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

Thu, 27 Nov 2014 10:54:44 +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/27/t1417085768v3wtegvjvon2g8e.htm/, Retrieved Thu, 28 May 2026 23:34:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=259612, Retrieved Thu, 28 May 2026 23:34:15 +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

305

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

-       [Classical Decomposition] [prijsindexcijfers...] [2014-11-27 10:54:44] [3acc2e190882a8fff3240b97d842d2ea] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259612&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259612&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259612&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	103.1	NA	NA	0.325	NA
2	113.5	NA	NA	0.416667	NA
3	115.7	NA	NA	-0.894167	NA
4	113.1	NA	NA	-0.605833	NA
5	112.7	NA	NA	0.0283333	NA
6	121.9	NA	NA	-0.185	NA
7	120.3	107.734	103.642	4.0925	12.5658
8	108.7	105.513	101.654	3.85833	3.1875
9	102.8	101.189	98.9875	2.20167	1.61083
10	83.4	93.5942	96.4917	-2.8975	-10.1942
11	79.4	91.2133	94.6917	-3.47833	-11.8133
12	77.8	90.1217	92.9833	-2.86167	-12.3217
13	85.7	91.0167	90.6917	0.325	-5.31667
14	83.2	89.1	88.6833	0.416667	-5.9
15	82	86.4058	87.3	-0.894167	-4.40583
16	86.9	86.3442	86.95	-0.605833	0.555833
17	95.7	87.895	87.8667	0.0283333	7.805
18	97.9	89.0733	89.2583	-0.185	8.82667
19	89.3	94.5592	90.4667	4.0925	-5.25917
20	91.5	95.0833	91.225	3.85833	-3.58333
21	86.8	94.0475	91.8458	2.20167	-7.2475
22	91	89.2817	92.1792	-2.8975	1.71833
23	93.8	88.4217	91.9	-3.47833	5.37833
24	96.8	88.355	91.2167	-2.86167	8.445
25	95.7	91.4542	91.1292	0.325	4.24583
26	91.4	92.1833	91.7667	0.416667	-0.783333
27	88.7	92.06	92.9542	-0.894167	-3.36
28	88.2	94.0358	94.6417	-0.605833	-5.83583
29	87.7	96.5408	96.5125	0.0283333	-8.84083
30	89.5	98.4983	98.6833	-0.185	-8.99833
31	95.6	105.48	101.388	4.0925	-9.88
32	100.5	108.721	104.862	3.85833	-8.22083
33	106.3	110.927	108.725	2.20167	-4.62667
34	112	109.765	112.662	-2.8975	2.235
35	117.7	113.147	116.625	-3.47833	4.55333
36	125	117.459	120.321	-2.86167	7.54083
37	132.4	123.825	123.5	0.325	8.575
38	138.1	126.65	126.233	0.416667	11.45
39	134.7	127.627	128.521	-0.894167	7.07333
40	136.7	129.203	129.808	-0.605833	7.4975
41	134.3	130.103	130.075	0.0283333	4.19667
42	131.6	129.34	129.525	-0.185	2.26
43	129.8	132.426	128.333	4.0925	-2.62583
44	131.9	130.65	126.792	3.85833	1.25
45	129.8	127.472	125.271	2.20167	2.3275
46	119.4	120.961	123.858	-2.8975	-1.56083
