ChangeAnomalyDetection サンプル

パッケージ読み込み

library(ChangeAnomalyDetection)

## Loading required package: TTR

## Loading required package: xts

## Loading required package: zoo

## Attaching package: 'zoo'

## The following object(s) are masked from 'package:base':
## 
## as.Date, as.Date.numeric

library(ggplot2)

## Find out what's changed in ggplot2 with news(Version == "0.9.0", package =
## "ggplot2")

library(RFinanceYJ)

## Loading required package: XML

library(reshape2)

株価情報の取得

yahoo <- quoteStockXtsData("4689.t", since = "2011-01-01")
head(yahoo)

##             Open  High   Low Close Volume AdjClose
## 2011-01-04 31650 31850 31500 31700  59831    31700
## 2011-01-05 31050 31400 30150 30200 160383    30200
## 2011-01-06 30200 30600 30050 30250 114564    30250
## 2011-01-07 30250 30550 30100 30200  77564    30200
## 2011-01-11 30100 30550 29560 30450 106584    30450
## 2011-01-12 30600 30900 30500 30750  69012    30750

yahoo <- as.data.frame(yahoo)
yahoo$date <- as.POSIXct(rownames(yahoo))

終値をプロット

ggplot(yahoo, aes(x = date, y = Close)) + geom_line()

異常スコア算出

change.score <- changeAnomalyDetection(x = yahoo$Close, 
    term = 30, order = c(1, 1, 0))
tail(change.score)

## [1] -0.1897 -0.3702 -0.3717 -0.3783 -0.3589 -0.3209

yahoo$change.score <- change.score

異常スコアの推移

ggplot(yahoo, aes(x = date, y = change.score)) + 
    geom_line()

整形

ggplotで同時にプロットするために、少し加工する。
この手の整形は、reshape2パッケージのmelt関数が便利

yahoo <- yahoo[yahoo$change.score != 0, ]
yahoo$change.score <- yahoo$change.score * 2000 + 
    10000
yahoo.melt <- melt(yahoo, id.vars = "date", measure.vars = c("Close", 
    "change.score"))

同時にプロット

ggplot(yahoo.melt, aes(x = date, y = value)) + 
    geom_line(aes(col = variable))