R中的时间序列

ts()对象具有一些限制.最值得注意的是，它不接受每次观察的时间戳.而是，它请求一个start和freq(end是可选的).此外，freq功能仅限于按季节查看数据.

Time Series in R

The ts() object has a few limitations. Most notably, it doesn't accept time stamps per observation. Instead, it requests a start and freq (the end is optional). Furthermore, the freq capabilities are limited to viewing data in terms of seasons.

Type      Frequency 
Annual     1
Quarterly  4
Monthly   12
Weekly    52

因此，要生成正确的季节"，我们将必须计算每日季节性，其中freq=1440(= 24 * 60).之后，它变得更加复杂.

Thus, to generate the correct "season" we would have to calculate a daily seasonality where freq=1440 (=24*60). It gets a bit more complicated after that.

因此，我强烈建议使用xts或zoo对象创建时间序列.

As a result, I would highly suggest creating the time series with an xts or zoo object.

接下来，出现窗口问题的原因之一是您提供的日期是字符串，而不是 POSIXct 或 POSIXlt 目的.优先考虑.

Next up, one of the reasons for your windowing issues is the date you are supplying is a string and not a POSIXct or POSIXlt object. The prior of which is preferred.

可以找到完整的细分:

as.POSIXct之间的差异/as.POSIXlt和strptime，用于将字符向量转换为POSIXct/POSIXlt

处理R中的时间戳

话虽如此，第一步是将数据从字符格式转换为 POSIXct

With that being said, one of the first steps is to convert your data from character form to POSIXct

# Convert to POSXICT
SampleData$DateTime = as.POSIXct(strptime(SampleData$DateTime, format ="%Y-%m-%d %H:%M"))

开窗

从那里开始，如果我们创建xts()对象，则窗口问题变得微不足道.

Windowing

From there, the windowing issue becomes trivial if we create a xts() object.

# install.packages("xts")
require(xts)

# Create an XTS object to hold the time series
sdts = xts(SampleData$MedTime, order.by = SampleData$DateTime)

# Subset training
train = window(sdts,end= as.POSIXct('2015-01-21 23:00', format ="%Y-%m-%d %H:%M"))