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Author

*The author of this computation has been verified*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 27 Dec 2010 10:06:19 +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/2010/Dec/27/t1293444315cnk9bjbavme3v4u.htm/, Retrieved Mon, 06 May 2024 18:30:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115878, Retrieved Mon, 06 May 2024 18:30:46 +0000

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Original text written by user:

prijsverandering in Nederland

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

163

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

F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Cross Correlation Function] [Q7 - zonder trans...] [2008-12-01 20:04:13] [299afd6311e4c20059ea2f05c8dd029d]
F RM D    [Variance Reduction Matrix] [Q8] [2008-12-01 20:20:44] [299afd6311e4c20059ea2f05c8dd029d]
F    D      [Variance Reduction Matrix] [Q8 - 2] [2008-12-01 20:25:07] [299afd6311e4c20059ea2f05c8dd029d]
F RM D        [Standard Deviation-Mean Plot] [Deel 2: Step 1] [2008-12-08 20:09:35] [299afd6311e4c20059ea2f05c8dd029d]
-    D          [Standard Deviation-Mean Plot] [Totale Uitvoer - SMP] [2008-12-17 15:57:12] [299afd6311e4c20059ea2f05c8dd029d]
- RMPD            [ARIMA Forecasting] [ARIMA Forecasting] [2010-12-24 14:15:31] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [Classical Decomposition] [Classical Decompo...] [2010-12-27 10:06:19] [fba9c6aa004af59d8497d682e70ddad5] [Current]

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Dataseries X:

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Histogram

Boxplots

13.7
13.7
13.7
1.3
1.3
1.3
-7.4
-7.4
-7.4
-12.9
-12.9
-12.9
-9.6
-9.6
-9.6
-11.1
-11.1
-11.1
-8.3
-8.3
-8.3
-2.7
-2.7
-2.7
5.1
5.1
5.1
4.6
4.6
4.6
5.6
5.6
5.6
5.1
5.1
5.1
0.8
0.8
0.8
6
6
6
9.3
9.3
9.3
8.7
8.7
8.7
11
11
11
8.5
8.5
8.5
4.4
4.4
4.4
2.5
2.5
2.5
0.3
0.3
0.3
-3
-3
-3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115878&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115878&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115878&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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	13.7	NA	NA	3.57228193625257	NA
2	13.7	NA	NA	0.951193791268256	NA
3	13.7	NA	NA	0.698612144839178	NA
4	1.3	NA	NA	0.735412071575998	NA
5	1.3	NA	NA	0.72127807155013	NA
6	1.3	NA	NA	0.722252280763126	NA
7	-7.4	-1.60978773266566	-2.29583333333333	0.701177959781775	4.59687935858865
8	-7.4	-3.16020078357764	-4.2375	0.745770096419503	2.34162336724140
9	-7.4	-5.09326574430955	-6.17916666666667	0.824264179793858	1.45289886125962
10	-12.9	-4.53864768800151	-7.66666666666667	0.591997524521936	2.84225630337045
11	-12.9	-6.05557909466641	-8.7	0.696043574099588	2.13026694859984
12	-12.9	-10.1199059929051	-9.73333333333333	1.03971636913409	1.27471539844777
13	-9.6	-36.7498504191983	-10.2875	3.57228193625257	0.261225553042929
14	-9.6	-9.8567456620173	-10.3625	0.951193791268256	0.973952289039306