47	116.7	118.88	122.358	-3.47833	-2.18
48	112.8	118.063	120.925	-2.86167	-5.26333
49	116	120.646	120.321	0.325	-4.64583
50	117.5	120.892	120.475	0.416667	-3.39167
51	118.8	119.768	120.663	-0.894167	-0.968333
52	118.7	120.482	121.088	-0.605833	-1.78167
53	116.3	121.658	121.629	0.0283333	-5.3575
54	115.2	121.982	122.167	-0.185	-6.78167
55	131.7	126.647	122.554	4.0925	5.05333
56	133.7	126.479	122.621	3.85833	7.22083
57	132.5	124.71	122.508	2.20167	7.79
58	126.9	119.244	122.142	-2.8975	7.65583
59	122.2	118.284	121.762	-3.47833	3.91583
60	120.2	118.747	121.608	-2.86167	1.45333
61	117.9	120.904	120.579	0.325	-3.00417
62	117.2	118.721	118.304	0.416667	-1.52083
63	116.4	114.885	115.779	-0.894167	1.515
64	112.3	112.882	113.488	-0.605833	-0.581667
65	113.6	111.549	111.521	0.0283333	2.05083
66	114.2	109.652	109.838	-0.185	4.5475
67	108	NA	NA	4.0925	NA
68	102.8	NA	NA	3.85833	NA
69	102.8	NA	NA	2.20167	NA
70	101.6	NA	NA	-2.8975	NA
71	100.3	NA	NA	-3.47833	NA
72	101.7	NA	NA	-2.86167	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 103.1 & NA & NA & 0.325 & NA \tabularnewline
2 & 113.5 & NA & NA & 0.416667 & NA \tabularnewline
3 & 115.7 & NA & NA & -0.894167 & NA \tabularnewline
4 & 113.1 & NA & NA & -0.605833 & NA \tabularnewline
5 & 112.7 & NA & NA & 0.0283333 & NA \tabularnewline
6 & 121.9 & NA & NA & -0.185 & NA \tabularnewline
7 & 120.3 & 107.734 & 103.642 & 4.0925 & 12.5658 \tabularnewline
8 & 108.7 & 105.513 & 101.654 & 3.85833 & 3.1875 \tabularnewline
9 & 102.8 & 101.189 & 98.9875 & 2.20167 & 1.61083 \tabularnewline
10 & 83.4 & 93.5942 & 96.4917 & -2.8975 & -10.1942 \tabularnewline
11 & 79.4 & 91.2133 & 94.6917 & -3.47833 & -11.8133 \tabularnewline
12 & 77.8 & 90.1217 & 92.9833 & -2.86167 & -12.3217 \tabularnewline
13 & 85.7 & 91.0167 & 90.6917 & 0.325 & -5.31667 \tabularnewline
14 & 83.2 & 89.1 & 88.6833 & 0.416667 & -5.9 \tabularnewline
15 & 82 & 86.4058 & 87.3 & -0.894167 & -4.40583 \tabularnewline
16 & 86.9 & 86.3442 & 86.95 & -0.605833 & 0.555833 \tabularnewline
17 & 95.7 & 87.895 & 87.8667 & 0.0283333 & 7.805 \tabularnewline
18 & 97.9 & 89.0733 & 89.2583 & -0.185 & 8.82667 \tabularnewline
19 & 89.3 & 94.5592 & 90.4667 & 4.0925 & -5.25917 \tabularnewline
20 & 91.5 & 95.0833 & 91.225 & 3.85833 & -3.58333 \tabularnewline
21 & 86.8 & 94.0475 & 91.8458 & 2.20167 & -7.2475 \tabularnewline
22 & 91 & 89.2817 & 92.1792 & -2.8975 & 1.71833 \tabularnewline
23 & 93.8 & 88.4217 & 91.9 & -3.47833 & 5.37833 \tabularnewline
24 & 96.8 & 88.355 & 91.2167 & -2.86167 & 8.445 \tabularnewline
