Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sat, 29 Nov 2014 11:20:43 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/29/t1417260113d2geljsmvy5ksvt.htm/, Retrieved Sun, 19 May 2024 12:06:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261083, Retrieved Sun, 19 May 2024 12:06:15 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

125

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [] [2014-11-29 11:20:43] [fa76cbd0c9542d7a6f5f3c5daec42b95] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261083&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261083&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261083&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	75	NA	NA	2.21299	NA
2	84.3	NA	NA	2.45465	NA
3	84	NA	NA	-0.362014	NA
4	79.1	NA	NA	-1.53785	NA
5	78.8	NA	NA	-2.33868	NA
6	82.7	NA	NA	-3.38618	NA
7	85.3	79.9297	78.2958	1.63382	5.37035
8	84.5	79.748	77.7167	2.03132	4.75201
9	80.8	79.1772	76.7292	2.44799	1.62285
10	70.1	75.268	76	-0.732014	-5.16799
11	68.2	74.3355	75.8542	-1.51868	-6.13549
12	68.1	74.9238	75.8292	-0.905347	-6.82382
13	72.3	77.7922	75.5792	2.21299	-5.49215
14	73.1	77.9922	75.5375	2.45465	-4.89215
15	71.5	75.6505	76.0125	-0.362014	-4.15049
16	74.1	75.7913	77.3292	-1.53785	-1.69132
17	80.3	76.978	79.3167	-2.33868	3.32201
18	80.6	78.1513	81.5375	-3.38618	2.44868
19	81.4	85.5338	83.9	1.63382	-4.13382
20	87.4	88.0355	86.0042	2.03132	-0.635486
21	89.3	90.1188	87.6708	2.44799	-0.818819
22	93.2	88.2222	88.9542	-0.732014	4.97785
23	92.8	88.2563	89.775	-1.51868	4.54368
24	96.8	89.6447	90.55	-0.905347	7.15535
25	100.3	93.988	91.775	2.21299	6.31201
26	95.6	95.5047	93.05	2.45465	0.0953472
27	89	93.9213	94.2833	-0.362014	-4.92132
28	87.4	94.0288	95.5667	-1.53785	-6.62882
29	86.7	94.7072	97.0458	-2.33868	-8.00715
30	92.8	95.5097	98.8958	-3.38618	-2.70965
31	98.6	102.6	100.967	1.63382	-4.00049
32	100.8	105.723	103.692	2.03132	-4.92299
33	105.5	109.669	107.221	2.44799	-4.16882
34	107.8	110.289	111.021	-0.732014	-2.48882
35	113.7	113.16	114.679	-1.51868	0.539514
36	120.3	116.957	117.862	-0.905347	3.34285
37	126.5	122.775	120.563	2.21299	3.72451
38	134.8	125.438	122.983	2.45465	9.36201
39	134.5	124.646	125.008	-0.362014	9.85368
40	133.1	124.733	126.271	-1.53785	8.36701
41	128.8	124.34	126.679	-2.33868	4.45951
42	127.1	122.847	126.233	-3.38618	4.25285
43	129.1	126.725	125.092	1.63382	2.37451
44	128.4	125.381	123.35	2.03132	3.01868
45	126.5	123.444	120.996	2.44799	3.05618
46	117.1	117.551	118.283	-0.732014	-0.451319
47	114.2	113.969	115.488	-1.51868	0.231181