15	-9.6	-7.29176426175891	-10.4375	0.698612144839178	1.31655380719676
16	-11.1	-7.39089131933878	-10.05	0.735412071575998	1.50184862967151
17	-11.1	-6.63575825826119	-9.2	0.72127807155013	1.67275533073874
18	-11.1	-6.0308065443721	-8.35	0.722252280763126	1.84054983663146
19	-8.3	-5.12736383090423	-7.3125	0.701177959781775	1.61876556330434
20	-8.3	-4.53987546195372	-6.0875	0.745770096419503	1.82824398368587
21	-8.3	-4.00798457424764	-4.8625	0.824264179793858	2.07086625366018
22	-2.7	-2.12872443192679	-3.59583333333333	0.591997524521936	1.26836520477013
23	-2.7	-1.59219967575281	-2.2875	0.696043574099588	1.69576720879774
24	-2.7	-1.01805561144380	-0.979166666666667	1.03971636913409	2.65211445195110
25	5.1	0.907954992130858	0.254166666666666	3.57228193625257	5.61701851325354
26	5.1	1.34356123016641	1.4125	0.951193791268256	3.79588208225413
27	5.1	1.79601538902405	2.57083333333333	0.698612144839178	2.83961932128617
28	4.6	2.55555694872659	3.475	0.735412071575998	1.79999901872354
29	4.6	2.97527204514428	4.125	0.72127807155013	1.54607710831260
30	4.6	3.44875464064392	4.775	0.722252280763126	1.33381480543398
31	5.6	3.45037987709282	4.92083333333333	0.701177959781775	1.62300969733176
32	5.6	3.40257606491398	4.5625	0.745770096419503	1.64581184760129
33	5.6	3.46534398921668	4.20416666666667	0.824264179793858	1.61600118701804
34	5.1	2.41732322513124	4.08333333333333	0.591997524521936	2.10977164616582
35	5.1	2.92338301121827	4.2	0.696043574099588	1.74455416222545
36	5.1	4.48810899342882	4.31666666666667	1.03971636913409	1.13633603984820
37	0.8	16.1794602696106	4.52916666666667	3.57228193625257	0.0494454071192113
38	0.8	4.60139996526019	4.8375	0.951193791268256	0.173860130838412
39	0.8	3.59494166198493	5.14583333333333	0.698612144839178	0.222534904657753
40	6	4.00799579008919	5.45	0.735412071575998	1.49700756044619
41	6	4.14734891141324	5.75	0.72127807155013	1.44670731307134
42	6	4.36962629861691	6.05	0.722252280763126	1.37311513387292
43	9.3	4.64530398355426	6.625	0.701177959781775	2.00202183386162
44	9.3	5.57463147073578	7.475	0.745770096419503	1.66827171425065
45	9.3	6.86199929678387	8.325	0.824264179793858	1.35529014180441
46	8.7	5.24164474837131	8.85416666666667	0.591997524521936	1.65978436495592
47	8.7	6.30789489027751	9.0625	0.696043574099588	1.37922399648883
48	8.7	9.6390371721806	9.27083333333333	1.03971636913409	0.902579774783857
49	11	32.7608022570496	9.17083333333333	3.57228193625257	0.335767113201051
50	11	8.33483559598809	8.7625	0.951193791268256	1.31976208448488
51	11	5.83632229334396	8.35416666666666	0.698612144839178	1.88474855347604
52	8.5	5.80362693152058	7.89166666666667	0.735412071575998	1.46460137777549
53	8.5	5.3194257776822	7.375	0.72127807155013	1.59791683449405
54	8.5	4.95344689223377	6.85833333333333	0.722252280763126	1.71597681067837
55	4.4	4.31516602749034	6.15416666666667	0.701177959781775	1.01965949211901
56	4.4	3.92461513240763	5.2625	0.745770096419503	1.12112904107892
57	4.4	3.60272135251566	4.37083333333333	0.824264179793858	1.22129900413409
