513 lines
18 KiB
R
513 lines
18 KiB
R
load(file = "tweets_untagged.RData")
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setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
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results_files <- "matched-ids/all.csv"
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load(file = "tweets_untagged.RData")
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View(issues)
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issues <- data.frame(date = drange)
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issuelist <- readLines("issues.xml")
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issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
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issuelist <- xmlToList(issuelist)
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issueheads <- names(issuelist)
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issues[issueheads] <- 0
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tweets$issue <- ""
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tweets$tags <- ""
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View(results)
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rm(r, results_temp, results_files)
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results <- results[!duplicated(results), ]
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names(results) <- c("date", "id_str", "issue", "tags")
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results <- results[order(results$id_str), ]
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row.names(results) <- NULL
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for(r in 1:nrow(results)) {
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curdate <- as.character(results$date[r])
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curid <- as.character(results$id_str[r])
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curissue <- as.character(results$issue[r])
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curtag <- as.character(results$tags[r])
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cat("Sorting match", r, "of 53383 \n")
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# Update issue counter (date and issue)
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issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
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# Update tweet dataframe (id, issue and tags)
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oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
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tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ",")
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oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
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tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ",")
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}
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curdate
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curissue
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issues[issues[, "date"] == curdate, curissue]
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issueheads
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issuelist <- readLines("issues-v2.xml")
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issues <- data.frame(date = drange)
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issuelist <- readLines("issues-v2.xml")
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issuelist <- str_replace_all(string = issuelist, pattern = ".*<!-- .+ -->", "")
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issuelist <- xmlToList(issuelist)
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issueheads <- names(issuelist)
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issues[issueheads] <- 0
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tweets$issue <- ""
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tweets$tags <- ""
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for(r in 1:nrow(results)) {
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curdate <- as.character(results$date[r])
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curid <- as.character(results$id_str[r])
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curissue <- as.character(results$issue[r])
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curtag <- as.character(results$tags[r])
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cat("Sorting match", r, "of 53383 \n")
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# Update issue counter (date and issue)
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issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
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# Update tweet dataframe (id, issue and tags)
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oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
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tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ",")
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oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
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tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ",")
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}
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results[33170,]
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results[33171,]
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results$date[33170]
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results$date[33170] <- "2014-08-21"
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for(r in 33170:nrow(results)) {
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curdate <- as.character(results$date[r])
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curid <- as.character(results$id_str[r])
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curissue <- as.character(results$issue[r])
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curtag <- as.character(results$tags[r])
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cat("Sorting match", r, "of 53383 \n")
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# Update issue counter (date and issue)
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issues[issues[, "date"] == curdate, curissue] <- issues[issues[, "date"] == curdate, curissue] + 1
