Alp*_*pha 5 r window time-series
我发现的大多数软件包和帖子均适用于固定大小的窗口或月/周汇总数据。可以计算滚动k个月的平均值吗?
例如,对于1个月的滚动窗口,假设数据为:
Date Value
2012-05-28 101
2012-05-25 99
2012-05-24 102
....
2012-04-30 78
2012-04-27 82
2012-04-26 77
2012-04-25 75
2012-04-24 76
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前三个1个月滚动窗口应为:
1. 2012-05-28 to 2012-04-30
2. 2012-05-25 to 2012-04-26
3. 2012-05-24 to 2012-04-25
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请注意,这不是固定宽度的滚动窗口。该窗口实际上每天都会更改。
我使用此代码根据每日价格数据计算每月平均值。
#function for extracting month is in the lubridate package
install.packages(c("plyr", "lubridate"))
require(plyr); require(lubridate)
#read the daily data
daily = read.csv("daily_lumber_prices.csv")
price = daily$Open
date = daily$Date
#convert date to a usable format
date = strptime(date, "%d-%b-%y")
mon = month(date)
T = length(price)
#need to know when months change
change_month = rep(0,T)
for(t in 2:T){
if(mon[t] != mon[t-1]){
change_month[t-1] = 1
}
}
month_avg = rep(0,T)
total = 0
days = 0
for(t in 1:T){
if(change_month[t] == 0){
#cumulative sums for each variable
total = total + price[t]
days = days + 1
}
else{
#need to include the current month in the calculation
month_avg[t] = (total + price[t]) / (days + 1)
#reset the variables
total = 0
days = 0
}
}
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因此,变量month_avg 存储每月平均值。
是这样的吗?此代码考虑了月份的可变长度。当然有一种更有效的方法来做到这一点,但这确实有效!