58	2.5	2.03992480324850	3.44583333333333	0.591997524521936	1.22553537072486
59	2.5	1.73140839057272	2.4875	0.696043574099588	1.44391121910472
60	2.5	1.58989961446754	1.52916666666667	1.03971636913409	1.57242632003358
61	0.3	NA	NA	NA	NA
62	0.3	NA	NA	NA	NA
63	0.3	NA	NA	NA	NA
64	-3	NA	NA	NA	NA
65	-3	NA	NA	NA	NA
66	-3	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 13.7 & NA & NA & 3.57228193625257 & NA \tabularnewline
2 & 13.7 & NA & NA & 0.951193791268256 & NA \tabularnewline
3 & 13.7 & NA & NA & 0.698612144839178 & NA \tabularnewline
4 & 1.3 & NA & NA & 0.735412071575998 & NA \tabularnewline
5 & 1.3 & NA & NA & 0.72127807155013 & NA \tabularnewline
6 & 1.3 & NA & NA & 0.722252280763126 & NA \tabularnewline
7 & -7.4 & -1.60978773266566 & -2.29583333333333 & 0.701177959781775 & 4.59687935858865 \tabularnewline
8 & -7.4 & -3.16020078357764 & -4.2375 & 0.745770096419503 & 2.34162336724140 \tabularnewline
9 & -7.4 & -5.09326574430955 & -6.17916666666667 & 0.824264179793858 & 1.45289886125962 \tabularnewline
10 & -12.9 & -4.53864768800151 & -7.66666666666667 & 0.591997524521936 & 2.84225630337045 \tabularnewline
11 & -12.9 & -6.05557909466641 & -8.7 & 0.696043574099588 & 2.13026694859984 \tabularnewline
12 & -12.9 & -10.1199059929051 & -9.73333333333333 & 1.03971636913409 & 1.27471539844777 \tabularnewline
13 & -9.6 & -36.7498504191983 & -10.2875 & 3.57228193625257 & 0.261225553042929 \tabularnewline
14 & -9.6 & -9.8567456620173 & -10.3625 & 0.951193791268256 & 0.973952289039306 \tabularnewline
15 & -9.6 & -7.29176426175891 & -10.4375 & 0.698612144839178 & 1.31655380719676 \tabularnewline
16 & -11.1 & -7.39089131933878 & -10.05 & 0.735412071575998 & 1.50184862967151 \tabularnewline
17 & -11.1 & -6.63575825826119 & -9.2 & 0.72127807155013 & 1.67275533073874 \tabularnewline
18 & -11.1 & -6.0308065443721 & -8.35 & 0.722252280763126 & 1.84054983663146 \tabularnewline
19 & -8.3 & -5.12736383090423 & -7.3125 & 0.701177959781775 & 1.61876556330434 \tabularnewline
20 & -8.3 & -4.53987546195372 & -6.0875 & 0.745770096419503 & 1.82824398368587 \tabularnewline
21 & -8.3 & -4.00798457424764 & -4.8625 & 0.824264179793858 & 2.07086625366018 \tabularnewline
22 & -2.7 & -2.12872443192679 & -3.59583333333333 & 0.591997524521936 & 1.26836520477013 \tabularnewline
23 & -2.7 & -1.59219967575281 & -2.2875 & 0.696043574099588 & 1.69576720879774 \tabularnewline
24 & -2.7 & -1.01805561144380 & -0.979166666666667 & 1.03971636913409 & 2.65211445195110 \tabularnewline
25 & 5.1 & 0.907954992130858 & 0.254166666666666 & 3.57228193625257 & 5.61701851325354 \tabularnewline
26 & 5.1 & 1.34356123016641 & 1.4125 & 0.951193791268256 & 3.79588208225413 \tabularnewline
27 & 5.1 & 1.79601538902405 & 2.57083333333333 & 0.698612144839178 & 2.83961932128617 \tabularnewline
28 & 4.6 & 2.55555694872659 & 3.475 & 0.735412071575998 & 1.79999901872354 \tabularnewline
29 & 4.6 & 2.97527204514428 & 4.125 & 0.72127807155013 & 1.54607710831260 \tabularnewline
30 & 4.6 & 3.44875464064392 & 4.775 & 0.722252280763126 & 1.33381480543398 \tabularnewline
