))

ip
mn[,3]
c = t$itempars$c
c
mn[,3]-c
summary(mn[,3]-c)
summary(mn[,3])
(mn[,3] - c)/c
(0.04138114-0.01244633)/0.01244633
nt=c(
1,1,1,1,0,1,1,0,0,1,
1,1,1,1,0,1,1,0,1,0,
1,1,1,1,0,1,1,0,1,1,
1,1,1,1,0,1,1,1,0,0,
1,1,1,1,0,1,1,1,0,1,
1,1,1,1,0,1,1,1,1,0,
1,1,1,1,0,1,1,1,1,1,
1,1,1,1,1,0,0,0,0,0,
1,1,1,1,1,0,0,0,1,1,
1,1,1,1,1,0,0,1,0,0,
1,1,1,1,1,0,0,1,0,1,
1,1,1,1,1,0,0,1,1,0,
1,1,1,1,1,0,0,1,1,1,
1,1,1,1,1,0,1,0,0,1,
1,1,1,1,1,0,1,0,1,0,
1,1,1,1,1,0,1,0,1,1,
1,1,1,1,1,0,1,1,0,0,
1,1,1,1,1,0,1,1,0,1,
1,1,1,1,1,0,1,1,1,0,
1,1,1,1,1,0,1,1,1,1,
1,1,1,1,1,1,0,0,0,0,
1,1,1,1,1,1,0,0,0,1,
1,1,1,1,1,1,0,0,1,0,
1,1,1,1,1,1,0,0,1,1,
1,1,1,1,1,1,0,1,0,1,
1,1,1,1,1,1,0,1,1,0,
1,1,1,1,1,1,0,1,1,1,
1,1,1,1,1,1,1,0,0,1,
1,1,1,1,1,1,1,0,1,0,
1,1,1,1,1,1,1,0,1,1,
1,1,1,1,1,1,1,1,0,0,
1,1,1,1,1,1,1,1,0,1,
1,1,1,1,1,1,1,1,1,0,
1,1,1,1,1,1,1,1,1,1)

irtpp(ndata,2)

ndata = matrix(nt,ncol=10)

Tdatos = as.matrix(read.table("/home//liberato//3PLMay//Test_10_1_1000.csv",sep=" ",header=T);

cuads = read.table("/home//liberato/git//IRTpp/inst/SICSRepository//SICS//Cuads.csv",sep=",",header=T);
cds = read.table()
x = as.matrix(datos);
x
cuads = as.matrix(cuads);
cuads = as.numeric(cuads);
cuads
typeof(cuads)
IRTpp
data(IRTpp)
typeof(irtpp(x))
k=irtpp(x)
typeof(unlist(k))
as.numeric(k)
data()
save(cuads,file="cuads.Rda")
irtppinterface(x,3,cuads)
?IRTpp
s=irtpp(x, "THREE_PL", 1, "ANDRADE" , 0.00001, 200, T)
s

irtppinterface(x)


m=s[[1]]
m=as.matrix(m)
plot(m)
library(roxygen2)



k=simulateTest(items=10,individuals=10000,reps=1,model="3PL",verbose=T,threshold=0.05)
k=simulateTest(items=10,individuals=10000,reps=1,model="3PL",verbose=T,threshold=0)


install.packages("/home/liberato/git/lineprof_0.1.tar.gz", repos=NULL, type = "source")
library(lineprof)
getwd()
source("R/test.R")
l <- lineprof(simulateTest(items=10,individuals=1000,reps=1,model="3PL",verbose=T,threshold=0.05))
shine(l)









