## Package library("kml") ## Examples data("epipageShort", package = "kml") head(epipageShort) imputation(as.matrix(epipageShort[, 3:6])) imputation(as.matrix(epipageShort[, 3:6]), method = "linearInterpol") cldSDQ <- cld(epipageShort, timeInData = 3:6) cldSDQ kml(cldSDQ, nbRedraw = 2, toPlot = 'both') kml(cldSDQ) kml(cldSDQ, 4, parAlgo = parALGO(distance = function(x, y) cor(x, y), saveFreq = 10)) choice(cldSDQ) plotAllCriterion(cldSDQ) epipageShort$clusters <- getClusters(cldSDQ, 4) epipageGroupAD <- epipageShort[epipageShort$clusters %in% c("A", "D"),] summary(glm(clusters ~ gender, data = epipageGroupAD, family = "binomial")) library("kml3d") data("pregnandiol", package = "kml3d") head(pregnandiol) cldPreg <- cld3d(pregnandiol, timeInData = list(preg = 1:30 * 2 + 1, temp = 1:30 * 2)) cldPreg kml3d(cldPreg) choice(cldPreg) scene <- plot3dPdf(cldPreg, 3) saveTrianglesAsASY(scene) makeLatexFile() ## Table 1 values <- c(3, 10, 30, 100, 300, 1000, 3000, 10000) result <- expand.grid(reroll = 1:10, nbTimes = values, nbId = values) result$id <- 1:nrow(result) result$times <- 1 result <- result[order(result[, 2] * result[, 3]), c(4:1, 5)] summary(result) for(i in 1:nrow(result)){ try(myData <- gald(result$nbId[i], time = seq(0, 10, , result$nbTimes[i] + 1))) try(plot(myData)) try(result$times[i] <- try(system.time(kml(myData, , 2))[3])) print(result[i,]) save(result, file = "valeursLimites.Rdata") rm(myData) }