31 & 5.6 & 3.45037987709282 & 4.92083333333333 & 0.701177959781775 & 1.62300969733176 \tabularnewline
32 & 5.6 & 3.40257606491398 & 4.5625 & 0.745770096419503 & 1.64581184760129 \tabularnewline
33 & 5.6 & 3.46534398921668 & 4.20416666666667 & 0.824264179793858 & 1.61600118701804 \tabularnewline
34 & 5.1 & 2.41732322513124 & 4.08333333333333 & 0.591997524521936 & 2.10977164616582 \tabularnewline
35 & 5.1 & 2.92338301121827 & 4.2 & 0.696043574099588 & 1.74455416222545 \tabularnewline
36 & 5.1 & 4.48810899342882 & 4.31666666666667 & 1.03971636913409 & 1.13633603984820 \tabularnewline
37 & 0.8 & 16.1794602696106 & 4.52916666666667 & 3.57228193625257 & 0.0494454071192113 \tabularnewline
38 & 0.8 & 4.60139996526019 & 4.8375 & 0.951193791268256 & 0.173860130838412 \tabularnewline
39 & 0.8 & 3.59494166198493 & 5.14583333333333 & 0.698612144839178 & 0.222534904657753 \tabularnewline
40 & 6 & 4.00799579008919 & 5.45 & 0.735412071575998 & 1.49700756044619 \tabularnewline
41 & 6 & 4.14734891141324 & 5.75 & 0.72127807155013 & 1.44670731307134 \tabularnewline
42 & 6 & 4.36962629861691 & 6.05 & 0.722252280763126 & 1.37311513387292 \tabularnewline
43 & 9.3 & 4.64530398355426 & 6.625 & 0.701177959781775 & 2.00202183386162 \tabularnewline
44 & 9.3 & 5.57463147073578 & 7.475 & 0.745770096419503 & 1.66827171425065 \tabularnewline
45 & 9.3 & 6.86199929678387 & 8.325 & 0.824264179793858 & 1.35529014180441 \tabularnewline
46 & 8.7 & 5.24164474837131 & 8.85416666666667 & 0.591997524521936 & 1.65978436495592 \tabularnewline
47 & 8.7 & 6.30789489027751 & 9.0625 & 0.696043574099588 & 1.37922399648883 \tabularnewline
48 & 8.7 & 9.6390371721806 & 9.27083333333333 & 1.03971636913409 & 0.902579774783857 \tabularnewline
49 & 11 & 32.7608022570496 & 9.17083333333333 & 3.57228193625257 & 0.335767113201051 \tabularnewline
50 & 11 & 8.33483559598809 & 8.7625 & 0.951193791268256 & 1.31976208448488 \tabularnewline
51 & 11 & 5.83632229334396 & 8.35416666666666 & 0.698612144839178 & 1.88474855347604 \tabularnewline
52 & 8.5 & 5.80362693152058 & 7.89166666666667 & 0.735412071575998 & 1.46460137777549 \tabularnewline
53 & 8.5 & 5.3194257776822 & 7.375 & 0.72127807155013 & 1.59791683449405 \tabularnewline
54 & 8.5 & 4.95344689223377 & 6.85833333333333 & 0.722252280763126 & 1.71597681067837 \tabularnewline
55 & 4.4 & 4.31516602749034 & 6.15416666666667 & 0.701177959781775 & 1.01965949211901 \tabularnewline
56 & 4.4 & 3.92461513240763 & 5.2625 & 0.745770096419503 & 1.12112904107892 \tabularnewline
57 & 4.4 & 3.60272135251566 & 4.37083333333333 & 0.824264179793858 & 1.22129900413409 \tabularnewline
58 & 2.5 & 2.03992480324850 & 3.44583333333333 & 0.591997524521936 & 1.22553537072486 \tabularnewline
59 & 2.5 & 1.73140839057272 & 2.4875 & 0.696043574099588 & 1.44391121910472 \tabularnewline
60 & 2.5 & 1.58989961446754 & 1.52916666666667 & 1.03971636913409 & 1.57242632003358 \tabularnewline
61 & 0.3 & NA & NA & NA & NA \tabularnewline
62 & 0.3 & NA & NA & NA & NA \tabularnewline