48	109.1	111.715	112.621	-0.905347	-2.61549
49	110.3	112.071	109.858	2.21299	-1.77132
50	109.2	109.634	107.179	2.45465	-0.433819
51	103.6	104.117	104.479	-0.362014	-0.517153
52	98.9	100.683	102.221	-1.53785	-1.78299
53	95.9	97.8822	100.221	-2.33868	-1.98215
54	91.2	94.8888	98.275	-3.38618	-3.68882
55	98.7	98.0255	96.3917	1.63382	0.674514
56	94.5	96.4272	94.3958	2.03132	-1.92715
57	95.6	95.0063	92.5583	2.44799	0.593681
58	93.8	90.3847	91.1167	-0.732014	3.41535
59	89.5	88.3938	89.9125	-1.51868	1.10618
60	87.1	87.8738	88.7792	-0.905347	-0.773819
61	87.1	89.588	87.375	2.21299	-2.48799
62	84.5	88.3463	85.8917	2.45465	-3.84632
63	84.2	84.1797	84.5417	-0.362014	0.0203472
64	83.7	81.6788	83.2167	-1.53785	2.02118
65	82.2	79.7072	82.0458	-2.33868	2.49285
66	77.7	77.718	81.1042	-3.38618	-0.0179861
67	78.5	NA	NA	1.63382	NA
68	79.1	NA	NA	2.03132	NA
69	78.6	NA	NA	2.44799	NA
70	79	NA	NA	-0.732014	NA
71	76.2	NA	NA	-1.51868	NA
72	77.8	NA	NA	-0.905347	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 75 & NA & NA & 2.21299 & NA \tabularnewline
2 & 84.3 & NA & NA & 2.45465 & NA \tabularnewline
3 & 84 & NA & NA & -0.362014 & NA \tabularnewline
4 & 79.1 & NA & NA & -1.53785 & NA \tabularnewline
5 & 78.8 & NA & NA & -2.33868 & NA \tabularnewline
6 & 82.7 & NA & NA & -3.38618 & NA \tabularnewline
7 & 85.3 & 79.9297 & 78.2958 & 1.63382 & 5.37035 \tabularnewline
8 & 84.5 & 79.748 & 77.7167 & 2.03132 & 4.75201 \tabularnewline
9 & 80.8 & 79.1772 & 76.7292 & 2.44799 & 1.62285 \tabularnewline
10 & 70.1 & 75.268 & 76 & -0.732014 & -5.16799 \tabularnewline
11 & 68.2 & 74.3355 & 75.8542 & -1.51868 & -6.13549 \tabularnewline
12 & 68.1 & 74.9238 & 75.8292 & -0.905347 & -6.82382 \tabularnewline
13 & 72.3 & 77.7922 & 75.5792 & 2.21299 & -5.49215 \tabularnewline
14 & 73.1 & 77.9922 & 75.5375 & 2.45465 & -4.89215 \tabularnewline
15 & 71.5 & 75.6505 & 76.0125 & -0.362014 & -4.15049 \tabularnewline
16 & 74.1 & 75.7913 & 77.3292 & -1.53785 & -1.69132 \tabularnewline
17 & 80.3 & 76.978 & 79.3167 & -2.33868 & 3.32201 \tabularnewline
18 & 80.6 & 78.1513 & 81.5375 & -3.38618 & 2.44868 \tabularnewline
19 & 81.4 & 85.5338 & 83.9 & 1.63382 & -4.13382 \tabularnewline
20 & 87.4 & 88.0355 & 86.0042 & 2.03132 & -0.635486 \tabularnewline
21 & 89.3 & 90.1188 & 87.6708 & 2.44799 & -0.818819 \tabularnewline
22 & 93.2 & 88.2222 & 88.9542 & -0.732014 & 4.97785 \tabularnewline
23 & 92.8 & 88.2563 & 89.775 & -1.51868 & 4.54368 \tabularnewline
24 & 96.8 & 89.6447 & 90.55 & -0.905347 & 7.15535 \tabularnewline