pars = c(41,10,
         -5.1225,-4.86637,-4.61025,-4.35412,-4.098,-3.84187,-3.58575,-3.32962,-3.0735,-2.81737,-2.56125,-2.30512,-2.049,-1.79287,-1.53675,-1.28062,-1.0245,-0.768375,-0.51225,-0.256125,0,0.256125,0.51225,0.768375,1.0245,1.28062,1.53675,1.79287,2.049,2.30512,2.56125,2.81737,3.0735,3.32962,3.58575,3.84187,4.098,4.35412,4.61025,4.86637,5.1225
         ,0.00013926,0.000501087,0.00168783,0.00532149,0.0157028,0.0433615,0.112039,0.270844,0.612522,1.29587,2.56482,4.75011,8.23561,13.3778,20.3871,29.2094,39.4682,50.5134,61.5682,71.8724,80.6771,87.0343,89.6119,87.0175,78.7362,65.8808,50.8712,36.3056,24.0096,14.744,8.41748,4.46966,2.20737,1.01364,0.432688,0.171653,0.0632792,0.0216765,0.00690032,0.0020416,0.000561558,4.78329e-05,5.81866e-05,8.0757e-06,5.65331e-05,2.70552e-05,9.88053e-06,4.57838e-05,7.36304e-05,5.14646e-05,4.91724e-05,0.000172988,0.000209468,2.94927e-05,0.000209253,0.000100475,3.75296e-05,0.000167544,0.000266427,0.000187529,0.000179799,0.000586369,0.000706182,0.00010128,0.000726205,0.00035013,0.000134042,0.000574898,0.000903305,0.000639853,0.000616194,0.00186317,0.00222949,0.000327301,0.00236264,0.00114484,0.000450167,0.00184969,0.0028697,0.00204405,0.00197915,0.0055504,0.00659132,0.00099621,0.00720462,0.0035121,0.00142149,0.00558013,0.00854266,0.00611295,0.0059571,0.0155048,0.0182475,0.00285841,0.0205876,0.0101076,0.00421984,0.0157838,0.0238294,0.0171123,0.016801,0.0406225,0.0473028,0.0077387,0.0551157,0.027285,0.0117744,0.0418583,0.0622884,0.0448356,0.0443941,0.0998467,0.114821,0.0197863,0.1382,0.0690763,0.0308716,0.10407,0.152575,0.109941,0.109887,0.230304,0.260986,0.0478159,0.32448,0.163982,0.0760375,0.242561,0.350241,0.252298,0.254769,0.498682,0.55556,0.109292,0.713199,0.364979,0.175876,0.52998,0.753504,0.541889,0.553211,1.01414,1.10782,0.236392,1.46722,0.761584,0.381907,1.08556,1.5195,1.0895,1.12505,1.93807,2.0704,0.484018,2.82498,1.48998,0.778385,2.08485,2.87291,2.05132,2.14319,3.48314,3.62989,0.938319,5.0914,2.73393,1.48901,3.75561,5.095,3.61916,3.82583,5.89295,5.97962,1.72249,8.59345,4.70785,2.67419,6.34993,8.48196,5.98976,6.40489,9.39833,9.27961,2.99484,13.5969,7.61729,4.51245,10.089,13.2714,9.3141,10.0699,14.156,13.6212,4.93437,20.2025,11.6025,7.16489,15.0913,19.5544,13.6405,14.9018,20.1885,19.0234,7.71256,28.2652,16.6842,10.7309,21.3103,27.2103,18.877,20.8272,27.3517,25.4732,11.4569,37.3843,22.7373,15.2129,28.5134,35.9026,24.795,27.6212,35.3409,32.984,16.2144,46.9799,29.5026,20.5025,36.313,45.1428,31.075,34.963,43.7145,41.5738,21.9146,56.3992,36.6098,26.3775,44.2126,54.3667,37.352,42.4893,51.869,51.0404,28.3032,64.9324,43.5474,32.4651,51.5946,62.916,43.1909,49.7541,58.9194,60.5133,34.8138,71.6645,49.5435,38.1342,57.6094,69.8671,47.9613,56.0423,
