## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) set.seed(72604204) ## ----------------------------------------------------------------------------- library(AssocBin) ## ----------------------------------------------------------------------------- data(heart) summary(heart) ## ----------------------------------------------------------------------------- heartClean <- heart heartClean$thal <- NULL heartClean$ca <- NULL heartClean$slope <- NULL heartClean <- na.omit(heartClean) str(heartClean) ## ----------------------------------------------------------------------------- stopCrits <- makeCriteria(depth >= 6, n < 1, expn <= 10) assocs <- inDep(heartClean, stopCriteria = stopCrits) ## ----------------------------------------------------------------------------- summary(assocs) ## ----fig.width = 5, fig.height = 8-------------------------------------------- plot(assocs) # by default this displays the 5 strongest relationships ## ----fig.width = 5, fig.height = 8-------------------------------------------- ## by specifying which indices should be displayed, others can be plotted ## the binnings are returned in increasing order of p-value, so the indices ## chosen give the rank of the strength a particular pair's relationship plot(assocs, which = 6:10) # like the next 5 strongest plot(assocs, which = 62:66) # or the 5 weakest relationships ## ----------------------------------------------------------------------------- maxCatCon <- function(bn) uniMaxScoreSplit(bn, chiScores) maxConCon <- function(bn) maxScoreSplit(bn, chiScores) maxPairs <- inDep(data = heartClean, stopCriteria = stopCrits, catCon = maxCatCon, conCon = maxCatCon) summary(maxPairs) ## ----fig.width = 5, fig.height = 8-------------------------------------------- plot(maxPairs) plot(maxPairs, which = 6:10) ## ----fig.width = 5, fig.height = 5-------------------------------------------- randOrd <- match(assocs$pairs, assocs$pairs) maxOrd <- match(assocs$pairs, maxPairs$pairs) plot(randOrd, maxOrd, xlab = "Random rank", ylab = "Max chi rank", main = "Rankings of pair significance between methods") ## ----------------------------------------------------------------------------- heartCleve <- heartClean[heartClean$study == "cleveland", ] heartCleve$study <- NULL cleveAssoc <- inDep(heartCleve, stopCriteria = stopCrits, catCon = maxCatCon, conCon = maxConCon) summary(cleveAssoc) ## ----fig.width = 5, fig.height = 8-------------------------------------------- plot(cleveAssoc) plot(cleveAssoc, which = 6:10) plot(cleveAssoc, which = 11:15)