25 & 100.3 & 93.988 & 91.775 & 2.21299 & 6.31201 \tabularnewline
26 & 95.6 & 95.5047 & 93.05 & 2.45465 & 0.0953472 \tabularnewline
27 & 89 & 93.9213 & 94.2833 & -0.362014 & -4.92132 \tabularnewline
28 & 87.4 & 94.0288 & 95.5667 & -1.53785 & -6.62882 \tabularnewline
29 & 86.7 & 94.7072 & 97.0458 & -2.33868 & -8.00715 \tabularnewline
30 & 92.8 & 95.5097 & 98.8958 & -3.38618 & -2.70965 \tabularnewline
31 & 98.6 & 102.6 & 100.967 & 1.63382 & -4.00049 \tabularnewline
32 & 100.8 & 105.723 & 103.692 & 2.03132 & -4.92299 \tabularnewline
33 & 105.5 & 109.669 & 107.221 & 2.44799 & -4.16882 \tabularnewline
34 & 107.8 & 110.289 & 111.021 & -0.732014 & -2.48882 \tabularnewline
35 & 113.7 & 113.16 & 114.679 & -1.51868 & 0.539514 \tabularnewline
36 & 120.3 & 116.957 & 117.862 & -0.905347 & 3.34285 \tabularnewline
37 & 126.5 & 122.775 & 120.563 & 2.21299 & 3.72451 \tabularnewline
38 & 134.8 & 125.438 & 122.983 & 2.45465 & 9.36201 \tabularnewline
39 & 134.5 & 124.646 & 125.008 & -0.362014 & 9.85368 \tabularnewline
40 & 133.1 & 124.733 & 126.271 & -1.53785 & 8.36701 \tabularnewline
41 & 128.8 & 124.34 & 126.679 & -2.33868 & 4.45951 \tabularnewline
42 & 127.1 & 122.847 & 126.233 & -3.38618 & 4.25285 \tabularnewline
43 & 129.1 & 126.725 & 125.092 & 1.63382 & 2.37451 \tabularnewline
44 & 128.4 & 125.381 & 123.35 & 2.03132 & 3.01868 \tabularnewline
45 & 126.5 & 123.444 & 120.996 & 2.44799 & 3.05618 \tabularnewline
46 & 117.1 & 117.551 & 118.283 & -0.732014 & -0.451319 \tabularnewline
47 & 114.2 & 113.969 & 115.488 & -1.51868 & 0.231181 \tabularnewline
48 & 109.1 & 111.715 & 112.621 & -0.905347 & -2.61549 \tabularnewline
49 & 110.3 & 112.071 & 109.858 & 2.21299 & -1.77132 \tabularnewline
50 & 109.2 & 109.634 & 107.179 & 2.45465 & -0.433819 \tabularnewline
51 & 103.6 & 104.117 & 104.479 & -0.362014 & -0.517153 \tabularnewline
52 & 98.9 & 100.683 & 102.221 & -1.53785 & -1.78299 \tabularnewline
53 & 95.9 & 97.8822 & 100.221 & -2.33868 & -1.98215 \tabularnewline
54 & 91.2 & 94.8888 & 98.275 & -3.38618 & -3.68882 \tabularnewline
55 & 98.7 & 98.0255 & 96.3917 & 1.63382 & 0.674514 \tabularnewline
56 & 94.5 & 96.4272 & 94.3958 & 2.03132 & -1.92715 \tabularnewline
57 & 95.6 & 95.0063 & 92.5583 & 2.44799 & 0.593681 \tabularnewline
58 & 93.8 & 90.3847 & 91.1167 & -0.732014 & 3.41535 \tabularnewline
59 & 89.5 & 88.3938 & 89.9125 & -1.51868 & 1.10618 \tabularnewline
60 & 87.1 & 87.8738 & 88.7792 & -0.905347 & -0.773819 \tabularnewline
61 & 87.1 & 89.588 & 87.375 & 2.21299 & -2.48799 \tabularnewline
62 & 84.5 & 88.3463 & 85.8917 & 2.45465 & -3.84632 \tabularnewline
