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513 lines
24 KiB
R
513 lines
24 KiB
R
stop("Models RSM and GRSM cannot be used for unequal numbers of response categories!")
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}
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design_list <- design_GPCMlasso(formula = formula, data = data,
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Y = Y, RSM = RSM, GPCM = GPCM, DSF = DSF, all.dummies = control$all.dummies,
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main.effects = main.effects)
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if (design_list$m == 0) {
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control$lambda <- 0
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control$adaptive <- FALSE
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cv <- FALSE
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}
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if (length(control$lambda) == 1) {
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cv <- FALSE
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}
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loglik_fun <- loglikPCMlasso
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score_fun <- scorePCMlasso
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log_score_fun <- loglikscorePCMlasso2
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if (all(k == 2)) {
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loglik_fun <- loglikDIFlasso
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score_fun <- scoreDIFlasso
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log_score_fun <- loglikscoreDIFlasso2
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}
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fit <- fit_GPCMlasso(model = model, loglik_fun = loglik_fun, acoefs2 = acoefs2,
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score_fun = score_fun, log_score_fun, design_list = design_list,
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control = control, start = NULL, scale_fac = 1, main.effects = main.effects)
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if (is.null(control$lambda)) {
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control$lambda <- fit$lambda
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}
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coefficients <- fit$coefficients
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coef.rescal <- fit$coef.rescal
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logLik <- fit$logLik
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df <- fit$df
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BIC <- -2 * logLik + log(design_list$n) * df
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AIC <- -2 * logLik + 2 * df
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cAIC <- -2 * logLik + 2 * df + 2 * df * (df - 1)/(design_list$n -
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df - 1)
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if (cv) {
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cv_error <- fit_cv_GPCMlasso(model, design_list, control,
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score_fun, loglik_fun, log_score_fun, Y)
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}
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else {
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cv_error <- NULL
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}
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ret.list <- list(coefficients = coefficients, logLik = logLik,
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cv_error = cv_error, call = match.call(), model = model,
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data = data, control = control, DSF = DSF, formula = formula,
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item.names = item.names, Y = Y, design_list = design_list,
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AIC = AIC, BIC = BIC, cAIC = cAIC, df = df, coef.rescal = coef.rescal,
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main.effects = main.effects)
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class(ret.list) <- "GPCMlasso"
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return(ret.list)
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}
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GPCMlasso2 <- function (formula, data, DSF = FALSE, model = c("PCM", "RSM",
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"GPCM", "GRSM", "RM", "2PL"), control = ctrl_GPCMlasso(),
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cv = FALSE, main.effects = TRUE,acoefs2=NULL)
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{
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if (!is.data.frame(data))
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stop("data has to be a data.frame!")
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Y <- model.response(model.frame(formula, data = data))
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for (i in 1:ncol(Y)) {
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Y[, i] <- as.factor(Y[, i])
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}
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item.names <- colnames(Y)
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model <- match.arg(model)
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RSM <- GPCM <- FALSE
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if (model %in% c("GRSM", "RSM")) {
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RSM <- TRUE
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}
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if (model %in% c("GRSM", "GPCM", "2PL")) {
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GPCM <- TRUE
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}
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k <- apply(Y, 2, function(x) {
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length(levels(as.factor(x)))
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})
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if (all(k == 2) | model %in% c("RM", "2PL")) {
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DSF <- FALSE
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control$cv.crit <- "deviance"
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}
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if (length(unique(k)) > 1 & RSM) {
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stop("Models RSM and GRSM cannot be used for unequal numbers of response categories!")
