seasonal is an easy-to-use and full-featured R interface to X-13ARIMA-SEATS, the seasonal adjustment software developed by the United States Census Bureau. The latest CRAN version of seasonal fixes several bugs and makes it easier to access output from multiple objects. See here for a complete list of changes.
Photo by Aaron Burden
seas() is the core function of the
seasonal package. By
default, seas() calls the automatic procedures of X-13ARIMA-SEATS to
perform a seasonal adjustment that works well in most circumstances:
library(seasonal)
seas(AirPassengers)
For a more detailed introduction, read our article in the Journal of Statistical Software.
Multiple series adjustment
The previous version has introduced the adjustment of multiple
series in a
single call to seas(). This has removed the need for loops or
lapply() in such cases and finally brought the composite spec to
seasonal.
As Brian Monsell pointed out, this was not enough to access the output from the composite spec. The latest CRAN version fixes this problem.
Multiple adjustments can be performed by supplying multiple time series
as an "mts" object:
library(seasonal)
m0 <- seas(cbind(fdeaths, mdeaths), x11 = "")
final(m0)
fdeaths mdeaths
Jan 1974 614.1235 1598.740
Feb 1974 542.3500 1492.127
Mar 1974 613.5029 1443.238
Apr 1974 591.5725 1694.643
May 1974 607.4970 1696.021
Jun 1974 543.8415 1558.886
Jul 1974 597.0745 1663.176
Aug 1974 587.0533 1623.498
Sep 1974 588.2693 1741.394
Oct 1974 735.6666 1735.516
Nov 1974 602.0218 1665.590
Dec 1974 496.3985 1394.097
Jan 1975 564.0055 1560.605
Feb 1975 591.0320 1708.763
Mar 1975 585.7739 1652.994
Apr 1975 581.5294 1671.265
May 1975 537.8055 1588.605
Jun 1975 584.3284 1600.979
Jul 1975 566.4872 1541.099
Aug 1975 617.1197 1623.445
Sep 1975 516.4781 1521.497
Oct 1975 559.0481 1577.200
Nov 1975 561.6315 1602.659
Dec 1975 580.9778 1569.692
Jan 1976 519.8106 1477.855
Feb 1976 882.3725 2180.616
Mar 1976 674.5057 1744.114
Apr 1976 467.4502 1366.628
May 1976 509.7854 1344.809
Jun 1976 553.5233 1434.662
Jul 1976 503.2795 1447.952
Aug 1976 494.2373 1383.932
Sep 1976 529.1840 1453.496
Oct 1976 570.4128 1435.912
Nov 1976 590.4285 1540.551
Dec 1976 587.0971 1572.631
Jan 1977 583.2427 1607.153
Feb 1977 498.9514 1287.403
Mar 1977 500.4632 1306.324
Apr 1977 569.2076 1685.581
May 1977 565.6470 1405.231
Jun 1977 509.3196 1432.968
Jul 1977 548.4062 1414.216
Aug 1977 523.6985 1444.945
Sep 1977 563.3014 1402.720
Oct 1977 495.6653 1427.458
Nov 1977 453.9859 1307.828
Dec 1977 502.3045 1268.618
Jan 1978 535.2658 1415.724
Feb 1978 633.7605 1790.002
Mar 1978 559.2936 1469.883
Apr 1978 485.5062 1343.715
May 1978 590.4080 1509.166
Jun 1978 574.4467 1464.288
Jul 1978 571.2263 1428.398
Aug 1978 542.3579 1424.622
Sep 1978 551.2099 1422.428
Oct 1978 557.6905 1399.404
Nov 1978 479.8979 1199.762
Dec 1978 550.4253 1397.023
Jan 1979 548.9834 1557.853
Feb 1979 576.9922 1425.717
Mar 1979 549.3468 1393.788
Apr 1979 546.4590 1449.784
May 1979 525.9881 1359.843
Jun 1979 550.2481 1330.113
Jul 1979 533.7558 1373.156
Aug 1979 566.6884 1381.653
Sep 1979 552.6500 1377.175
Oct 1979 533.9571 1337.640
Nov 1979 557.9707 1414.101
Dec 1979 475.5049 1038.506
This performs two seasonal adjustments, one for fdeaths and one for
mdeaths. The vignette on multiple
adjustments
describes how to specify options for individual series.
Accessing composite output
The composite argument is a list with an X-13 specification applied to
the aggregated series:
m1 <- seas(
cbind(mdeaths, fdeaths),
composite = list(),
series.comptype = "add"
)
With version 1.9 can now use out() to access the output of the
composite spec:
out(m1)
We can also use series(), e.g., to access the final, indirectly
adjusted series via the composite spec (see ?series for all
available series):
series(m1, "composite.indseasadj")
To speed up, extend the `seas()` call (see ?series):
seas(x = cbind(mdeaths, fdeaths), composite = list(), series.comptype = "add", To speed up, extend the `seas()` call (see ?series):
composite.save = "isa")
Jan Feb Mar Apr May Jun Jul Aug
1974 2172.614 2053.613 2057.679 2284.821 2260.974 2105.191 2240.895 2185.517
1975 2098.251 2298.581 2213.878 2256.802 2111.628 2181.738 2098.883 2219.083
1976 1969.128 3078.359 2373.028 1846.802 1851.167 1983.231 1943.369 1872.025
1977 2132.860 1807.832 1795.898 2262.793 1957.817 1940.262 1949.784 1953.665
1978 1908.154 2431.050 2007.252 1830.715 2077.654 2033.120 1987.875 1956.487
1979 2061.627 1997.557 1925.365 1984.834 1885.778 1882.208 1903.203 1937.474
Sep Oct Nov Dec
1974 2296.345 2395.347 2291.835 2013.749
1975 2024.988 2100.543 2181.495 2234.826
1976 1967.742 1973.567 2151.597 2199.389
1977 1946.642 1894.848 1807.119 1808.051
1978 1959.824 1928.748 1724.336 1966.847
1979 1925.618 1846.713 1991.679 1517.027