63 & 84.2 & 84.1797 & 84.5417 & -0.362014 & 0.0203472 \tabularnewline
64 & 83.7 & 81.6788 & 83.2167 & -1.53785 & 2.02118 \tabularnewline
65 & 82.2 & 79.7072 & 82.0458 & -2.33868 & 2.49285 \tabularnewline
66 & 77.7 & 77.718 & 81.1042 & -3.38618 & -0.0179861 \tabularnewline
67 & 78.5 & NA & NA & 1.63382 & NA \tabularnewline
68 & 79.1 & NA & NA & 2.03132 & NA \tabularnewline
69 & 78.6 & NA & NA & 2.44799 & NA \tabularnewline
70 & 79 & NA & NA & -0.732014 & NA \tabularnewline
71 & 76.2 & NA & NA & -1.51868 & NA \tabularnewline
72 & 77.8 & NA & NA & -0.905347 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261083&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]75[/C][C]NA[/C][C]NA[/C][C]2.21299[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]84.3[/C][C]NA[/C][C]NA[/C][C]2.45465[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]84[/C][C]NA[/C][C]NA[/C][C]-0.362014[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]79.1[/C][C]NA[/C][C]NA[/C][C]-1.53785[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]78.8[/C][C]NA[/C][C]NA[/C][C]-2.33868[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]82.7[/C][C]NA[/C][C]NA[/C][C]-3.38618[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]85.3[/C][C]79.9297[/C][C]78.2958[/C][C]1.63382[/C][C]5.37035[/C][/ROW]
[ROW][C]8[/C][C]84.5[/C][C]79.748[/C][C]77.7167[/C][C]2.03132[/C][C]4.75201[/C][/ROW]
[ROW][C]9[/C][C]80.8[/C][C]79.1772[/C][C]76.7292[/C][C]2.44799[/C][C]1.62285[/C][/ROW]
[ROW][C]10[/C][C]70.1[/C][C]75.268[/C][C]76[/C][C]-0.732014[/C][C]-5.16799[/C][/ROW]
[ROW][C]11[/C][C]68.2[/C][C]74.3355[/C][C]75.8542[/C][C]-1.51868[/C][C]-6.13549[/C][/ROW]
[ROW][C]12[/C][C]68.1[/C][C]74.9238[/C][C]75.8292[/C][C]-0.905347[/C][C]-6.82382[/C][/ROW]
[ROW][C]13[/C][C]72.3[/C][C]77.7922[/C][C]75.5792[/C][C]2.21299[/C][C]-5.49215[/C][/ROW]
[ROW][C]14[/C][C]73.1[/C][C]77.9922[/C][C]75.5375[/C][C]2.45465[/C][C]-4.89215[/C][/ROW]
[ROW][C]15[/C][C]71.5[/C][C]75.6505[/C][C]76.0125[/C][C]-0.362014[/C][C]-4.15049[/C][/ROW]
[ROW][C]16[/C][C]74.1[/C][C]75.7913[/C][C]77.3292[/C][C]-1.53785[/C][C]-1.69132[/C][/ROW]
[ROW][C]17[/C][C]80.3[/C][C]76.978[/C][C]79.3167[/C][C]-2.33868[/C][C]3.32201[/C][/ROW]
[ROW][C]18[/C][C]80.6[/C][C]78.1513[/C][C]81.5375[/C][C]-3.38618[/C][C]2.44868[/C][/ROW]
[ROW][C]19[/C][C]81.4[/C][C]85.5338[/C][C]83.9[/C][C]1.63382[/C][C]-4.13382[/C][/ROW]
[ROW][C]20[/C][C]87.4[/C][C]88.0355[/C][C]86.0042[/C][C]2.03132[/C][C]-0.635486[/C][/ROW]
[ROW][C]21[/C][C]89.3[/C][C]90.1188[/C][C]87.6708[/C][C]2.44799[/C][C]-0.818819[/C][/ROW]