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}
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design_list <- design_GPCMlasso(formula = formula, data = data,
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Y = Y, RSM = RSM, GPCM = GPCM, DSF = DSF, all.dummies = control$all.dummies,
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main.effects = main.effects)
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if (design_list$m == 0) {
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control$lambda <- 0
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control$adaptive <- FALSE
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cv <- FALSE
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}
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if (length(control$lambda) == 1) {
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cv <- FALSE
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}
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loglik_fun <- loglikPCMlasso
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score_fun <- scorePCMlasso
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log_score_fun <- loglikscorePCMlasso2
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if (all(k == 2)) {
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loglik_fun <- loglikDIFlasso
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score_fun <- scoreDIFlasso
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log_score_fun <- loglikscoreDIFlasso2
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}
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fit <- fit_GPCMlasso(model = model, loglik_fun = loglik_fun, acoefs2 = acoefs2,
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score_fun = score_fun, log_score_fun, design_list = design_list,
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control = control, start = NULL, scale_fac = 1, main.effects = main.effects)
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if (is.null(control$lambda)) {
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control$lambda <- fit$lambda
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}
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coefficients <- fit$coefficients
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coef.rescal <- fit$coef.rescal
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logLik <- fit$logLik
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df <- fit$df
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BIC <- -2 * logLik + log(design_list$n) * df
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AIC <- -2 * logLik + 2 * df
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cAIC <- -2 * logLik + 2 * df + 2 * df * (df - 1)/(design_list$n -
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df - 1)
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if (cv) {
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cv_error <- fit_cv_GPCMlasso(model, design_list, control,
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score_fun, loglik_fun, log_score_fun, Y)
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}
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else {
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cv_error <- NULL
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}
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ret.list <- list(coefficients = coefficients, logLik = logLik,
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cv_error = cv_error, call = match.call(), model = model,
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data = data, control = control, DSF = DSF, formula = formula,
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item.names = item.names, Y = Y, design_list = design_list,
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AIC = AIC, BIC = BIC, cAIC = cAIC, df = df, coef.rescal = coef.rescal,
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main.effects = main.effects)
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class(ret.list) <- "GPCMlasso"
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return(ret.list)
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}
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GPCMlasso2(formula = cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control=ctrl_GPCMlasso(lambda=0.0000000000001),acoefs2 = u)
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u
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## create responses for acat from ordinal values
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createResponse <- function(Y){
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Y <- as.factor(Y)
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model.matrix(~0+Y)[,-length(levels(Y))]
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}
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design_GPCMlasso <- function(formula = formula, Y=Y, data = data, RSM = RSM,
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GPCM = GPCM, DSF = DSF, all.dummies = TRUE, main.effects = main.effects){
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## extract covariates
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if(all.dummies){
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term.labels <- attr(terms(formula), "term.labels")
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X <- matrix(rep(1,nrow(data)))
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for(ij in 1:length(term.labels)){
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x.now <- data[,term.labels[ij], drop = FALSE]
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if(is.factor(x.now[,1])){
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if(nlevels(x.now[,1])==2){
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X <- cbind(X,model.matrix(~.,data=x.now)[,-1,drop=FALSE])
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}else{
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X <- cbind(X,model.matrix(~0+.,data=x.now))
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}
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}else{
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X <- cbind(X,model.matrix(~.,data=x.now)[,-1,drop=FALSE])
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}
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}
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X <- X[,-1,drop = FALSE]
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}else{
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X <- model.matrix(formula, data = data)
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if(ncol(X)>=1){
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if(colnames(X)[1]=="(Intercept)"){
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X <- X[,-1,drop = FALSE]
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}
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}
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}
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x.names <- colnames(X)
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## factorize response vector
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## initialize basic parameters
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k <- apply(Y, 2, function(x){length(levels(as.factor(x)))})
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q <- k-1
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n <- nrow(Y)
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I <- ncol(Y)
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m <- ncol(X)