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# Update tweet dataframe (id, issue and tags)
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oldissue <- tweets[tweets[, "id_str"] == curid, "issue"]
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tweets[tweets[, "id_str"] == curid, "issue"] <- str_c(oldissue, curissue, ",")
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oldtag <- tweets[tweets[, "id_str"] == curid, "tags"]
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tweets[tweets[, "id_str"] == curid, "tags"] <- str_c(oldtag, curtag, ",")
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}
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save(tweets, file="tweets_tagged.RData")
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write.csv(tweets, file="tweets.csv")
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save(issues, file="issues.RData")
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require(stringr)
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require(reshape2)
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require(ggplot2)
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require(vars)
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drop_s <- which(str_detect(names(issues), "^s"))
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drop_i <- which(str_detect(names(issues), "^i"))
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issues_i <- issues[,-drop_s]
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issues_s <- issues[,-drop_i]
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issues_i$total <- rowSums(issues_i[2:ncol(issues_i)])
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issues_i$entropy <- 0
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for(r in 1:nrow(issues_i)) {
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curtotal <- as.numeric(issues_i$total[r])
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curp <- 0
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for(c in 2:ncol(issues_i)) {
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curcount <- as.numeric(issues_i[r,c])
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curp[c] <- curcount / curtotal
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}
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curp <- curp [2:length(curp)-2]
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curdrop <- which(curp==0)
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curp <- curp[-curdrop]
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issues_i$entropy[r] <- sum(-1 * curp * log(curp))
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}
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issues_s$total <- rowSums(issues_s[2:ncol(issues_s)])
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issues_s$entropy <- 0
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for(r in 1:nrow(issues_s)) {
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curtotal <- as.numeric(issues_s$total[r])
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curp <- 0
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for(c in 2:ncol(issues_s)) {
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curcount <- as.numeric(issues_s[r,c])
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curp[c] <- curcount / curtotal
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}
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curp <- curp [2:length(curp)-2]
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curdrop <- which(curp==0)
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curp <- curp[-curdrop]
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issues_s$entropy[r] <- sum(-1 * curp * log(curp))
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}
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stats_total <- data.frame(date=drange)
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stats_total$tpd <- 0
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stats_total$ipd <- issues_i$total
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stats_total$spd <- issues_s$total
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# Total number of tweets per day over time
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for(r in 1:length(drange)) {
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stats_total$tpd[r] <- length(tweets[tweets[, "created_at"] == drange[r], "id_str"])
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}
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g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
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geom_line()+
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geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
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g1
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stats_entropy <- data.frame(date=drange)
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stats_entropy$entropy <- issues_i$entropy
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stats_entropy <- melt(stats_entropy, id="date")
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g1 <- ggplot(data = stats_entropy, aes(x=date,y=value,colour=variable, group=variable)) +
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geom_line() +
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geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
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g1
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test <- VAR(issues[,2:32], p=1, type="none")
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View(issues_i)
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View(issues_s)
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View(issues)
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test <- VAR(issues[,2:44], p=1, type="none")
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VAR(issues_s[,2:23], p=1, type=c("const", "trend", "both", "none"), season=NULL, exogen = issues_i[2:22])
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plot(irf(test, impulse = names(issues_s[2:23]), response = names(issues_i[2:22])))
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rm(c_correct, c_curissue, c_errcode, c_errid, c_errissue, c_error1, c_error2, c_errors)
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rm(c_issues, c_issuelist, c_issueheads)