[ROW][C]22[/C][C]93.2[/C][C]88.2222[/C][C]88.9542[/C][C]-0.732014[/C][C]4.97785[/C][/ROW]
[ROW][C]23[/C][C]92.8[/C][C]88.2563[/C][C]89.775[/C][C]-1.51868[/C][C]4.54368[/C][/ROW]
[ROW][C]24[/C][C]96.8[/C][C]89.6447[/C][C]90.55[/C][C]-0.905347[/C][C]7.15535[/C][/ROW]
[ROW][C]25[/C][C]100.3[/C][C]93.988[/C][C]91.775[/C][C]2.21299[/C][C]6.31201[/C][/ROW]
[ROW][C]26[/C][C]95.6[/C][C]95.5047[/C][C]93.05[/C][C]2.45465[/C][C]0.0953472[/C][/ROW]
[ROW][C]27[/C][C]89[/C][C]93.9213[/C][C]94.2833[/C][C]-0.362014[/C][C]-4.92132[/C][/ROW]
[ROW][C]28[/C][C]87.4[/C][C]94.0288[/C][C]95.5667[/C][C]-1.53785[/C][C]-6.62882[/C][/ROW]
[ROW][C]29[/C][C]86.7[/C][C]94.7072[/C][C]97.0458[/C][C]-2.33868[/C][C]-8.00715[/C][/ROW]
[ROW][C]30[/C][C]92.8[/C][C]95.5097[/C][C]98.8958[/C][C]-3.38618[/C][C]-2.70965[/C][/ROW]
[ROW][C]31[/C][C]98.6[/C][C]102.6[/C][C]100.967[/C][C]1.63382[/C][C]-4.00049[/C][/ROW]
[ROW][C]32[/C][C]100.8[/C][C]105.723[/C][C]103.692[/C][C]2.03132[/C][C]-4.92299[/C][/ROW]
[ROW][C]33[/C][C]105.5[/C][C]109.669[/C][C]107.221[/C][C]2.44799[/C][C]-4.16882[/C][/ROW]
[ROW][C]34[/C][C]107.8[/C][C]110.289[/C][C]111.021[/C][C]-0.732014[/C][C]-2.48882[/C][/ROW]
[ROW][C]35[/C][C]113.7[/C][C]113.16[/C][C]114.679[/C][C]-1.51868[/C][C]0.539514[/C][/ROW]
[ROW][C]36[/C][C]120.3[/C][C]116.957[/C][C]117.862[/C][C]-0.905347[/C][C]3.34285[/C][/ROW]
[ROW][C]37[/C][C]126.5[/C][C]122.775[/C][C]120.563[/C][C]2.21299[/C][C]3.72451[/C][/ROW]
[ROW][C]38[/C][C]134.8[/C][C]125.438[/C][C]122.983[/C][C]2.45465[/C][C]9.36201[/C][/ROW]
[ROW][C]39[/C][C]134.5[/C][C]124.646[/C][C]125.008[/C][C]-0.362014[/C][C]9.85368[/C][/ROW]
[ROW][C]40[/C][C]133.1[/C][C]124.733[/C][C]126.271[/C][C]-1.53785[/C][C]8.36701[/C][/ROW]
[ROW][C]41[/C][C]128.8[/C][C]124.34[/C][C]126.679[/C][C]-2.33868[/C][C]4.45951[/C][/ROW]
[ROW][C]42[/C][C]127.1[/C][C]122.847[/C][C]126.233[/C][C]-3.38618[/C][C]4.25285[/C][/ROW]
[ROW][C]43[/C][C]129.1[/C][C]126.725[/C][C]125.092[/C][C]1.63382[/C][C]2.37451[/C][/ROW]
[ROW][C]44[/C][C]128.4[/C][C]125.381[/C][C]123.35[/C][C]2.03132[/C][C]3.01868[/C][/ROW]
[ROW][C]45[/C][C]126.5[/C][C]123.444[/C][C]120.996[/C][C]2.44799[/C][C]3.05618[/C][/ROW]
[ROW][C]46[/C][C]117.1[/C][C]117.551[/C][C]118.283[/C][C]-0.732014[/C][C]-0.451319[/C][/ROW]
[ROW][C]47[/C][C]114.2[/C][C]113.969[/C][C]115.488[/C][C]-1.51868[/C][C]0.231181[/C][/ROW]
[ROW][C]48[/C][C]109.1[/C][C]111.715[/C][C]112.621[/C][C]-0.905347[/C][C]-2.61549[/C][/ROW]
[ROW][C]49[/C][C]110.3[/C][C]112.071[/C][C]109.858[/C][C]2.21299[/C][C]-1.77132[/C][/ROW]