25 & 95.7 & 91.4542 & 91.1292 & 0.325 & 4.24583 \tabularnewline
26 & 91.4 & 92.1833 & 91.7667 & 0.416667 & -0.783333 \tabularnewline
27 & 88.7 & 92.06 & 92.9542 & -0.894167 & -3.36 \tabularnewline
28 & 88.2 & 94.0358 & 94.6417 & -0.605833 & -5.83583 \tabularnewline
29 & 87.7 & 96.5408 & 96.5125 & 0.0283333 & -8.84083 \tabularnewline
30 & 89.5 & 98.4983 & 98.6833 & -0.185 & -8.99833 \tabularnewline
31 & 95.6 & 105.48 & 101.388 & 4.0925 & -9.88 \tabularnewline
32 & 100.5 & 108.721 & 104.862 & 3.85833 & -8.22083 \tabularnewline
33 & 106.3 & 110.927 & 108.725 & 2.20167 & -4.62667 \tabularnewline
34 & 112 & 109.765 & 112.662 & -2.8975 & 2.235 \tabularnewline
35 & 117.7 & 113.147 & 116.625 & -3.47833 & 4.55333 \tabularnewline
36 & 125 & 117.459 & 120.321 & -2.86167 & 7.54083 \tabularnewline
37 & 132.4 & 123.825 & 123.5 & 0.325 & 8.575 \tabularnewline
38 & 138.1 & 126.65 & 126.233 & 0.416667 & 11.45 \tabularnewline
39 & 134.7 & 127.627 & 128.521 & -0.894167 & 7.07333 \tabularnewline
40 & 136.7 & 129.203 & 129.808 & -0.605833 & 7.4975 \tabularnewline
41 & 134.3 & 130.103 & 130.075 & 0.0283333 & 4.19667 \tabularnewline
42 & 131.6 & 129.34 & 129.525 & -0.185 & 2.26 \tabularnewline
43 & 129.8 & 132.426 & 128.333 & 4.0925 & -2.62583 \tabularnewline
44 & 131.9 & 130.65 & 126.792 & 3.85833 & 1.25 \tabularnewline
45 & 129.8 & 127.472 & 125.271 & 2.20167 & 2.3275 \tabularnewline
46 & 119.4 & 120.961 & 123.858 & -2.8975 & -1.56083 \tabularnewline
47 & 116.7 & 118.88 & 122.358 & -3.47833 & -2.18 \tabularnewline
48 & 112.8 & 118.063 & 120.925 & -2.86167 & -5.26333 \tabularnewline
49 & 116 & 120.646 & 120.321 & 0.325 & -4.64583 \tabularnewline
50 & 117.5 & 120.892 & 120.475 & 0.416667 & -3.39167 \tabularnewline
51 & 118.8 & 119.768 & 120.663 & -0.894167 & -0.968333 \tabularnewline
52 & 118.7 & 120.482 & 121.088 & -0.605833 & -1.78167 \tabularnewline
53 & 116.3 & 121.658 & 121.629 & 0.0283333 & -5.3575 \tabularnewline
54 & 115.2 & 121.982 & 122.167 & -0.185 & -6.78167 \tabularnewline
55 & 131.7 & 126.647 & 122.554 & 4.0925 & 5.05333 \tabularnewline
56 & 133.7 & 126.479 & 122.621 & 3.85833 & 7.22083 \tabularnewline
57 & 132.5 & 124.71 & 122.508 & 2.20167 & 7.79 \tabularnewline
58 & 126.9 & 119.244 & 122.142 & -2.8975 & 7.65583 \tabularnewline
59 & 122.2 & 118.284 & 121.762 & -3.47833 & 3.91583 \tabularnewline
60 & 120.2 & 118.747 & 121.608 & -2.86167 & 1.45333 \tabularnewline
61 & 117.9 & 120.904 & 120.579 & 0.325 & -3.00417 \tabularnewline