63 & 0.3 & NA & NA & NA & NA \tabularnewline
64 & -3 & NA & NA & NA & NA \tabularnewline
65 & -3 & NA & NA & NA & NA \tabularnewline
66 & -3 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115878&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]13.7[/C][C]NA[/C][C]NA[/C][C]3.57228193625257[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]13.7[/C][C]NA[/C][C]NA[/C][C]0.951193791268256[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]13.7[/C][C]NA[/C][C]NA[/C][C]0.698612144839178[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.3[/C][C]NA[/C][C]NA[/C][C]0.735412071575998[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.3[/C][C]NA[/C][C]NA[/C][C]0.72127807155013[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.3[/C][C]NA[/C][C]NA[/C][C]0.722252280763126[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]-7.4[/C][C]-1.60978773266566[/C][C]-2.29583333333333[/C][C]0.701177959781775[/C][C]4.59687935858865[/C][/ROW]
[ROW][C]8[/C][C]-7.4[/C][C]-3.16020078357764[/C][C]-4.2375[/C][C]0.745770096419503[/C][C]2.34162336724140[/C][/ROW]
[ROW][C]9[/C][C]-7.4[/C][C]-5.09326574430955[/C][C]-6.17916666666667[/C][C]0.824264179793858[/C][C]1.45289886125962[/C][/ROW]
[ROW][C]10[/C][C]-12.9[/C][C]-4.53864768800151[/C][C]-7.66666666666667[/C][C]0.591997524521936[/C][C]2.84225630337045[/C][/ROW]
[ROW][C]11[/C][C]-12.9[/C][C]-6.05557909466641[/C][C]-8.7[/C][C]0.696043574099588[/C][C]2.13026694859984[/C][/ROW]
[ROW][C]12[/C][C]-12.9[/C][C]-10.1199059929051[/C][C]-9.73333333333333[/C][C]1.03971636913409[/C][C]1.27471539844777[/C][/ROW]
[ROW][C]13[/C][C]-9.6[/C][C]-36.7498504191983[/C][C]-10.2875[/C][C]3.57228193625257[/C][C]0.261225553042929[/C][/ROW]
[ROW][C]14[/C][C]-9.6[/C][C]-9.8567456620173[/C][C]-10.3625[/C][C]0.951193791268256[/C][C]0.973952289039306[/C][/ROW]
[ROW][C]15[/C][C]-9.6[/C][C]-7.29176426175891[/C][C]-10.4375[/C][C]0.698612144839178[/C][C]1.31655380719676[/C][/ROW]
[ROW][C]16[/C][C]-11.1[/C][C]-7.39089131933878[/C][C]-10.05[/C][C]0.735412071575998[/C][C]1.50184862967151[/C][/ROW]
[ROW][C]17[/C][C]-11.1[/C][C]-6.63575825826119[/C][C]-9.2[/C][C]0.72127807155013[/C][C]1.67275533073874[/C][/ROW]
[ROW][C]18[/C][C]-11.1[/C][C]-6.0308065443721[/C][C]-8.35[/C][C]0.722252280763126[/C][C]1.84054983663146[/C][/ROW]
[ROW][C]19[/C][C]-8.3[/C][C]-5.12736383090423[/C][C]-7.3125[/C][C]0.701177959781775[/C][C]1.61876556330434[/C][/ROW]
[ROW][C]20[/C][C]-8.3[/C][C]-4.53987546195372[/C][C]-6.0875[/C][C]0.745770096419503[/C][C]1.82824398368587[/C][/ROW]
[ROW][C]21[/C][C]-8.3[/C][C]-4.00798457424764[/C][C]-4.8625[/C][C]0.824264179793858[/C][C]2.07086625366018[/C][/ROW]
[ROW][C]22[/C][C]-2.7[/C][C]-2.12872443192679[/C][C]-3.59583333333333[/C][C]0.591997524521936[/C][C]1.26836520477013[/C][/ROW]
[ROW][C]23[/C][C]-2.7[/C][C]-1.59219967575281[/C][C]-2.2875[/C][C]0.696043574099588[/C][C]1.69576720879774[/C][/ROW]
[ROW][C]24[/C][C]-2.7[/C][C]-1.01805561144380[/C][C]-0.979166666666667[/C][C]1.03971636913409[/C][C]2.65211445195110[/C][/ROW]
