将时间序列对象转换为矩阵答案

【问题标题】：converting time series object to matrix将时间序列对象转换为矩阵
【发布时间】：2019-04-13 16:23:34
【问题描述】：

我正在尝试将时间序列对象转换为矩阵。

births <- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat")

birthstimeseries <-ts(matrix(births, frequency=12, start=c(1946,1)))

此代码生成错误为：

Error in matrix(births, start = c(1946, 1)) : 
  unused argument (start = c(1946, 1))

但是

birthstimeseries <- ts(births,start=c(1946,1), frequency = 12) 生成时间序列对象。

data.matrix(birthstimeseries)。它生成一维数据。如何将此数据框的行数和列数保存到矩阵中。

我想要这样的结果作为矩阵。

    Jan    Feb    Mar    Apr    May    Jun    Jul    Aug    Sep    Oct    Nov    Dec
1946 26.663 23.598 26.931 24.740 25.806 24.364 24.477 23.901 23.175 23.227 21.672 21.870
1947 21.439 21.089 23.709 21.669 21.752 20.761 23.479 23.824 23.105 23.110 21.759 22.073

【问题讨论】：

@akrun - 抱歉过早发布。你现在可以检查。第一个birthstimeseries 产生错误。
谢谢，知道了。如果我不想硬编码 14 怎么办？
谢谢，真的很有帮助

标签： r matrix time-series

【解决方案1】：

一种选择是将split的时间序列由cycle（列索引）转换成list，然后将cbind和cbind一起设置为dimnames

t2 <- do.call(cbind, split(t1, cycle(t1)))
dimnames(t2) <- dimnames(.preformat.ts(t1))
t2
#        Jan    Feb    Mar    Apr    May    Jun    Jul    Aug    Sep    Oct    Nov    Dec
#1946 26.663 23.598 26.931 24.740 25.806 24.364 24.477 23.901 23.175 23.227 21.672 21.870
#1947 21.439 21.089 23.709 21.669 21.752 20.761 23.479 23.824 23.105 23.110 21.759 22.073
#1948 21.937 20.035 23.590 21.672 22.222 22.123 23.950 23.504 22.238 23.142 21.059 21.573
#1949 21.548 20.000 22.424 20.615 21.761 22.874 24.104 23.748 23.262 22.907 21.519 22.025
#1950 22.604 20.894 24.677 23.673 25.320 23.583 24.671 24.454 24.122 24.252 22.084 22.991
#1951 23.287 23.049 25.076 24.037 24.430 24.667 26.451 25.618 25.014 25.110 22.964 23.981
#1952 23.798 22.270 24.775 22.646 23.988 24.737 26.276 25.816 25.210 25.199 23.162 24.707
#1953 24.364 22.644 25.565 24.062 25.431 24.635 27.009 26.606 26.268 26.462 25.246 25.180
#1954 24.657 23.304 26.982 26.199 27.210 26.122 26.706 26.878 26.152 26.379 24.712 25.688
#1955 24.990 24.239 26.721 23.475 24.767 26.219 28.361 28.599 27.914 27.784 25.693 26.881
#1956 26.217 24.218 27.914 26.975 28.527 27.139 28.982 28.169 28.056 29.136 26.291 26.987
#1957 26.589 24.848 27.543 26.896 28.878 27.390 28.065 28.141 29.048 28.484 26.634 27.735
#1958 27.132 24.924 28.963 26.589 27.931 28.009 29.229 28.759 28.405 27.945 25.912 26.619
#1959 26.076 25.286 27.660 25.951 26.398 25.565 28.865 30.000 29.261 29.012 26.992 27.897


is.matrix(t2)
#[1] TRUE

在哪里

t1  <- birthstimeseries

【讨论】：