62 & 117.2 & 118.721 & 118.304 & 0.416667 & -1.52083 \tabularnewline
63 & 116.4 & 114.885 & 115.779 & -0.894167 & 1.515 \tabularnewline
64 & 112.3 & 112.882 & 113.488 & -0.605833 & -0.581667 \tabularnewline
65 & 113.6 & 111.549 & 111.521 & 0.0283333 & 2.05083 \tabularnewline
66 & 114.2 & 109.652 & 109.838 & -0.185 & 4.5475 \tabularnewline
67 & 108 & NA & NA & 4.0925 & NA \tabularnewline
68 & 102.8 & NA & NA & 3.85833 & NA \tabularnewline
69 & 102.8 & NA & NA & 2.20167 & NA \tabularnewline
70 & 101.6 & NA & NA & -2.8975 & NA \tabularnewline
71 & 100.3 & NA & NA & -3.47833 & NA \tabularnewline
72 & 101.7 & NA & NA & -2.86167 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259612&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]103.1[/C][C]NA[/C][C]NA[/C][C]0.325[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]113.5[/C][C]NA[/C][C]NA[/C][C]0.416667[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]115.7[/C][C]NA[/C][C]NA[/C][C]-0.894167[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]113.1[/C][C]NA[/C][C]NA[/C][C]-0.605833[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]112.7[/C][C]NA[/C][C]NA[/C][C]0.0283333[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]121.9[/C][C]NA[/C][C]NA[/C][C]-0.185[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]120.3[/C][C]107.734[/C][C]103.642[/C][C]4.0925[/C][C]12.5658[/C][/ROW]
[ROW][C]8[/C][C]108.7[/C][C]105.513[/C][C]101.654[/C][C]3.85833[/C][C]3.1875[/C][/ROW]
[ROW][C]9[/C][C]102.8[/C][C]101.189[/C][C]98.9875[/C][C]2.20167[/C][C]1.61083[/C][/ROW]
[ROW][C]10[/C][C]83.4[/C][C]93.5942[/C][C]96.4917[/C][C]-2.8975[/C][C]-10.1942[/C][/ROW]
[ROW][C]11[/C][C]79.4[/C][C]91.2133[/C][C]94.6917[/C][C]-3.47833[/C][C]-11.8133[/C][/ROW]
[ROW][C]12[/C][C]77.8[/C][C]90.1217[/C][C]92.9833[/C][C]-2.86167[/C][C]-12.3217[/C][/ROW]
[ROW][C]13[/C][C]85.7[/C][C]91.0167[/C][C]90.6917[/C][C]0.325[/C][C]-5.31667[/C][/ROW]
[ROW][C]14[/C][C]83.2[/C][C]89.1[/C][C]88.6833[/C][C]0.416667[/C][C]-5.9[/C][/ROW]
[ROW][C]15[/C][C]82[/C][C]86.4058[/C][C]87.3[/C][C]-0.894167[/C][C]-4.40583[/C][/ROW]
[ROW][C]16[/C][C]86.9[/C][C]86.3442[/C][C]86.95[/C][C]-0.605833[/C][C]0.555833[/C][/ROW]
[ROW][C]17[/C][C]95.7[/C][C]87.895[/C][C]87.8667[/C][C]0.0283333[/C][C]7.805[/C][/ROW]
[ROW][C]18[/C][C]97.9[/C][C]89.0733[/C][C]89.2583[/C][C]-0.185[/C][C]8.82667[/C][/ROW]
[ROW][C]19[/C][C]89.3[/C][C]94.5592[/C][C]90.4667[/C][C]4.0925[/C][C]-5.25917[/C][/ROW]
[ROW][C]20[/C][C]91.5[/C][C]95.0833[/C][C]91.225[/C][C]3.85833[/C][C]-3.58333[/C][/ROW]