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n_sigma <- 1
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if(GPCM){
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n_sigma <- I
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}
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## get final response vector
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if(all(q==1)){
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response <- as.numeric(as.factor(c(t(Y))))-1
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}else{
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response <- lapply(as.data.frame(Y),createResponse)
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response <- c(t(do.call("cbind",response)))
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}
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## total number of parameters to be optimized
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px <- sum(q)+n_sigma
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if(RSM){
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px <- q[1]+I+n_sigma-1
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}
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## scale X and save standard deviations for re-scaling
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# X <- scale(X, center = FALSE)
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X <- scale(X, center = FALSE, scale = apply(X, 2, sd, na.rm = TRUE))
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sd.vec <- attributes(X)$scale
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sd.vec <- create.sd.vec(sd.vec, DSF, px, n_sigma, I, q, main.effects)
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## create design matrix for basic item parameters
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if(!RSM){
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design <- -diag(px-n_sigma)
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}else{
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design <- -cbind(matrix(rep(diag(I),each=q[1]),ncol=I),
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matrix(rep(diag(q[1]),I),ncol=q[1],byrow = TRUE))[,-(I+1)]
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}
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## create design matrix for covariate part
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if(m>=1){
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designX <- -get_designX(X, DSF, m, I, q, n)
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## create penalization matrix
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acoefs <- get_acoefs(RSM, DSF, m, I, q, n_sigma)
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## update number of parameters to be optimized
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px <- px + ncol(designX)
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}else{
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## dummy matrix in case no covariates are specified
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designX <- matrix(0,0,0)
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acoefs <- matrix(0,nrow=px,ncol=1)
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}
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if(main.effects){
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design.main <- matrix(rep(X, each = sum(q)),ncol = ncol(X))
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designX <- cbind(design.main, designX)
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acoefs <- rbind(matrix(0, ncol = ncol(acoefs), nrow = ncol(design.main)), acoefs)
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px <- px + ncol(X)
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}
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ret.list <- list(q = q, I = I, m = m, px = px, n = n, response = response,
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design = design, designX = designX, sd.vec = sd.vec,
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acoefs = acoefs, n_sigma = n_sigma, x.names = x.names,
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RSM = RSM, GPCM = GPCM, Y = Y, DSF = DSF)
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return(ret.list)
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}
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create.sd.vec <- function(sd.vec, DSF, px, n_sigma, I, q, main.effects){
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if(DSF){
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new_vec <- rep(sd.vec, sum(q))
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}else{
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new_vec <- rep(sd.vec, I)
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}
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if(main.effects){
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new_vec <- c(sd.vec, new_vec)
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}
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new_vec <- c(rep(1,px-n_sigma),new_vec,rep(1,n_sigma))
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new_vec
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}
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GPCMlasso2(formula = cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control=ctrl_GPCMlasso(lambda=0.0000000000001),acoefs2 = u)
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get_designX <- function(X, DSF, m, I, q, n){
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if(!DSF){
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designX <- matrix(0, ncol = m * I, nrow = n * sum(q))
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pos_u <- 1
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for (u in 1:n) {
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for(uu in 1:I){
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designX[pos_u:(pos_u+q[uu]-1), ((uu - 1) * m + 1):(uu * m)] <-
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matrix(rep(X[u,], q[uu]), byrow = TRUE, ncol = m, nrow = q[uu])
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pos_u <- pos_u+q[uu]
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}
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}
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}else{
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designX <- matrix(0, ncol = m * sum(q), nrow = n * sum(q))
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pos_u <- 1
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for (u in 1:n) {
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pos_uu <- 1
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for(uu in 1:I){
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for(uuu in 1:q[uu]){
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designX[pos_u, pos_uu:(pos_uu+m-1)] <-
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X[u,]
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pos_u <- pos_u+1
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pos_uu <- pos_uu+m
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}
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}
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}
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}
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return(designX)
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}
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get_acoefs_old <- function(RSM, DSF, m, I, q, n_sigma){
