wenchao-ma / gdina Goto Github PK

library("GDINA")
factordata <- read.csv("factorandmultiples.csv")
factorQ <- read.csv("q-matrix.csv")

ACDMmod1 <- GDINA(dat = factordata, Q = factorQ, model = "ACDM")
summary(ACDMmod1)

1. GDINA(dat = data, Q = Q, model = "logitGDINA")
2. SG.Est(dat = dat, Q = Q, model = model, sequential = sequential, 
 .     att.dist = att.dist, att.prior = att.prior, saturated = saturated, 
 .     att.str = att.str, mono.constraint = mono.constraint, latent.var = latent.var, 
 .     verbose = verbose, catprob.parm = catprob.parm, loglinear = loglinear, 
 .     item.names = item.names, control = control, item.prior = item.prior, 
 .     nloptr_args = nloptr.args, auglag_args = auglag.args, solnp_args = solnp.args, 
 .     linkfunc = linkfunc, higher.order = higher.order, solver = solver, 
 .     DesignMatrices = design.matrix, ConstrPairs = constr.pairs)
3. as.matrix(att.structure(hierarchy.list = att.str, K = K, Q = Q, 
 .     att.prob = "uniform")$att.str)
4. att.structure(hierarchy.list = att.str, K = K, Q = Q, att.prob = "uniform")
5. attributepattern(K = K, Q = Q)
6. alpha2(K)

Q <- sim30GDINA$simQ
K <- ncol(Q)
# divergent structure A1->A2->A3;A1->A4->A5;A1->A4->A6
diverg <- list(c(1,2),
               c(2,3),
               c(1,4),
               c(4,5))
struc <- att.structure(diverg,K)
# data simulation
N <- 1000
true.lc <- sample(c(1:2^K),N,replace=TRUE,prob=struc$att.prob)
table(true.lc) #check the sample
true.att <- attributepattern(K)[true.lc,]
gs <- matrix(rep(0.1,2*nrow(Q)),ncol=2)
# data simulation
simD <- simGDINA(N,Q,gs.parm = gs,
                 model = "DINA",attribute = true.att)
dat <- extract(simD,"dat")
modp1 <- GDINA(dat = dat, Q = Q, att.prior = struc$att.prob, att.str = TRUE, att.dist = "saturated")

Microsoft R Open 4.0.2
The enhanced R distribution from Microsoft
Microsoft packages Copyright (C) 2020 Microsoft Corporation

Using the Intel MKL for parallel mathematical computing (using 1 cores).

Default CRAN mirror snapshot taken on 2020-07-16.
See: https://mran.microsoft.com/.

* installing *source* package ‘GDINA’ ...
** package ‘GDINA’ successfully unpacked and MD5 sums checked
** using staged installation
** libs
.
.
. _<removing some g++ compilation outputs>_
g++ -shared -L/opt/microsoft/ropen/4.0.2/lib64/R/lib -o GDINA.so Lik.o Lik2.o LouisC.o Mord.o Mstep.o NgRg.o RcppExports.o SE.o aggregateCol.o fitstats.o scorep.o sequP.o util.o varsigma.o Microsoft R Open 4.0.2 The enhanced R distribution from Microsoft Microsoft packages Copyright (C) 2020 Microsoft Corporation Using the Intel MKL for parallel mathematical computing (using 1 cores). Default CRAN mirror snapshot taken on 2020-07-16. See: https://mran.microsoft.com/. -L/opt/microsoft/ropen/4.0.2/lib64/R/lib -lRlapack -L/opt/microsoft/ropen/4.0.2/lib64/R/lib -lRblas -lgfortran -lm -L/opt/microsoft/ropen/4.0.2/lib64/R/lib -lR
g++: error: Microsoft: No such file or directory
g++: error: R: No such file or directory
g++: error: Open: No such file or directory
g++: error: 4.0.2: No such file or directory
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/opt/microsoft/ropen/4.0.2/lib64/R/share/make/shlib.mk:6: recipe for target 'GDINA.so' failed
make: *** [GDINA.so] Error 1
ERROR: compilation failed for package ‘GDINA’
* removing ‘/home/rstudio/R/x86_64-pc-linux-gnu-library/4.0/GDINA’
Warning in install.packages :
  installation of package ‘GDINA’ had non-zero exit status

The downloaded source packages are in
	‘/tmp/RtmpTrbkOd/downloaded_packages’

Error in if (func.lambda(lower, X2, df, b = bb) * func.lambda(l.upper,  : 
  missing value where TRUE/FALSE needed