[ROW][C]21[/C][C]86.8[/C][C]94.0475[/C][C]91.8458[/C][C]2.20167[/C][C]-7.2475[/C][/ROW]
[ROW][C]22[/C][C]91[/C][C]89.2817[/C][C]92.1792[/C][C]-2.8975[/C][C]1.71833[/C][/ROW]
[ROW][C]23[/C][C]93.8[/C][C]88.4217[/C][C]91.9[/C][C]-3.47833[/C][C]5.37833[/C][/ROW]
[ROW][C]24[/C][C]96.8[/C][C]88.355[/C][C]91.2167[/C][C]-2.86167[/C][C]8.445[/C][/ROW]
[ROW][C]25[/C][C]95.7[/C][C]91.4542[/C][C]91.1292[/C][C]0.325[/C][C]4.24583[/C][/ROW]
[ROW][C]26[/C][C]91.4[/C][C]92.1833[/C][C]91.7667[/C][C]0.416667[/C][C]-0.783333[/C][/ROW]
[ROW][C]27[/C][C]88.7[/C][C]92.06[/C][C]92.9542[/C][C]-0.894167[/C][C]-3.36[/C][/ROW]
[ROW][C]28[/C][C]88.2[/C][C]94.0358[/C][C]94.6417[/C][C]-0.605833[/C][C]-5.83583[/C][/ROW]
[ROW][C]29[/C][C]87.7[/C][C]96.5408[/C][C]96.5125[/C][C]0.0283333[/C][C]-8.84083[/C][/ROW]
[ROW][C]30[/C][C]89.5[/C][C]98.4983[/C][C]98.6833[/C][C]-0.185[/C][C]-8.99833[/C][/ROW]
[ROW][C]31[/C][C]95.6[/C][C]105.48[/C][C]101.388[/C][C]4.0925[/C][C]-9.88[/C][/ROW]
[ROW][C]32[/C][C]100.5[/C][C]108.721[/C][C]104.862[/C][C]3.85833[/C][C]-8.22083[/C][/ROW]
[ROW][C]33[/C][C]106.3[/C][C]110.927[/C][C]108.725[/C][C]2.20167[/C][C]-4.62667[/C][/ROW]
[ROW][C]34[/C][C]112[/C][C]109.765[/C][C]112.662[/C][C]-2.8975[/C][C]2.235[/C][/ROW]
[ROW][C]35[/C][C]117.7[/C][C]113.147[/C][C]116.625[/C][C]-3.47833[/C][C]4.55333[/C][/ROW]
[ROW][C]36[/C][C]125[/C][C]117.459[/C][C]120.321[/C][C]-2.86167[/C][C]7.54083[/C][/ROW]
[ROW][C]37[/C][C]132.4[/C][C]123.825[/C][C]123.5[/C][C]0.325[/C][C]8.575[/C][/ROW]
[ROW][C]38[/C][C]138.1[/C][C]126.65[/C][C]126.233[/C][C]0.416667[/C][C]11.45[/C][/ROW]
[ROW][C]39[/C][C]134.7[/C][C]127.627[/C][C]128.521[/C][C]-0.894167[/C][C]7.07333[/C][/ROW]
[ROW][C]40[/C][C]136.7[/C][C]129.203[/C][C]129.808[/C][C]-0.605833[/C][C]7.4975[/C][/ROW]
[ROW][C]41[/C][C]134.3[/C][C]130.103[/C][C]130.075[/C][C]0.0283333[/C][C]4.19667[/C][/ROW]
[ROW][C]42[/C][C]131.6[/C][C]129.34[/C][C]129.525[/C][C]-0.185[/C][C]2.26[/C][/ROW]
[ROW][C]43[/C][C]129.8[/C][C]132.426[/C][C]128.333[/C][C]4.0925[/C][C]-2.62583[/C][/ROW]
[ROW][C]44[/C][C]131.9[/C][C]130.65[/C][C]126.792[/C][C]3.85833[/C][C]1.25[/C][/ROW]
[ROW][C]45[/C][C]129.8[/C][C]127.472[/C][C]125.271[/C][C]2.20167[/C][C]2.3275[/C][/ROW]
[ROW][C]46[/C][C]119.4[/C][C]120.961[/C][C]123.858[/C][C]-2.8975[/C][C]-1.56083[/C][/ROW]
[ROW][C]47[/C][C]116.7[/C][C]118.88[/C][C]122.358[/C][C]-3.47833[/C][C]-2.18[/C][/ROW]
[ROW][C]48[/C][C]112.8[/C][C]118.063[/C][C]120.925[/C][C]-2.86167[/C][C]-5.26333[/C][/ROW]
[ROW][C]49[/C][C]116[/C][C]120.646[/C][C]120.321[/C][C]0.325[/C][C]-4.64583[/C][/ROW]