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rm(c_errtags, c_errtext, c_result, c_tag, c_tmp, c_tweets)
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require(stringr)
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require(XML)
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readYN <- function(question) {
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n <- readline(prompt=question)
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n <- as.character(n)
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return(n)
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}
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checkIssue <- function(string, issuelist) {
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status <- any(str_detect(string, issuelist))
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return(status)
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}
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checkAllIssues <- function(string, issuelist) {
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status <- NULL
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for(i in 1:length(string)) {
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if(checkIssue(string[i], issuelist)) {
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status[i] <- TRUE
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}
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else {
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cat("Issue",string[i],"does not exist. Please try again.\n")
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status[i] <- FALSE
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}
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}
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return(status)
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}
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View(tweets)
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c_tweets <- read.csv("tweets.csv", colClasses="character")
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for(r in 1:nrow(c_tweets)) {
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curtext <- as.character(c_tweets$text[r])
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if(str_detect(curtext, "\"")) {
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c_tweets$text[r] <- str_replace(curtext, "\"", "")
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}
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}
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c_tweets$X <- NULL
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c_issues <- data.frame(date = drange)
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c_issuelist <- xmlToList("issues-v2.xml")
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c_issueheads <- names(issuelist)
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c_issues[issueheads] <- 0
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source("issuecomp-codingsample-function.R")
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require(stringr)
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curtext
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curtext <- str_replace_all(curtext, "#", "")
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curtext <- str_replace_all(curtext, "-", " ")
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curtext
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curtext
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str_replace_all(curtext, "[^[:alnum:]]", "")
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str_replace_all(curtext, "[^[:alnum:]\s]", "")
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str_replace_all(curtext, "[^[:alnum:]\\s]", "")
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str_replace_all(curtext, "[^[:alnum:]^\\s]", "")
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str_replace_all(curtext, "[^[:alnum:]^\\S]", "")
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str_replace_all(curtext, "[^[:alnum:]][^\\s]", "")
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str_replace_all(curtext, "[^[:alnum:]][^\\S]", "")
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str_replace_all(curtext, "[^[:alnum:]][^[:blank]]", "")
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str_replace_all(curtext, "[^[:alnum:]][^[:blank:]]", "")
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str_replace_all(curtext, "[^[:alnum:]]", "")
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str_replace_all(curtext, "\\W", "")
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str_replace_all(curtext, "[\\W|\\S]", "")
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str_replace_all(curtext, "(\\W|\\S)", "")
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str_replace_all(curtext, "\\W|\\S", "")
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str_replace_all(curtext, "\\W", "")
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str_replace_all(curtext, "[\\W\\S]", "")
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str_replace_all(curtext, "[\\S\\W]", "")
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str_replace_all(curtext, "[\\s\\W]", "")
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str_replace_all(curtext, "[\\W\\s]", "")
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str_replace_all(curtext, "[\\W\s]", "")
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str_replace_all(curtext, "[\\Ws]", "")
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str_replace_all(curtext, "[\\W]", "")
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str_replace_all(curtext, "\\W", "")
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str_replace_all(curtext, "\\W|\\S", "")
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str_replace_all(curtext, "\\W|\\s", "")
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str_replace_all(curtext, "[^[:alnum:]]", "")
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str_replace_all(curtext, "[^[:alnum:] ]", "")
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str_replace_all(curtext, "[^[:alnum:]\\s]", "")
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str_replace_all(curtext, "[^[:alnum:] ]", "")
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curtext
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curtext <- "liebe @cdu, wir finden #Steuer gut, aber die KFZ-Steuer nicht!"
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curtext <- str_replace_all(curtext, "-", " ")