[ROW][C]25[/C][C]5.1[/C][C]0.907954992130858[/C][C]0.254166666666666[/C][C]3.57228193625257[/C][C]5.61701851325354[/C][/ROW]
[ROW][C]26[/C][C]5.1[/C][C]1.34356123016641[/C][C]1.4125[/C][C]0.951193791268256[/C][C]3.79588208225413[/C][/ROW]
[ROW][C]27[/C][C]5.1[/C][C]1.79601538902405[/C][C]2.57083333333333[/C][C]0.698612144839178[/C][C]2.83961932128617[/C][/ROW]
[ROW][C]28[/C][C]4.6[/C][C]2.55555694872659[/C][C]3.475[/C][C]0.735412071575998[/C][C]1.79999901872354[/C][/ROW]
[ROW][C]29[/C][C]4.6[/C][C]2.97527204514428[/C][C]4.125[/C][C]0.72127807155013[/C][C]1.54607710831260[/C][/ROW]
[ROW][C]30[/C][C]4.6[/C][C]3.44875464064392[/C][C]4.775[/C][C]0.722252280763126[/C][C]1.33381480543398[/C][/ROW]
[ROW][C]31[/C][C]5.6[/C][C]3.45037987709282[/C][C]4.92083333333333[/C][C]0.701177959781775[/C][C]1.62300969733176[/C][/ROW]
[ROW][C]32[/C][C]5.6[/C][C]3.40257606491398[/C][C]4.5625[/C][C]0.745770096419503[/C][C]1.64581184760129[/C][/ROW]
[ROW][C]33[/C][C]5.6[/C][C]3.46534398921668[/C][C]4.20416666666667[/C][C]0.824264179793858[/C][C]1.61600118701804[/C][/ROW]
[ROW][C]34[/C][C]5.1[/C][C]2.41732322513124[/C][C]4.08333333333333[/C][C]0.591997524521936[/C][C]2.10977164616582[/C][/ROW]
[ROW][C]35[/C][C]5.1[/C][C]2.92338301121827[/C][C]4.2[/C][C]0.696043574099588[/C][C]1.74455416222545[/C][/ROW]
[ROW][C]36[/C][C]5.1[/C][C]4.48810899342882[/C][C]4.31666666666667[/C][C]1.03971636913409[/C][C]1.13633603984820[/C][/ROW]
[ROW][C]37[/C][C]0.8[/C][C]16.1794602696106[/C][C]4.52916666666667[/C][C]3.57228193625257[/C][C]0.0494454071192113[/C][/ROW]
[ROW][C]38[/C][C]0.8[/C][C]4.60139996526019[/C][C]4.8375[/C][C]0.951193791268256[/C][C]0.173860130838412[/C][/ROW]
[ROW][C]39[/C][C]0.8[/C][C]3.59494166198493[/C][C]5.14583333333333[/C][C]0.698612144839178[/C][C]0.222534904657753[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]4.00799579008919[/C][C]5.45[/C][C]0.735412071575998[/C][C]1.49700756044619[/C][/ROW]
[ROW][C]41[/C][C]6[/C][C]4.14734891141324[/C][C]5.75[/C][C]0.72127807155013[/C][C]1.44670731307134[/C][/ROW]
[ROW][C]42[/C][C]6[/C][C]4.36962629861691[/C][C]6.05[/C][C]0.722252280763126[/C][C]1.37311513387292[/C][/ROW]
[ROW][C]43[/C][C]9.3[/C][C]4.64530398355426[/C][C]6.625[/C][C]0.701177959781775[/C][C]2.00202183386162[/C][/ROW]
[ROW][C]44[/C][C]9.3[/C][C]5.57463147073578[/C][C]7.475[/C][C]0.745770096419503[/C][C]1.66827171425065[/C][/ROW]
[ROW][C]45[/C][C]9.3[/C][C]6.86199929678387[/C][C]8.325[/C][C]0.824264179793858[/C][C]1.35529014180441[/C][/ROW]
[ROW][C]46[/C][C]8.7[/C][C]5.24164474837131[/C][C]8.85416666666667[/C][C]0.591997524521936[/C][C]1.65978436495592[/C][/ROW]
[ROW][C]47[/C][C]8.7[/C][C]6.30789489027751[/C][C]9.0625[/C][C]0.696043574099588[/C][C]1.37922399648883[/C][/ROW]
[ROW][C]48[/C][C]8.7[/C][C]9.6390371721806[/C][C]9.27083333333333[/C][C]1.03971636913409[/C][C]0.902579774783857[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]32.7608022570496[/C][C]9.17083333333333[/C][C]3.57228193625257[/C][C]0.335767113201051[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]8.33483559598809[/C][C]8.7625[/C][C]0.951193791268256[/C][C]1.31976208448488[/C][/ROW]