         63.596,68.1116,40.4291,75.3201,53.4746,42.3997,61.0963,73.8782,50.7356,60.192,64.4722,71.3528,43.7735,74.5139,54.0953,44.084,60.8405,73.4697,50.4887,60.8044,60.6846,68.5093,43.6615,68.5658,50.6975,42.3744,56.2588,67.8801,46.6894,57.0075,52.6456,59.8781,39.8284,58.2394,43.7155,37.4074,47.9812,57.8306,39.822,49.2049,42.0068,47.6792,33.1726,45.5682,34.6335,30.2947,37.6859,45.3498,31.2681,39.0214,30.8698,34.7543,25.2777,32.8933,25.26,22.5584,27.3074,32.7934,22.6401,28.485,20.9455,23.3156,17.6803,21.9641,17.0112,15.4936,18.3041,21.9307,15.1576,19.1983,13.1499,14.4568,11.3848,13.5973,10.6039,9.84035,11.3744,13.5961,9.40412,11.9771,7.64977,8.30726,6.76403,7.81514,6.12802,5.78891,6.56145,7.82557,5.41404,6.92795,4.12667,4.43037,3.71334,4.17291,3.28597,3.15701,3.51575,4.1846,2.89394,3.71878,2.06502,2.19436,1.88549,2.0703,1.63553,1.59662,1.75004,2.07923,1.43639,1.8531,0.958702,1.00963,0.88609,0.954319,0.755732,0.748915,0.809203,0.959907,0.661951,0.857332,0.412965,0.431545,0.385614,0.408665,0.324206,0.325828,0.347538,0.411695,0.2832,0.368267,0.165063,0.17135,0.155469,0.162558,0.129134,0.131491,0.138625,0.164015,0.112467,0.146875,0.0612289,0.0632044,0.0580953,0.0600627,0.0477623,0.0492279,0.0513542,0.060692,0.0414584,0.054392,0.0210825,0.0216594,0.0201296,0.0206149,0.0164068,0.0171008,0.0176699,0.020861,0.0141868,0.0187061,0.00674,0.00689668,0.00647029,0.00657354,0.00523548,0.00551346,0.00564786,0.00666114,0.00450722,0.0059756,0.00200129,0.00204088,0.00193023,0.00194781,0.00155241,0.00165035,0.00167735,0.00197631,0.00132979,0.00177354,0.000552109,0.000561426,0.000534683,0.000536465,0.000427871,0.000458805,0.000462996,0.000544967,0.000364447,0.000489205,0)
length(pars)
plot(pars)
args=c(rep(0.2,10),rep(1.1,10),rep(0.2,10));
length(args)
loglikitem(tar,args,pars,c(30,469),c(1))
loglikitem
tar = c(0.2,1.1,0.2)
optim(par = tar,args=args,fn = loglikitem,pars = pars,lens = c(3,469),index=c(0),method="BFGS")
div = 100;
t = 1:div
t
0.190968,0.630604,-1.75309e+84
t = list()
for (n in 1:div) {
  i = -3+(6*n)/div;
  args=c(rep(i,10),rep(1.1,10),rep(0.2,10));
  tar=c(i,-0.06663574,-0.82024796)
  t[n]=loglikitem(tar,args,pars,c(30,469),c(1));
}
t
t=unlist(t)
plot(t)
plot(pt)
plot(args)
plot(pars)
loglik(loglikargs,loglikpars,c(300,300))