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curtext <- str_replace_all(curtext, "[^[:alnum:] ]", "")
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curtext
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curtext <- "liebe @cdu, wir finden #Steuer gut, aber die KFZ--Steuer nicht!"
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curtext <- str_replace_all(curtext, "-", " ")
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curtext <- str_replace_all(curtext, "[^[:alnum:] ]", "")
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curtext
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str_replace_all(curtext, " ", " ")
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smartPatternMatch
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require(vars)
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require(stringr)
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adf1 <- summary(ur.df(issues))
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issues
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summary(issues)
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summary(issues[2:44])
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summary(issues[2:44], digits = 2)
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adf1 <- summary(ur.df(issues[, 2:44]), type ="trend", lags=1)
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data("Canda")
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data("Canada")
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class(Canada)
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class(issues)
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view(Canada)
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View(Canada)
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as.ts(issues)
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issues_ts <- as.ts(issues)
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class(issues_ts)
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View(issues_ts)
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View(issues)
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adf1 <- summary(ur.df(issues_ts[, 2:44]), type ="trend", lags=1)
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adf1 <- summary(ur.df(issues_ts[, 2]), type ="trend", lags=1)
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adf1 <- summary(ur.df(issues_ts[, 2], type ="trend", lags=1))
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adf1 <- summary(ur.df(issues_ts[, 2:44], type ="trend", lags=1))
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adf1 <- summary(ur.df(issues_ts[, 2], type ="trend", lags=1))
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adf1
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adf1 <- summary(ur.df(issues_ts[, 3], type ="trend", lags=1))
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adf1
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adf1 <- summary(ur.df(issues_ts[, 2], type ="none", lags=1))
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adf1
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adf1 <- summary(ur.df(issues_ts[, 2], type ="trend", lags=1))
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adf1
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summary(ur.df(issues_ts[, 2], type ="none", lags=1))
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VARselect(issues_ts[2:44], lag.max = 8, type = "both")
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VARselect(issues_ts[1:44], lag.max = 8, type = "both")
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VARselect(issues[1:44], lag.max = 8, type = "both")
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VARselect(issues[2:44], lag.max = 8, type = "both")
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VARselect(issues_ts[2:44], lag.max = 8, type = "both")
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VARselect(issues[2:44], lag.max = 8, type = "none")
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VARselect(issues[2:44], lag.max = 8, type = "trend")
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VARselect(issues[2:44], lag.max = 8, type = "const")
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VARselect(issues[2:44], lag.max = 8, type = "both")
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test <- VAR(issues[,2:44], p=1, type="both")
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# VAR(issues_s[,2:23], p=1, type=c("const", "trend", "both", "none"), season=NULL, exogen = issues_i[2:22])
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plot(irf(test, impulse = names(issues_s[2:23]), response = names(issues_i[2:22])))
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summary(ur.df(issues_ts[, 2], type ="both", lags=1))
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summary(ur.df(issues_ts[, 2], type ="none", lags=1))
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test <- VAR(issues_ts[,2:44], p=1, type="both")
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plot(irf(test, impulse = names(issues_s[2:23]), response = names(issues_i[2:22])))
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acc_df <- read.csv("MdB-twitter.csv")
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delrow <- NULL
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for(r in 1:nrow(acc_df)) {
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acc <- as.character(acc_df$twitter_acc[r])
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if(!nzchar(acc)) {
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delrow <- c(delrow, r)
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}
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}
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acc_df <- acc_df[-delrow, ]
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rm(delrow, r, acc)
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acc_df$row.names <- NULL
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row.names(acc_df) <- NULL
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View(acc_df)
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View(c_tweets)
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issueheads
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length(issueheads)
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issuelist
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length(issuelist)
