【发布时间】:2015-03-17 13:44:34
【问题描述】:
我正在尝试从长格式的 data.frame 中预测单个变量。我陷入了循环 [apply] 部分。问题是:如何用应用替换手动预测?
library(forecast)
library(data.table)
# get time series
www = "http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/cbe.dat"
cbe = read.table(www, header = T)
# in this case, there is a data.frame in long format to start with
df = data.table(cbe[, 2:3])
df[, year := 1958:1990]
dfm = melt(df, id.var = "year", variable.name = "indicator", variable.factor = F) # will give warning because beer = num and others are int
dfm[, site := "A"]
dfm2= copy(dfm) # make duplicate to simulate other site
dfm2[, site := "B"]
dfm = rbind(dfm, dfm2)
# function to make time series & forecast
f.forecast = function(df, mysite, myindicator, forecast.length = 6, frequency = freq) {
# get site and indicator
x = df[site == mysite & indicator == myindicator,]
# convert to time series
start.date = min(x$year)
myts = ts(x$value, frequency = freq, start = start.date)
# forecast
myfc = forecast(myts, h = forecast.length, fan = F, robust = T)
plot(myfc, main = paste(mysite, myindicator, sep = " / "))
grid()
return(myfc)
}
# the manual solution
par(mfrow = c(2,1))
f1 = f.forecast(dfm, mysite = "A", myindicator = "beer", forecast.length = 6, freq = 12)
f2 = f.forecast(dfm, mysite = "A", myindicator = "elec", forecast.length = 6, freq = 12)
# how to loop? [in the actual data set there are many variables per site]
par(mfrow = c(2,1))
myindicators = unique(dfm$indicator)
sapply(myindicator, f.forecast(dfm, "A", myindicator = myindicators, forecast.length = 6, freq = 12)) # does not work
【问题讨论】:
-
您只是在寻找
sapply(myindicators, function(i) f.forecast(dfm, "A", myindicator = i, forecast.length = 6, freq = 12))吗?
标签: r forecasting