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if(!DSF){
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pen1 <- diag(m*I)
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}else{
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pen1 <- matrix(0,nrow=m*sum(q),ncol=m*sum(choose(q,2)))
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pos1 <-1
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pos_pos <- 1
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for(u in 1:I){
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n_comb <- choose(q[u],2)
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if(n_comb>0){
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combis <- combn(q[u],2)-1
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for(uuu in 1:m){
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for(uu in 1:n_comb){
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pen1[combis[1,uu]*m+pos_pos,pos1] <- 1
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pen1[combis[2,uu]*m+pos_pos,pos1] <- -1
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pos1 <- pos1+1
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}
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pos_pos <- pos_pos+1
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}
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pos_pos <- pos_pos+(q[u]-1)*m
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}
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}
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pen1 <- cbind(diag(m*sum(q)),pen1)
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}
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if(RSM){
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acoefs <- rbind(matrix(0,nrow=q[1]+I-1,ncol=ncol(pen1)),pen1,
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matrix(0, ncol = ncol(pen1), nrow = n_sigma))
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}else{
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acoefs <- rbind(matrix(0,nrow=sum(q),ncol=ncol(pen1)),pen1,
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matrix(0, ncol = ncol(pen1), nrow = n_sigma))
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}
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}
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get_acoefs <- function(RSM, DSF, m, I, q, n_sigma){
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if(!DSF){
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pen1 <- diag(m*I)
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}else{
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pen1 <- matrix(0,nrow=m*sum(q),ncol=m*sum(q-1))
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pos1 <-1
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pos_pos <- 1
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for(u in 1:I){
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n_comb <- q[u] - 1
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if(n_comb>0){
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combis <- rep(1:q[u], each = 2)
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combis <- matrix(combis[-c(1,length(combis))]-1, nrow = 2)
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for(uuu in 1:m){
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for(uu in 1:n_comb){
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pen1[combis[1,uu]*m+pos_pos,pos1] <- 1
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pen1[combis[2,uu]*m+pos_pos,pos1] <- -1
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pos1 <- pos1+1
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}
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pos_pos <- pos_pos+1
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}
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pos_pos <- pos_pos+(q[u]-1)*m
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}
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}
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pen1 <- cbind(diag(m*sum(q)),pen1)
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}
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if(RSM){
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acoefs <- rbind(matrix(0,nrow=q[1]+I-1,ncol=ncol(pen1)),pen1,
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matrix(0, ncol = ncol(pen1), nrow = n_sigma))
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}else{
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acoefs <- rbind(matrix(0,nrow=sum(q),ncol=ncol(pen1)),pen1,
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matrix(0, ncol = ncol(pen1), nrow = n_sigma))
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}
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}
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GPCMlasso2(formula = cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control=ctrl_GPCMlasso(lambda=0.0000000000001),acoefs2 = u)
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# Generated by using Rcpp::compileAttributes() -> do not edit by hand
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# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
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loglikPCMlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
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.Call(`_GPCMlasso_loglikPCMlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
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}
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scorePCMlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
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.Call(`_GPCMlasso_scorePCMlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
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}
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loglikDIFlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
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.Call(`_GPCMlasso_loglikDIFlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
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}
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scoreDIFlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
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.Call(`_GPCMlasso_scoreDIFlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
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}
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loglikscorePCMlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
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.Call(`_GPCMlasso_loglikscorePCMlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
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}
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loglikscoreDIFlasso <- function(alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac) {
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.Call(`_GPCMlasso_loglikscoreDIFlasso`, alpha, Y, X, Z, Q, q, n, I, px, GHweights, GHnodes, acoefs, lambda, lambda2, cvalue, cores, weight, n_sigma, scale_fac)
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}
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GPCMlasso2(formula = cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control=ctrl_GPCMlasso(lambda=0.0000000000001),acoefs2 = u)
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library(GPCMlasso)
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trace(GPCMlasso,edit=T)
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library(GPCMlasso)
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View(GPCMlasso)
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u