loglikitem(loglikargs,loglikpars,c(300,300),1)
t = c(1,2)
grad(loglik,loglikargs,pars = loglikpars,lens = c(300,300))
optim(c(1,2),y = 2, fr, method = "BFGS")
optim(loglikargs,pars = loglikpars,lens = c(300,300),fn = loglik,method="BFGS")
fr(c(2,1))
abc 7 0.48449 0.0517453 -1.38629
gr : -6.54245 94.8828 39.9581
OPTIM SUCCESS
abc 7 0.48449 0.0517453 -1.38629
t = 1:1000
for (n in 1:1000) {  
  t[[n]]=loglikitem(loglikargs,loglikpars,c(300,300),1);}
t = unlist(t)
t
plot(t)
plot(t[1:60])
summary(t)
library(Rcpp)
remove.packages("IRTpp")
mode(t)
cuads = c(-5.1225, -4.86637, -4.61025, -4.35412, -4.098, -3.84187, -3.58575,-3.32962, -3.0735, -2.81737, -2.56125, -2.30512, -2.049, -1.79287, -1.53675, -1.28062, -1.0245, -0.768375, -0.51225, -0.256125, 0,0.256125, 0.51225, 0.768375, 1.0245, 1.28062, 1.53675, 1.79287, 2.049, 2.30512, 2.56125, 2.81737, 3.0735, 3.32962, 3.58575, 3.84187,4.098, 4.35412, 4.61025, 4.86637, 5.1225)
compileAttributes(pkgdir="/home/liberato/git/IRTpp/")
loglikargs = c(0.711677,0.752584,0.641149,0.618435,0.657948,0.71369,1.02755,0.855801,0.836348,0.926245,1.36213,1.1413,0.89035,0.685629,1.23771,0.630701,0.838525,0.942435,0.828374,0.757061,1.01684,1.22312,1.16375,0.37498,1.16971,0.436191,1.00002,1.02688,0.979781,0.612999,1.21281,0.849379,1.40708,1.1801,1.30679,0.943499,0.798607,0.555377,0.933245,1.21013,0.72374,0.888534,0.814143,0.893807,1.04433,1.07851,0.746544,0.972017,0.802061,1.23483,0.88394,1.01949,0.637523,0.880908,0.683619,1.32869,0.775008,0.609169,1.18858,0.956975,0.821728,0.693423,0.748436,0.750259,0.611322,1.42003,1.02714,0.825444,0.502088,0.613391,1.63018,0.250412,0.966357,0.995783,0.82902,0.927253,2.14152,0.992661,1.23292,1.02552,1.01456,1.10658,0.801614,1.04323,1.0794,0.346134,0.663877,0.773446,1.16334,0.850074,1.11103,0.999648,0.666467,1.26102,1.32175,1.03391,0.93777,0.597904,1.05992,0.400465,0.234821,0.109915,0.187097,0.694033,0.182169,0.911487,0.592079,-1.46898,-0.379148,0.106715,-3.66745,-0.0251032,0.56149,0.966998,0.702244,-0.0245912,0.165179,-1.47813,-0.101761,-0.523302,0.306355,0.0372879,-0.60661,0.514999,1.79122,0.311716,0.858644,-0.734112,-0.934705,-0.292162,1.15789,-0.149042,0.965506,-0.472392,0.681014,0.455218,-2.49709,-1.43561,-0.0264432,0.115618,-0.11499,0.281993,0.0937782,-0.667721,-1.10994,1.20073,-0.890415,0.17067,-0.732268,-0.66265,1.27444,0.0927718,-0.508035,-0.244069,-0.510627,-0.359319,-0.440652,0.857832,0.36119,0.336651,-0.141048,0.1516,-0.0614255,-0.127011,-0.974534,-0.933476,0.539849,0.112842,0.128137,0.692704,-0.266044,-1.56457,-1.66051,-0.658497,1.3929,0.531854,0.584749,2.17092,0.086047,-1.0154,-1.44796,-1.27996,1.17043,-0.122012,-0.777155,-0.153951,1.10532,-1.1204,0.433304,0.0610695,-0.146444,-0.160844,1.15408,0.711735,-0.917135,-0.129932,-0.20054,0.391693,-1.01289,0.369209,-1.01745,-0.243837,-0.687668,-2.01128,-1.2787,-2.87911,-0.926459,-1.45944,-0.973725,-0.849209,-0.997532,-2.86402,-1.32666,-1.37747,-2.14598,-8.40519,-1.46984,-0.828745,-1.6675,-2.09445,-1.94482,-2.50169,-0.570433,-6.79986,-1.90632,-9.57155,-1.21274,-1.82356,-2.38215,-8.84717,-0.616414,-1.02638,-1.95523,-0.826023,-1.0541,-0.729821,-0.628994,-7.94518,-1.41933,-2.92225,-0.609128,-1.76969,-1.60947,-2.77244,-1.8687,-0.598485,-4.11915,-15.7457,-1.98912,-3.55091,-3.0625,-2.1824,-1.27725,-2.3223,-2.41081,-0.992614,-2.62387,-3.69984,-0.835945,-0.977929,-7.35991,-3.79871,-2.03707,-3.90252,-3.74723,-0.804128,-2.16999,-2.91405,-0.701105,-1.82641,-1.47731,-12.8069,-0.49281,-3.13499,-3.14132,-1.60537,-1.49112,-9.81848,-1.0008,-1.79413,-1.90551,-0.927548,-1.46769,-1.42094,-1.14255,-5.38639,-2.94946,-9.21669,-0.577567,-1.73707,-0.886726,-1.11935,-0.338854,-0.771945,-0.995808,-1.46044,-2.98849,-1.34705,-1.87568,-3.26733);