[ROW][C]51[/C][C]11[/C][C]5.83632229334396[/C][C]8.35416666666666[/C][C]0.698612144839178[/C][C]1.88474855347604[/C][/ROW]
[ROW][C]52[/C][C]8.5[/C][C]5.80362693152058[/C][C]7.89166666666667[/C][C]0.735412071575998[/C][C]1.46460137777549[/C][/ROW]
[ROW][C]53[/C][C]8.5[/C][C]5.3194257776822[/C][C]7.375[/C][C]0.72127807155013[/C][C]1.59791683449405[/C][/ROW]
[ROW][C]54[/C][C]8.5[/C][C]4.95344689223377[/C][C]6.85833333333333[/C][C]0.722252280763126[/C][C]1.71597681067837[/C][/ROW]
[ROW][C]55[/C][C]4.4[/C][C]4.31516602749034[/C][C]6.15416666666667[/C][C]0.701177959781775[/C][C]1.01965949211901[/C][/ROW]
[ROW][C]56[/C][C]4.4[/C][C]3.92461513240763[/C][C]5.2625[/C][C]0.745770096419503[/C][C]1.12112904107892[/C][/ROW]
[ROW][C]57[/C][C]4.4[/C][C]3.60272135251566[/C][C]4.37083333333333[/C][C]0.824264179793858[/C][C]1.22129900413409[/C][/ROW]
[ROW][C]58[/C][C]2.5[/C][C]2.03992480324850[/C][C]3.44583333333333[/C][C]0.591997524521936[/C][C]1.22553537072486[/C][/ROW]
[ROW][C]59[/C][C]2.5[/C][C]1.73140839057272[/C][C]2.4875[/C][C]0.696043574099588[/C][C]1.44391121910472[/C][/ROW]
[ROW][C]60[/C][C]2.5[/C][C]1.58989961446754[/C][C]1.52916666666667[/C][C]1.03971636913409[/C][C]1.57242632003358[/C][/ROW]
[ROW][C]61[/C][C]0.3[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]62[/C][C]0.3[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]63[/C][C]0.3[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]64[/C][C]-3[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]65[/C][C]-3[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]66[/C][C]-3[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115878&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115878&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	13.7	NA	NA	3.57228193625257	NA
2	13.7	NA	NA	0.951193791268256	NA
3	13.7	NA	NA	0.698612144839178	NA
4	1.3	NA	NA	0.735412071575998	NA
5	1.3	NA	NA	0.72127807155013	NA
6	1.3	NA	NA	0.722252280763126	NA
7	-7.4	-1.60978773266566	-2.29583333333333	0.701177959781775	4.59687935858865
8	-7.4	-3.16020078357764	-4.2375	0.745770096419503	2.34162336724140
9	-7.4	-5.09326574430955	-6.17916666666667	0.824264179793858	1.45289886125962
10	-12.9	-4.53864768800151	-7.66666666666667	0.591997524521936	2.84225630337045
11	-12.9	-6.05557909466641	-8.7	0.696043574099588	2.13026694859984
12	-12.9	-10.1199059929051	-9.73333333333333	1.03971636913409	1.27471539844777
13	-9.6	-36.7498504191983	-10.2875	3.57228193625257	0.261225553042929
14	-9.6	-9.8567456620173	-10.3625	0.951193791268256	0.973952289039306
15	-9.6	-7.29176426175891	-10.4375	0.698612144839178	1.31655380719676
16	-11.1	-7.39089131933878	-10.05	0.735412071575998	1.50184862967151
17	-11.1	-6.63575825826119	-9.2	0.72127807155013	1.67275533073874
18	-11.1	-6.0308065443721	-8.35	0.722252280763126	1.84054983663146
19	-8.3	-5.12736383090423	-7.3125	0.701177959781775	1.61876556330434
20	-8.3	-4.53987546195372	-6.0875	0.745770096419503	1.82824398368587