[ROW][C]50[/C][C]117.5[/C][C]120.892[/C][C]120.475[/C][C]0.416667[/C][C]-3.39167[/C][/ROW]
[ROW][C]51[/C][C]118.8[/C][C]119.768[/C][C]120.663[/C][C]-0.894167[/C][C]-0.968333[/C][/ROW]
[ROW][C]52[/C][C]118.7[/C][C]120.482[/C][C]121.088[/C][C]-0.605833[/C][C]-1.78167[/C][/ROW]
[ROW][C]53[/C][C]116.3[/C][C]121.658[/C][C]121.629[/C][C]0.0283333[/C][C]-5.3575[/C][/ROW]
[ROW][C]54[/C][C]115.2[/C][C]121.982[/C][C]122.167[/C][C]-0.185[/C][C]-6.78167[/C][/ROW]
[ROW][C]55[/C][C]131.7[/C][C]126.647[/C][C]122.554[/C][C]4.0925[/C][C]5.05333[/C][/ROW]
[ROW][C]56[/C][C]133.7[/C][C]126.479[/C][C]122.621[/C][C]3.85833[/C][C]7.22083[/C][/ROW]
[ROW][C]57[/C][C]132.5[/C][C]124.71[/C][C]122.508[/C][C]2.20167[/C][C]7.79[/C][/ROW]
[ROW][C]58[/C][C]126.9[/C][C]119.244[/C][C]122.142[/C][C]-2.8975[/C][C]7.65583[/C][/ROW]
[ROW][C]59[/C][C]122.2[/C][C]118.284[/C][C]121.762[/C][C]-3.47833[/C][C]3.91583[/C][/ROW]
[ROW][C]60[/C][C]120.2[/C][C]118.747[/C][C]121.608[/C][C]-2.86167[/C][C]1.45333[/C][/ROW]
[ROW][C]61[/C][C]117.9[/C][C]120.904[/C][C]120.579[/C][C]0.325[/C][C]-3.00417[/C][/ROW]
[ROW][C]62[/C][C]117.2[/C][C]118.721[/C][C]118.304[/C][C]0.416667[/C][C]-1.52083[/C][/ROW]
[ROW][C]63[/C][C]116.4[/C][C]114.885[/C][C]115.779[/C][C]-0.894167[/C][C]1.515[/C][/ROW]
[ROW][C]64[/C][C]112.3[/C][C]112.882[/C][C]113.488[/C][C]-0.605833[/C][C]-0.581667[/C][/ROW]
[ROW][C]65[/C][C]113.6[/C][C]111.549[/C][C]111.521[/C][C]0.0283333[/C][C]2.05083[/C][/ROW]
[ROW][C]66[/C][C]114.2[/C][C]109.652[/C][C]109.838[/C][C]-0.185[/C][C]4.5475[/C][/ROW]
[ROW][C]67[/C][C]108[/C][C]NA[/C][C]NA[/C][C]4.0925[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]102.8[/C][C]NA[/C][C]NA[/C][C]3.85833[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]102.8[/C][C]NA[/C][C]NA[/C][C]2.20167[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]101.6[/C][C]NA[/C][C]NA[/C][C]-2.8975[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]100.3[/C][C]NA[/C][C]NA[/C][C]-3.47833[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]101.7[/C][C]NA[/C][C]NA[/C][C]-2.86167[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259612&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259612&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	103.1	NA	NA	0.325	NA
2	113.5	NA	NA	0.416667	NA
3	115.7	NA	NA	-0.894167	NA
4	113.1	NA	NA	-0.605833	NA
5	112.7	NA	NA	0.0283333	NA
6	121.9	NA	NA	-0.185	NA
7	120.3	107.734	103.642	4.0925	12.5658
8	108.7	105.513	101.654	3.85833	3.1875
9	102.8	101.189	98.9875	2.20167	1.61083