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aaa
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aaa <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',100,'/scenario_',"5A_100",'.csv'))
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aaa <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',100,'/scenario_',"5A_100",'.csv'))
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aaaa <- aaa[aaa$replication==1,]
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GPCMlasso(formula=cbind('item1','item2',"item3","item4")~TT,data=aaaa,model="PCM")
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GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM")
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GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001))
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acc <- matrix(nrow = 10,ncol=4,0)
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acc
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GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001),acoefs2 = acc)
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acc[6,1]1
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acc[6,1]<-1
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acc
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acc[7,2]<-1
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acc[8,3]<-1
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acc[9,4]<-1
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acc
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GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001),acoefs2 = acc)
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library(TAM)
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tam.mml(resp=aaaa[,c('item1',"item2","item3","item4")],group=aaaa[,'TT'])
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zzz <- tam.mml(resp=aaaa[,c('item1',"item2","item3","item4")],group=aaaa[,'TT'])
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summary(zzz)
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GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001),acoefs2 = acc)
|
|
acc <- matrix(nrow = 10,ncol=4,0)
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GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001),acoefs2 = acc)
|
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summary(zzz)
|
|
remove.packages(GPCMlasso)
|
|
remove.packages("GPCMlasso")
|
|
install.packages("GPCMlasso")
|
|
install.packages("GPCMlasso")
|
|
library(GPCMlasso)
|
|
View(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001))
|
|
tam.mml(resp=aaaa[,c('item1',"item2","item3","item4")],group=aaaa[,'TT'])
|
|
library(tam.mml)
|
|
library(TAM)
|
|
tam.mml(resp=aaaa[,c('item1',"item2","item3","item4")],group=aaaa[,'TT'])
|
|
tam.mml(resp=aaaa[,c('item1',"item2","item3","item4")],group=aaaa[,'TT'])
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.000000000000000000001))
|
|
remove.packages("GPCMlasso")
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.000000000000000000001))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),acoefs=acc)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),acoefs2=acc)
|
|
View(GPCMlasso)
|
|
library(GPCMlasso)
|
|
View(GPCMlasso)
|
|
aaa <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',100,'/scenario_',"5A_100",'.csv'))
|
|
aaa <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',100,'/scenario_',"5A_100",'.csv'))
|
|
aaaa <- aaa[aaa$replication==1,]
|
|
acc <- matrix(nrow = 10,ncol=4,0)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),acoefs2=acc)
|
|
acc[6,1] <- 1;acc[7,2] <- 1;acc[8,3] <- 1;acc[9,4] <- 1
|
|
acc
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),acoefs2=acc)
|
|
remove.packages("GPCMlasso")
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 100))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001))$coefficients
|
|
install.packages("geoR")
|
|
library(geoR)
|
|
nlmP
|
|
nlmP()
|
|
.nlmP()
|
|
geoR::.nlmP
|
|
remove.packages("GPCMlasso")
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001))
|
|
remove.packages("GPCMlasso")
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001))$design_list
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = T)
|
|
summary(GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = T))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = T)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = F)
|
|
library(TAM)
|
|
tam.mml(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"],irtmodel="PCM2")
|
|
summary(tam.mml(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"],irtmodel="PCM2"))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = F)
|
|
summary(tam.mml(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"],irtmodel="PCM2"))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = F)
|
|
summary(tam.mml(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"],irtmodel="PCM2"))
|
|
summary(tam.jml(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"],irtmodel="PCM2"))
|
|
summary(tam.jml(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"]))
|
|
summary(tam(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"]))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000000000000000001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000000000000000000001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1),DSF = F,cv=F)
|
|
summary(tam(resp = aaaa[,c("item1","item2","item3","item4")],group=aaaa[,"TT"]))
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.5),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.1),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.01),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00000001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.01),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.00000001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000001),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.0000005),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)$design_list
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
remove.packages('GPCMlasso')
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)$design_list
|
|
remove.packages("PCMlasso")
|
|
remove.packages("GPCMlasso")
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)$design_list
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)$design_list
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
remove.packages("GPCMlasso")
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)$design_list
|
|
remove.packages("GPCMlasso")
|
|
install.packages('/home/corentin/Documents/These/Recherche/GPCMlasso_0.1-7.tar.gz')
|
|
library(GPCMlasso)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT:item1,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~I(TT:item1*0),data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT:item1*0,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
aaaa$item1tt <- 1-aaaa$item1
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT:item1tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
aaaa$item2tt <- 1-aaaa$item2
|
|
aaaa$item3tt <- 1-aaaa$item3
|
|
aaaa$item1
|
|
aaaa$item4tt <- 1-aaaa$item4
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT:item1tt+TT:item2TT+TT:item3tt+TT:item4tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT:item1tt+TT:item2tt+TT:item3tt+TT:item4tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT*item1tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|
|
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT*item1tt+TT*item2tt+TT*item3tt+TT*item4tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
|