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Basic Lag TS Object in R not "working"

开发者 https://www.devze.com 2023-01-29 04:06 出处:网络
Here is some basic info about my data > prod.ts Time Series: Start = 2009.26027397260 End = 2010.83719704953

Here is some basic info about my data

> prod.ts
Time Series:
Start = 2009.26027397260 
End = 2010.83719704953 
Frequency = 52 
 [1]  895 1780 1989 1996 1660 1860 1921 2188 1789 1996 2085 2185 2205 2232 2062
[16] 2257 2000 2055 2084 1977 2051 1999 2428 2220 2385 2174 2307 2549 2211 开发者_StackOverflow社区2224
[31] 1922 2091 2318 1986 2080 2069 2106 1998 1480 1841 1819 2119 2109 2072 2206
[46] 1965 2017 2296 1866 2262 2088 2157 2582 2398 2325 1393 2577 2375 2452 2534
[61] 2586 2032 2781 2423 2575 2362 2132 2375 2105 2425 2346 2495 2908 2301 2918
[76] 2426 2633 2312 2472 2305 2622 2662 2626

I am stumped as to why these two are equivlane

> length(prod.ts)
[1] 83
> length(lag(prod.ts, 1))
[1] 83

This probably shows that I am new to R and Time series, but what am I missing?

Thanks in advance


lag.ts lags the time index. The data is unchanged. Compare the series g and lag(g) below. Note that the data is the same but g goes from 1 to 5 and lag(g) goes from 0 to 4:

> g <- ts(101:105)
> g
Time Series:
Start = 1 
End = 5 
Frequency = 1 
[1] 101 102 103 104 105
> lag(g)
Time Series:
Start = 0 
End = 4 
Frequency = 1 
[1] 101 102 103 104 105


That is just the way lag() for ts objects is defined. From help(lag):

lag                   package:stats                    R
Documentation

Lag a Time Series

Description:

     Compute a lagged version of a time series, shifting the time base
     back by a given number of observations.

Use xts() or zoo() if you'd rather have NAs added while keeping start and end times.

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