[ROW][C]50[/C][C]109.2[/C][C]109.634[/C][C]107.179[/C][C]2.45465[/C][C]-0.433819[/C][/ROW]
[ROW][C]51[/C][C]103.6[/C][C]104.117[/C][C]104.479[/C][C]-0.362014[/C][C]-0.517153[/C][/ROW]
[ROW][C]52[/C][C]98.9[/C][C]100.683[/C][C]102.221[/C][C]-1.53785[/C][C]-1.78299[/C][/ROW]
[ROW][C]53[/C][C]95.9[/C][C]97.8822[/C][C]100.221[/C][C]-2.33868[/C][C]-1.98215[/C][/ROW]
[ROW][C]54[/C][C]91.2[/C][C]94.8888[/C][C]98.275[/C][C]-3.38618[/C][C]-3.68882[/C][/ROW]
[ROW][C]55[/C][C]98.7[/C][C]98.0255[/C][C]96.3917[/C][C]1.63382[/C][C]0.674514[/C][/ROW]
[ROW][C]56[/C][C]94.5[/C][C]96.4272[/C][C]94.3958[/C][C]2.03132[/C][C]-1.92715[/C][/ROW]
[ROW][C]57[/C][C]95.6[/C][C]95.0063[/C][C]92.5583[/C][C]2.44799[/C][C]0.593681[/C][/ROW]
[ROW][C]58[/C][C]93.8[/C][C]90.3847[/C][C]91.1167[/C][C]-0.732014[/C][C]3.41535[/C][/ROW]
[ROW][C]59[/C][C]89.5[/C][C]88.3938[/C][C]89.9125[/C][C]-1.51868[/C][C]1.10618[/C][/ROW]
[ROW][C]60[/C][C]87.1[/C][C]87.8738[/C][C]88.7792[/C][C]-0.905347[/C][C]-0.773819[/C][/ROW]
[ROW][C]61[/C][C]87.1[/C][C]89.588[/C][C]87.375[/C][C]2.21299[/C][C]-2.48799[/C][/ROW]
[ROW][C]62[/C][C]84.5[/C][C]88.3463[/C][C]85.8917[/C][C]2.45465[/C][C]-3.84632[/C][/ROW]
[ROW][C]63[/C][C]84.2[/C][C]84.1797[/C][C]84.5417[/C][C]-0.362014[/C][C]0.0203472[/C][/ROW]
[ROW][C]64[/C][C]83.7[/C][C]81.6788[/C][C]83.2167[/C][C]-1.53785[/C][C]2.02118[/C][/ROW]
[ROW][C]65[/C][C]82.2[/C][C]79.7072[/C][C]82.0458[/C][C]-2.33868[/C][C]2.49285[/C][/ROW]
[ROW][C]66[/C][C]77.7[/C][C]77.718[/C][C]81.1042[/C][C]-3.38618[/C][C]-0.0179861[/C][/ROW]
[ROW][C]67[/C][C]78.5[/C][C]NA[/C][C]NA[/C][C]1.63382[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]79.1[/C][C]NA[/C][C]NA[/C][C]2.03132[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]78.6[/C][C]NA[/C][C]NA[/C][C]2.44799[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]79[/C][C]NA[/C][C]NA[/C][C]-0.732014[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]76.2[/C][C]NA[/C][C]NA[/C][C]-1.51868[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]77.8[/C][C]NA[/C][C]NA[/C][C]-0.905347[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261083&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261083&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	75	NA	NA	2.21299	NA
2	84.3	NA	NA	2.45465	NA
3	84	NA	NA	-0.362014	NA
4	79.1	NA	NA	-1.53785	NA
5	78.8	NA	NA	-2.33868	NA
6	82.7	NA	NA	-3.38618	NA
7	85.3	79.9297	78.2958	1.63382	5.37035
8	84.5	79.748	77.7167	2.03132	4.75201
9	80.8	79.1772	76.7292	2.44799	1.62285
10	70.1	75.268	76	-0.732014	-5.16799
