## ----opts = TRUE, setup = TRUE, include = FALSE------------------------------- knitr::opts_chunk$set(echo = TRUE, comment = "") ## ----eval=FALSE--------------------------------------------------------------- # install.packages("zebu") ## ----------------------------------------------------------------------------- library(zebu) ## ----------------------------------------------------------------------------- starter_prob <- c("Tomato Mozzarella Salad" = 1/3, "Rice Tuna Salad" = 1/3, "Lentil Salad" = 1/3) starter_prob ## ----------------------------------------------------------------------------- main_given_starter_prob <- matrix(c(5/11, 1/11, 5/11, 5/11, 5/11, 1/10, 1/11, 5/11, 5/11), 3, 3, byrow = TRUE) rownames(main_given_starter_prob) <- names(starter_prob) colnames(main_given_starter_prob) <- c("Sausage and Lentil Stew", "Pizza Margherita", "Pilaf Rice") main_given_starter_prob ## ----------------------------------------------------------------------------- dessert_given_main <- matrix(c(2/6, 2/6, 2/6, 7/12, 1/12, 2/6, 1/12, 7/12, 2/6), 3, 3, byrow = TRUE) rownames(dessert_given_main) <- colnames(main_given_starter_prob) colnames(dessert_given_main) <- c("Rice Pudding", "Apple Pie", "Fruit Salad") dessert_given_main ## ----------------------------------------------------------------------------- set.seed(0) sample_size <- 1000 df <- t(sapply(seq_len(sample_size), function(i) { starter <- sample(names(starter_prob), size = 1, prob = starter_prob) main <- sample(colnames(main_given_starter_prob), size = 1, prob = main_given_starter_prob[starter, ]) dessert <- sample(colnames(dessert_given_main), size = 1, prob = dessert_given_main[main, ]) c(Starter = starter, Main = main, Dessert = dessert) })) df <- as.data.frame(df) ## ----------------------------------------------------------------------------- head(df) ## ----------------------------------------------------------------------------- table(df) ## ----------------------------------------------------------------------------- las <- lassie(df, select = c("Main", "Dessert"), measure = "z") ## ----------------------------------------------------------------------------- las <- permtest(las, nb = 5000, p_adjust = "BH") ## ----plot-local-association--------------------------------------------------- print(las) plot(las) ## ----------------------------------------------------------------------------- las2 <- lassie(df, measure = "z") las2 <- permtest(las2, nb = 5000) print(las2, what_sort = "local_p", decreasing = FALSE)