## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set(collapse = TRUE, comment = "#>") ## ----------------------------------------------------------------------------- library("Gifi") ABC6 <- ABC[,6:11] ## we use 6 items from the dataset head(ABC6) ## ----------------------------------------------------------------------------- fit_ordpca <- princals(ABC6, ndim = 2, levels = "ordinal") fit_ordpca ## ----------------------------------------------------------------------------- summary(fit_ordpca) ## ----fig.height=5, fig.width=5------------------------------------------------ plot(fit_ordpca, plot.type = "loadplot") ## ----fig.height=5, fig.width=5------------------------------------------------ plot(fit_ordpca, plot.type = "biplot", col.loadings = "coral3", col.scores = "lightgrey") abline(h = 0, v = 0, lty = 2) ## ----fig.height=7, fig.width=7------------------------------------------------ plot(fit_ordpca, plot.type = "transplot") ## ----------------------------------------------------------------------------- head(fit_ordpca$scoremat) ## ----------------------------------------------------------------------------- fit_metpca <- princals(ABC6, ndim = 2, levels = "metric") fit_metpca ## ----fig.height=7, fig.width=7------------------------------------------------ plot(fit_metpca, plot.type = "transplot") ## ----------------------------------------------------------------------------- data("WilPat2") WilPat2$Age <- cut(WilPat2$Age, breaks = c(17, 20, 23, 30, 40, 100), labels = 1:5) head(WilPat2) ## ----------------------------------------------------------------------------- levelvec <- c(rep("nominal", 6), "nominal", "metric", "metric", "nominal", "ordinal") wen_prin <- princals(WilPat2, levels = levelvec) ## fit 2D princals wen_prin summary(wen_prin) ## ----fig.height=7, fig.width=7------------------------------------------------ plot(wen_prin, plot.type = "transplot", var.subset = c(1, 8, 9, 11)) ## ----fig.height=7, fig.width=7------------------------------------------------ plot(wen_prin, plot.type = "jointplot", expand = 0.08) ## ----fig.height=7, fig.width=7------------------------------------------------ plot(wen_prin, "objplot", cex.scores = 0.6)