21	-8.3	-4.00798457424764	-4.8625	0.824264179793858	2.07086625366018
22	-2.7	-2.12872443192679	-3.59583333333333	0.591997524521936	1.26836520477013
23	-2.7	-1.59219967575281	-2.2875	0.696043574099588	1.69576720879774
24	-2.7	-1.01805561144380	-0.979166666666667	1.03971636913409	2.65211445195110
25	5.1	0.907954992130858	0.254166666666666	3.57228193625257	5.61701851325354
26	5.1	1.34356123016641	1.4125	0.951193791268256	3.79588208225413
27	5.1	1.79601538902405	2.57083333333333	0.698612144839178	2.83961932128617
28	4.6	2.55555694872659	3.475	0.735412071575998	1.79999901872354
29	4.6	2.97527204514428	4.125	0.72127807155013	1.54607710831260
30	4.6	3.44875464064392	4.775	0.722252280763126	1.33381480543398
31	5.6	3.45037987709282	4.92083333333333	0.701177959781775	1.62300969733176
32	5.6	3.40257606491398	4.5625	0.745770096419503	1.64581184760129
33	5.6	3.46534398921668	4.20416666666667	0.824264179793858	1.61600118701804
34	5.1	2.41732322513124	4.08333333333333	0.591997524521936	2.10977164616582
35	5.1	2.92338301121827	4.2	0.696043574099588	1.74455416222545
36	5.1	4.48810899342882	4.31666666666667	1.03971636913409	1.13633603984820
37	0.8	16.1794602696106	4.52916666666667	3.57228193625257	0.0494454071192113
38	0.8	4.60139996526019	4.8375	0.951193791268256	0.173860130838412
39	0.8	3.59494166198493	5.14583333333333	0.698612144839178	0.222534904657753
40	6	4.00799579008919	5.45	0.735412071575998	1.49700756044619
41	6	4.14734891141324	5.75	0.72127807155013	1.44670731307134
42	6	4.36962629861691	6.05	0.722252280763126	1.37311513387292
43	9.3	4.64530398355426	6.625	0.701177959781775	2.00202183386162
44	9.3	5.57463147073578	7.475	0.745770096419503	1.66827171425065
45	9.3	6.86199929678387	8.325	0.824264179793858	1.35529014180441
46	8.7	5.24164474837131	8.85416666666667	0.591997524521936	1.65978436495592
47	8.7	6.30789489027751	9.0625	0.696043574099588	1.37922399648883
48	8.7	9.6390371721806	9.27083333333333	1.03971636913409	0.902579774783857
49	11	32.7608022570496	9.17083333333333	3.57228193625257	0.335767113201051
50	11	8.33483559598809	8.7625	0.951193791268256	1.31976208448488
51	11	5.83632229334396	8.35416666666666	0.698612144839178	1.88474855347604
52	8.5	5.80362693152058	7.89166666666667	0.735412071575998	1.46460137777549
53	8.5	5.3194257776822	7.375	0.72127807155013	1.59791683449405
54	8.5	4.95344689223377	6.85833333333333	0.722252280763126	1.71597681067837
55	4.4	4.31516602749034	6.15416666666667	0.701177959781775	1.01965949211901
56	4.4	3.92461513240763	5.2625	0.745770096419503	1.12112904107892
57	4.4	3.60272135251566	4.37083333333333	0.824264179793858	1.22129900413409
58	2.5	2.03992480324850	3.44583333333333	0.591997524521936	1.22553537072486
59	2.5	1.73140839057272	2.4875	0.696043574099588	1.44391121910472
60	2.5	1.58989961446754	1.52916666666667	1.03971636913409	1.57242632003358
61	0.3	NA	NA	NA	NA
62	0.3	NA	NA	NA	NA
63	0.3	NA	NA	NA	NA
64	-3	NA	NA	NA	NA
65	-3	NA	NA	NA	NA
66	-3	NA	NA	NA	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
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