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length(issuelist[*])
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length(issuelist[[*]])
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length(issuelist[1:43])
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length(issuelist[1)
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length(issuelist[1])
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length(issuelist[2])
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length(issuelist[[1]])
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length(issuelist[[2]])
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length(issuelist[[70]])
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length(issuelist[[43]])
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length(issuelist[[44]])
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length(issuelist[[1:43]])
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length(issuelist[[1-43]])
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length(issuelist[[2]])
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test <- 0
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num <- 0
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for(i in 1:length(issuelist)) {
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j <- length(issuelist[[i]])
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num <- num + j
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rm(j)
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}
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num
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drop_s <- which(str_detect(names(issues), "^s"))
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drop_i <- which(str_detect(names(issues), "^i"))
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issues_i <- issues[,-drop_s]
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issues_s <- issues[,-drop_i]
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require(stringr)
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drop_s <- which(str_detect(names(issues), "^s"))
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drop_i <- which(str_detect(names(issues), "^i"))
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issues_i <- issues[,-drop_s]
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issues_s <- issues[,-drop_i]
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issues_i$total <- rowSums(issues_i[2:ncol(issues_i)])
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issues_i$entropy <- 0
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for(r in 1:nrow(issues_i)) {
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curtotal <- as.numeric(issues_i$total[r])
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curp <- 0
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for(c in 2:ncol(issues_i)) {
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curcount <- as.numeric(issues_i[r,c])
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curp[c] <- curcount / curtotal
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}
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curp <- curp [2:length(curp)-2]
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curdrop <- which(curp==0)
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curp <- curp[-curdrop]
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issues_i$entropy[r] <- sum(-1 * curp * log(curp))
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}
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issues_s$total <- rowSums(issues_s[2:ncol(issues_s)])
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issues_s$entropy <- 0
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for(r in 1:nrow(issues_s)) {
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curtotal <- as.numeric(issues_s$total[r])
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curp <- 0
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for(c in 2:ncol(issues_s)) {
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curcount <- as.numeric(issues_s[r,c])
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curp[c] <- curcount / curtotal
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}
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curp <- curp [2:length(curp)-2]
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curdrop <- which(curp==0)
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curp <- curp[-curdrop]
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issues_s$entropy[r] <- sum(-1 * curp * log(curp))
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}
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stats_total <- data.frame(date=drange)
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stats_total$tpd <- 0
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stats_total$ipd <- issues_i$total
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stats_total$spd <- issues_s$total
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# Total number of tweets per day over time
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for(r in 1:length(drange)) {
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stats_total$tpd[r] <- length(tweets[tweets[, "created_at"] == drange[r], "id_str"])
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}
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stats_melt <- melt(stats_total, id="date")
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g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
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geom_line()+
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geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
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g1
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require(ggplot2)
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stats_melt <- melt(stats_total, id="date")
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g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
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geom_line()+
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geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
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g1
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g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
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geom_line()+