11	68.2	74.3355	75.8542	-1.51868	-6.13549
12	68.1	74.9238	75.8292	-0.905347	-6.82382
13	72.3	77.7922	75.5792	2.21299	-5.49215
14	73.1	77.9922	75.5375	2.45465	-4.89215
15	71.5	75.6505	76.0125	-0.362014	-4.15049
16	74.1	75.7913	77.3292	-1.53785	-1.69132
17	80.3	76.978	79.3167	-2.33868	3.32201
18	80.6	78.1513	81.5375	-3.38618	2.44868
19	81.4	85.5338	83.9	1.63382	-4.13382
20	87.4	88.0355	86.0042	2.03132	-0.635486
21	89.3	90.1188	87.6708	2.44799	-0.818819
22	93.2	88.2222	88.9542	-0.732014	4.97785
23	92.8	88.2563	89.775	-1.51868	4.54368
24	96.8	89.6447	90.55	-0.905347	7.15535
25	100.3	93.988	91.775	2.21299	6.31201
26	95.6	95.5047	93.05	2.45465	0.0953472
27	89	93.9213	94.2833	-0.362014	-4.92132
28	87.4	94.0288	95.5667	-1.53785	-6.62882
29	86.7	94.7072	97.0458	-2.33868	-8.00715
30	92.8	95.5097	98.8958	-3.38618	-2.70965
31	98.6	102.6	100.967	1.63382	-4.00049
32	100.8	105.723	103.692	2.03132	-4.92299
33	105.5	109.669	107.221	2.44799	-4.16882
34	107.8	110.289	111.021	-0.732014	-2.48882
35	113.7	113.16	114.679	-1.51868	0.539514
36	120.3	116.957	117.862	-0.905347	3.34285
37	126.5	122.775	120.563	2.21299	3.72451
38	134.8	125.438	122.983	2.45465	9.36201
39	134.5	124.646	125.008	-0.362014	9.85368
40	133.1	124.733	126.271	-1.53785	8.36701
41	128.8	124.34	126.679	-2.33868	4.45951
42	127.1	122.847	126.233	-3.38618	4.25285
43	129.1	126.725	125.092	1.63382	2.37451
44	128.4	125.381	123.35	2.03132	3.01868
45	126.5	123.444	120.996	2.44799	3.05618
46	117.1	117.551	118.283	-0.732014	-0.451319
47	114.2	113.969	115.488	-1.51868	0.231181
48	109.1	111.715	112.621	-0.905347	-2.61549
49	110.3	112.071	109.858	2.21299	-1.77132
50	109.2	109.634	107.179	2.45465	-0.433819
51	103.6	104.117	104.479	-0.362014	-0.517153
52	98.9	100.683	102.221	-1.53785	-1.78299
53	95.9	97.8822	100.221	-2.33868	-1.98215
54	91.2	94.8888	98.275	-3.38618	-3.68882
55	98.7	98.0255	96.3917	1.63382	0.674514
56	94.5	96.4272	94.3958	2.03132	-1.92715
57	95.6	95.0063	92.5583	2.44799	0.593681
58	93.8	90.3847	91.1167	-0.732014	3.41535
59	89.5	88.3938	89.9125	-1.51868	1.10618
60	87.1	87.8738	88.7792	-0.905347	-0.773819
61	87.1	89.588	87.375	2.21299	-2.48799
62	84.5	88.3463	85.8917	2.45465	-3.84632
63	84.2	84.1797	84.5417	-0.362014	0.0203472
64	83.7	81.6788	83.2167	-1.53785	2.02118
65	82.2	79.7072	82.0458	-2.33868	2.49285
66	77.7	77.718	81.1042	-3.38618	-0.0179861
67	78.5	NA	NA	1.63382	NA
68	79.1	NA	NA	2.03132	NA
69	78.6	NA	NA	2.44799	NA
70	79	NA	NA	-0.732014	NA
71	76.2	NA	NA	-1.51868	NA
72	77.8	NA	NA	-0.905347	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code