loglikpars = c(41,100,-5.1225,-4.86637,-4.61025,-4.35412,-4.098,-3.84187,-3.58575,-3.32962,-3.0735,-2.81737,-2.56125,-2.30512,-2.049,-1.79287,-1.53675,-1.28062,-1.0245,-0.768375,-0.51225,-0.256125,0,0.256125,0.51225,0.768375,1.0245,1.28062,1.53675,1.79287,2.049,2.30512,2.56125,2.81737,3.0735,3.32962,3.58575,3.84187,4.098,4.35412,4.61025,4.86637,5.1225,0.00139144,0.00510624,0.0175899,0.05702,0.174471,0.505378,1.38792,3.60975,8.8505,20.2965,43.0919,83.8168,148.28,238.699,353.062,486.282,629.597,772.323,901.9,986.303,1002.71,963.968,870.536,733.93,580.736,436.09,312.963,208.423,121.659,58.8987,22.7818,6.95043,1.68986,0.335419,0.0557903,0.00793814,0.000979086,0.000105573,1.00152e-05,8.41033e-07,6.29005e-08,0.00071425,0.000828733,0.000502939,0.000119907,0.000808131,0.000376658,0.000507903,0.000647477,0.000155892,0.000398927,0.000188721,3.34272e-05,0.000403825,0.000366221,7.64203e-05,1.25414e-05,0.000149398,0.000575667,1.18706e-05,0.000155769,7.75854e-05,0.00010866,0.000541487,8.51508e-05,0.000753781,0.000210168,0.000112476,0.000372662,3.7035e-05,6.14041e-05,0.000242461,0.000499964,0.000441696,0.000357953,0.000194239,0.000549244,0.000610802,2.91908e-05,0.000553312,1.52456e-05,0.000118737,0.000314861,0.000589546,0.000264982,0.000180635,0.000223743,2.55232e-05,6.4648e-06,9.17302e-05,1.01253e-05,0.000137989,5.3485e-05,8.03377e-05,0.000102037,0.000502866,0.000217143,0.000152036,0.000230838,0.000823015,0.000235512,1.63348e-05,1.23598e-05,0.000116231,2.24032e-05,4.03962e-06,0.000613835,0.000488883,4.81043e-05,0.00102119,0.000101886,0.000259742,4.47005e-05,0.00108445,6.02003e-06,0.000126279,0.000248361,0.000236786,4.09797e-05,0.000630688,9.6556e-05,0.000149979,0.000154627,0.000100707,0.000391857,0.000297093,6.17275e-05,0.000601454,5.00743e-07,0.000413821,0.000354012,0.000521644,9.64844e-05,0.00093485,0.000637348,0.000351541,0.000176891,2.99891e-05,0.000309415,0.000533545,7.97166e-05,0.00256121,0.00307625,0.00191507,0.000522717,0.00281052,0.0013594,0.00190858,0.00224292,0.000659601,0.0015173,0.000763282,0.000133123,0.00151574,0.00135924,0.000316509,6.45181e-05,0.000597479,0.00203095,6.10772e-05,0.000622635,0.000340259,0.000430829,0.00205043,0.000401372,0.00264274,0.000822146,0.000473787,0.00135266,0.00016768,0.000288068,0.000979419,0.00173921,0.00150164,0.00130572,0.000795612,0.00204967,0.00218088,0.000115554,0.00197974,6.73368e-05,0.000531666,0.00112198,0.00208438,0.000995819,0.000713142,0.000955718,0.000107184,3.44431e-05,0.000414298,4.65949e-05,0.000585426,0.000244311,0.00036618,0.000398424,0.00176936,0.000870818,0.000588079,0.000872606,0.00287954,0.000950082,8.80141e-05,6.68322e-05,0.000475208,9.36652e-05,2.27523e-05,0.00220532,0.00168736,0.00019764,0.00355392,0.000474854,0.000966534,0.000202873,0.00381809,2.89355e-05,0.000518956,0.000961648,0.000888114,0.000216864,0.00227277,0.000419114,0.000589561,0.000647947,0.000447924,0.00143572,0.00118745,0.000293296,0.00214485,3.16739e-06,0.00156944,0.00127845,0.00196692,0.000401173,0.00339907,0.00227771,0.00131062,0.000726089,0.000132443,0.00120532,0.00184803,0.000384758,0.0086139,0.0106691,0.00688202,0.00216836,0.00909226,0.00458709,0.00675183,0.00719704,0.00263325,0.0054087,0.00290497,0.000506919,0.00530894,0.00477657,0.00124685,0.000314892);
length(loglikargs)
length(loglikpars)
plot(cuads)
summary(cuads)
loglikpars[3:43] = cuads
loglikpars
weis = c(0.000000204842,0.000000736153,0.00000247758,0.00000780904,0.0000230504,0.000063719,0.000164957,0.000399927,0.000908035,0.00193079,0.00384482,0.00717015,0.0125225,0.0204816,0.0313724,0.0450029,0.0604567,0.0760603,0.0896154,0.098882,0.102179,0.098882,0.0896154,0.0760603,0.0604567,0.0450029,0.0313724,0.0204816,0.0125225,0.00717015,0.00384482,0.00193079,0.000908035,0.000399927,0.000164957,0.000063719,0.0000230504,0.00000780904,0.00000247758,0.000000736153,0.000000204842);
summary(loglikpars)
plot(loglikpars[2+82:10*41])
10*41
pars[(2+82):470]
pars
length(pars)
pars[length(pars)]
idx = 0
idf=1:41
idxx = 1:41
pars[2]
it = 1
for(z in 1:41){
  idx = idx + it
  idf[[z]]=pars[(85+idx)]
  idxx[[z]] = idx+85
  idx = idx + (pars[2]-it)
}
pars[1:2]
pars[3:43]
pars[44:84]
pars[85:length(pars)]
idf
idxx
length(pars)
 ;
summary(t)