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geom_smooth(size=1,formula = y ~ x, method="lm", se=FALSE, color=1)
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g1
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g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
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geom_line()+
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geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
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g1
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# Visuals for entropy in time series
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stats_entropy <- data.frame(date=drange)
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stats_entropy$entropy <- issues_i$entropy
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stats_entropy <- melt(stats_entropy, id="date")
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require(reshape2)
|
|
stats_melt <- melt(stats_total, id="date")
|
|
g1 <- ggplot(data = stats_melt, aes(x=date,y=value,colour=variable, group=variable)) +
|
|
geom_line()+
|
|
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
|
|
g1
|
|
stats_entropy <- data.frame(date=drange)
|
|
stats_entropy$entropy <- issues_i$entropy
|
|
stats_entropy <- melt(stats_entropy, id="date")
|
|
g1 <- ggplot(data = stats_entropy, aes(x=date,y=value,colour=variable, group=variable)) +
|
|
geom_line() +
|
|
geom_smooth(size=1,formula = y ~ x, method="loess", se=FALSE, color=1)
|
|
g1
|
|
g1 <- ggplot(data = stats_entropy, aes(x=date,y=value,colour=variable, group=variable)) +
|
|
geom_line() +
|
|
geom_smooth(size=1,formula = y ~ x, method="lm", se=FALSE, color=1)
|
|
g1
|
|
vIssues <- VAR(issues_ts[,2:44], p=1, type="both")
|
|
require(vars)
|
|
VARselect(issues_ts, lag.max = 8, type = "both")
|
|
vIssues <- VAR(issues_ts[,2:44], p=1, type="both")
|
|
VARselect(issues_ts, lag.max = 16, type = "both")
|
|
VARselect(issues_ts, lag.max = 4, type = "both")
|
|
VARselect(issues_ts, lag.max = 5, type = "both")
|
|
VARselect(issues_ts, lag.max = 6, type = "both")
|
|
VARselect(issues_ts, lag.max = 5, type = "both")
|
|
names(issues_ts)
|
|
issues_ts
|
|
issues_ts[2:44]
|
|
issues_ts <- as.ts(issues[,2:44])
|
|
issues_ts[1:1]
|
|
issues_ts[,1]
|
|
issues_ts[1,1]
|
|
issues_ts2,1]
|
|
issues_ts[2,1]
|
|
issues_ts <- as.ts(issues[,2:44])
|
|
VARselect(issues_ts, lag.max = 5, type = "both")
|
|
VARselect(issues_ts, lag.max = 8, type = "both")
|
|
VARselect(issues_ts, lag.max = 7, type = "both")
|
|
VARselect(issues_ts, lag.max = 5, type = "both")
|
|
vIssues <- VAR(issues_ts[,2:44], p=5, type="both")
|
|
vIssues <- VAR(issues_ts, p=5, type="both")
|
|
plot(irf(vIssues, impulse = names(issues_s[2:23]), response = names(issues_i[2:22])))
|
|
require(stringr)
|
|
require(XML)
|
|
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
|
|
names(c_errors) <- c("str_id", "code", "issue", "tags", "text")
|
|
for(r in 1:nrow(c_errors)) {
|
|
c_errcode <- as.character(c_errors$code[r])
|
|
c_errissue <- as.character(c_errors$issue[r])
|
|
c_errtags <- as.character(c_errors$tags[r])
|
|
c_errtext <- as.character(c_errors$text[r])
|
|
c_errid <- as.character(c_errors$str_id[r])
|
|
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
|
|
source("issuecomp-codingsample-function2.R")
|
|
}
|
|
for(r in 1:nrow(c_errors)) {
|
|
c_errcode <- as.character(c_errors$code[r])
|
|
c_errissue <- as.character(c_errors$issue[r])
|
|
c_errtags <- as.character(c_errors$tags[r])
|
|
c_errtext <- as.character(c_errors$text[r])
|
|
c_errid <- as.character(c_errors$str_id[r])
|
|
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
|
|
source("issuecomp-codingsample-function2.R")
|
|
}
|
|
issueheads
|
|
for(i in 1:length(issueheads)) {paste(issueheads[i])}
|
|
for(i in 1:length(issueheads)) {cat(issueheads[i], "\n")}
|
|
for(r in 1:nrow(c_errors)) {
|
|
c_errcode <- as.character(c_errors$code[r])
|
|
c_errissue <- as.character(c_errors$issue[r])
|
|
c_errtags <- as.character(c_errors$tags[r])
|
|
c_errtext <- as.character(c_errors$text[r])
|
|
c_errid <- as.character(c_errors$str_id[r])
|
|
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
|
|
source("issuecomp-codingsample-function2.R")
|
|
}
|
|
for(r in 1:nrow(c_errors)) {
|
|
c_errcode <- as.character(c_errors$code[r])
|
|
c_errissue <- as.character(c_errors$issue[r])
|
|
c_errtags <- as.character(c_errors$tags[r])
|
|
c_errtext <- as.character(c_errors$text[r])
|
|
c_errid <- as.character(c_errors$str_id[r])
|
|
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
|
|
source("issuecomp-codingsample-function2.R")
|
|
}
|
|
c_errors <- read.csv("issuecomp-codingsample-error.csv", header = F, sep=",", colClasses="character")
|
|
names(c_errors) <- c("str_id", "code", "issue", "tags", "text")
|
|
for(r in 1:nrow(c_errors)) {
|
|
c_errcode <- as.character(c_errors$code[r])
|
|
c_errissue <- as.character(c_errors$issue[r])
|
|
c_errtags <- as.character(c_errors$tags[r])
|
|
c_errtext <- as.character(c_errors$text[r])
|
|
c_errid <- as.character(c_errors$str_id[r])
|
|
cat("===============\n\n[TWEET]: ",c_errtext,"\n[ISSUES]: ", c_errissue, " (", c_errtags, ")\n", sep="")
|
|
source("issuecomp-codingsample-function2.R")
|
|
}
|
|
c_tmp <- read.csv("issuecomp-codingsample-error1.csv", header = F, colClasses="character")
|
|
names(c_tmp) <- c("str_id", "all", "wrong", "tagged", "text")
|
|
c_error1 <- c_tmp[, c("wrong", "tagged", "all", "text")]
|
|
c_tmp <- read.csv("issuecomp-codingsample-error2.csv", header = F, colClasses="character")
|
|
names(c_tmp) <- c("str_id", "all", "missing", "tagged", "text")
|
|
c_error2 <- c_tmp[, c("missing", "text", "tagged", "all")]
|
|
View(c_error2)
|
|
summary(ur.df(issues_ts[, 2], type ="none", lags=1))
|
|
require(vars)
|
|
summary(ur.df(issues_ts[, 2], type ="none", lags=1))
|
|
stability(vIssues)
|
|
stability(vIssues[2:])
|
|
stability(vIssues[2:44])
|
|
plot(stability(vIssues))
|
|
class(vIssues)
|
|
summary(vIssues)
|
|
plot(stability(vIssues[2]))
|
|
plot(stability(vIssues), nc=2)
|
|
plot(stability(vIssues), h=0.15)
|
|
stability(vIssues)
|
|
efp(formula = formula, data = data, type = type, h = h, dynamic = dynamic,
|
|
rescale = rescale)
|
|
plot(stability(vIssues), h=0.15)
|
|
plot(stability(vIssues, h=0.15))
|
|
plot(stability(vIssues, h=0.15, rescale = TRUE))
|
|
plot(stability(vIssues, h=0.15, rescale = TRUE), nc=2)
|
|
par("mar")
|
|
par(mar=c(1,1,1,1))
|
|
plot(stability(vIssues, h=0.15, rescale = TRUE), nc=2)
|