10	83.4	93.5942	96.4917	-2.8975	-10.1942
11	79.4	91.2133	94.6917	-3.47833	-11.8133
12	77.8	90.1217	92.9833	-2.86167	-12.3217
13	85.7	91.0167	90.6917	0.325	-5.31667
14	83.2	89.1	88.6833	0.416667	-5.9
15	82	86.4058	87.3	-0.894167	-4.40583
16	86.9	86.3442	86.95	-0.605833	0.555833
17	95.7	87.895	87.8667	0.0283333	7.805
18	97.9	89.0733	89.2583	-0.185	8.82667
19	89.3	94.5592	90.4667	4.0925	-5.25917
20	91.5	95.0833	91.225	3.85833	-3.58333
21	86.8	94.0475	91.8458	2.20167	-7.2475
22	91	89.2817	92.1792	-2.8975	1.71833
23	93.8	88.4217	91.9	-3.47833	5.37833
24	96.8	88.355	91.2167	-2.86167	8.445
25	95.7	91.4542	91.1292	0.325	4.24583
26	91.4	92.1833	91.7667	0.416667	-0.783333
27	88.7	92.06	92.9542	-0.894167	-3.36
28	88.2	94.0358	94.6417	-0.605833	-5.83583
29	87.7	96.5408	96.5125	0.0283333	-8.84083
30	89.5	98.4983	98.6833	-0.185	-8.99833
31	95.6	105.48	101.388	4.0925	-9.88
32	100.5	108.721	104.862	3.85833	-8.22083
33	106.3	110.927	108.725	2.20167	-4.62667
34	112	109.765	112.662	-2.8975	2.235
35	117.7	113.147	116.625	-3.47833	4.55333
36	125	117.459	120.321	-2.86167	7.54083
37	132.4	123.825	123.5	0.325	8.575
38	138.1	126.65	126.233	0.416667	11.45
39	134.7	127.627	128.521	-0.894167	7.07333
40	136.7	129.203	129.808	-0.605833	7.4975
41	134.3	130.103	130.075	0.0283333	4.19667
42	131.6	129.34	129.525	-0.185	2.26
43	129.8	132.426	128.333	4.0925	-2.62583
44	131.9	130.65	126.792	3.85833	1.25
45	129.8	127.472	125.271	2.20167	2.3275
46	119.4	120.961	123.858	-2.8975	-1.56083
47	116.7	118.88	122.358	-3.47833	-2.18
48	112.8	118.063	120.925	-2.86167	-5.26333
49	116	120.646	120.321	0.325	-4.64583
50	117.5	120.892	120.475	0.416667	-3.39167
51	118.8	119.768	120.663	-0.894167	-0.968333
52	118.7	120.482	121.088	-0.605833	-1.78167
53	116.3	121.658	121.629	0.0283333	-5.3575
54	115.2	121.982	122.167	-0.185	-6.78167
55	131.7	126.647	122.554	4.0925	5.05333
56	133.7	126.479	122.621	3.85833	7.22083
57	132.5	124.71	122.508	2.20167	7.79
58	126.9	119.244	122.142	-2.8975	7.65583
59	122.2	118.284	121.762	-3.47833	3.91583
60	120.2	118.747	121.608	-2.86167	1.45333
61	117.9	120.904	120.579	0.325	-3.00417
62	117.2	118.721	118.304	0.416667	-1.52083
63	116.4	114.885	115.779	-0.894167	1.515
64	112.3	112.882	113.488	-0.605833	-0.581667
65	113.6	111.549	111.521	0.0283333	2.05083
66	114.2	109.652	109.838	-0.185	4.5475
67	108	NA	NA	4.0925	NA
68	102.8	NA	NA	3.85833	NA
69	102.8	NA	NA	2.20167	NA
70	101.6	NA	NA	-2.8975	NA
71	100.3	NA	NA	-3.47833	NA
72	101.7	NA	NA	-2.86167	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