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, 02 May 2013 03:44:08 -0400

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/2013/May/02/t1367480709lwq2wvbbucch694.htm/, Retrieved Fri, 03 May 2024 21:25:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208645, Retrieved Fri, 03 May 2024 21:25:34 +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

132

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

-       [Classical Decomposition] [addi eigen cijfers] [2013-05-02 07:44:08] [5f178b5bce8a01d64692a8a5c649399b] [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	3 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208645&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208645&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208645&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	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	599	NA	NA	2.70481249999999	NA
2	599	NA	NA	1.6003125	NA
3	599	NA	NA	0.495812499999996	NA
4	599	NA	NA	-0.533437499999983	NA
5	599	NA	NA	-1.48743749999998	NA
6	599	NA	NA	-2.44143749999995	NA
7	599	600.3453125	604.2675	-3.92218750000001	-1.34531249999998
8	599	600.7458125	605.7725	-5.0266875	-1.74581250000006
9	599	601.1463125	607.2775	-6.13118750000003	-2.14631250000002
10	617.06	614.8008125	608.7825	6.01831249999999	2.25918749999994
11	617.06	615.2013125	610.2875	4.91381249999998	1.85868749999997
12	617.06	615.6018125	611.7925	3.80931249999999	1.45818749999989
13	617.06	616.0023125	613.2975	2.70481249999999	1.05768749999993
14	617.06	616.4028125	614.8025	1.6003125	0.657187499999964
15	617.06	616.8033125	616.3075	0.495812499999996	0.256687499999998
16	617.06	616.989895833333	617.523333333333	-0.533437499999983	0.0701041666666242
17	617.06	616.9625625	618.45	-1.48743749999998	0.0974374999999554
18	617.06	616.935229166667	619.376666666667	-2.44143749999995	0.1247708333334
19	617.06	616.381145833333	620.303333333333	-3.92218750000001	0.678854166666724
20	617.06	616.2033125	621.23	-5.0266875	0.856687500000021
21	617.06	616.025479166667	622.156666666667	-6.13118750000003	1.03452083333332
22	628.18	629.101645833333	623.083333333333	6.01831249999999	-0.921645833333287
23	628.18	628.9238125	624.01	4.91381249999998	-0.743812499999876
24	628.18	628.745979166667	624.936666666666	3.80931249999999	-0.56597916666658
25	628.18	628.568145833333	625.863333333333	2.70481249999999	-0.388145833333169
26	628.18	628.3903125	626.79	1.6003125	-0.210312499999759
27	628.18	628.212479166666	627.716666666666	0.495812499999996	-0.0324791666664623
28	628.18	628.1840625	628.7175	-0.533437499999983	-0.00406249999991815
29	628.18	628.3050625	629.7925	-1.48743749999998	-0.125062500000013
30	628.18	628.4260625	630.8675	-2.44143749999995	-0.24606249999988
31	628.18	628.0203125	631.9425	-3.92218750000001	0.159687500000132
32	628.18	627.9908125	633.0175	-5.0266875	0.189187500000003
33	628.18	627.9613125	634.0925	-6.13118750000003	0.218687499999987
34	641.08	641.1858125	635.1675	6.01831249999999	-0.105812499999956
35	641.08	641.1563125	636.2425	4.91381249999998	-0.0763124999999718
36	641.08	641.1268125	637.3175	3.80931249999999	-0.046812500000101
37	641.08	641.0973125	638.3925	2.70481249999999	-0.0173125000001164
38	641.08	641.0678125	639.4675	1.6003125	0.0121874999999818
39	641.08	641.0383125	640.5425	0.495812499999996	0.04168750000008
40	641.08	641.676979166667	642.210416666667	-0.533437499999983	-0.596979166666642
41	641.08	642.9838125	644.47125	-1.48743749999998	-1.90381250000007
42	641.08	644.290645833333	646.732083333333	-2.44143749999995	-3.21064583333327
43	641.08	645.070729166667	648.992916666667	-3.92218750000001	-3.9907291666666
44	641.08	646.2270625	651.25375	-5.0266875	-5.14706249999995
45	641.08	647.383395833333	653.514583333333	-6.13118750000003	-6.3033958333333
46	668.21	661.793729166667	655.775416666667	6.01831249999999	6.41627083333344
47	668.21	662.9500625	658.03625	4.91381249999998	5.25993750000009
48	668.21	664.106395833333	660.297083333333	3.80931249999999	4.10360416666674
49	668.21	665.262729166667	662.557916666667	2.70481249999999	2.94727083333339
50	668.21	666.4190625	664.81875	1.6003125	1.79093750000004
51	668.21	667.575395833333	667.079583333333	0.495812499999996	0.634604166666691
52	668.21	667.5540625	668.0875	-0.533437499999983	0.65593750000005
53	668.21	666.3550625	667.8425	-1.48743749999998	1.85493750000001
54	668.21	665.1560625	667.5975	-2.44143749999995	3.05393750000007
55	668.21	663.4303125	667.3525	-3.92218750000001	4.77968750000014
56	668.21	662.0808125	667.1075	-5.0266875	6.12918750000006
57	668.21	660.7313125	666.8625	-6.13118750000003	7.47868750000009
58	665.27	672.6358125	666.6175	6.01831249999999	-7.36581249999995
59	665.27	671.2863125	666.3725	4.91381249999998	-6.01631249999991
60	665.27	669.9368125	666.1275	3.80931249999999	-4.66681249999999
61	665.27	668.5873125	665.8825	2.70481249999999	-3.31731249999996
62	665.27	667.2378125	665.6375	1.6003125	-1.96781249999992
63	665.27	665.8883125	665.3925	0.495812499999996	-0.618312499999888
64	665.27	665.1128125	665.64625	-0.533437499999983	0.157187500000077
65	665.27	664.9113125	666.39875	-1.48743749999998	0.358687500000087
66	665.27	664.7098125	667.15125	-2.44143749999995	0.560187500000097
67	665.27	NA	NA	-3.92218750000001	NA
68	665.27	NA	NA	-5.0266875	NA
69	665.27	NA	NA	-6.13118750000003	NA
70	674.3	NA	NA	6.01831249999999	NA
71	674.3	NA	NA	4.91381249999998	NA
72	674.3	NA	NA	3.80931249999999	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 599 & NA & NA & 2.70481249999999 & NA \tabularnewline
2 & 599 & NA & NA & 1.6003125 & NA \tabularnewline
3 & 599 & NA & NA & 0.495812499999996 & NA \tabularnewline
4 & 599 & NA & NA & -0.533437499999983 & NA \tabularnewline
5 & 599 & NA & NA & -1.48743749999998 & NA \tabularnewline
6 & 599 & NA & NA & -2.44143749999995 & NA \tabularnewline
7 & 599 & 600.3453125 & 604.2675 & -3.92218750000001 & -1.34531249999998 \tabularnewline
8 & 599 & 600.7458125 & 605.7725 & -5.0266875 & -1.74581250000006 \tabularnewline
9 & 599 & 601.1463125 & 607.2775 & -6.13118750000003 & -2.14631250000002 \tabularnewline
10 & 617.06 & 614.8008125 & 608.7825 & 6.01831249999999 & 2.25918749999994 \tabularnewline
11 & 617.06 & 615.2013125 & 610.2875 & 4.91381249999998 & 1.85868749999997 \tabularnewline
12 & 617.06 & 615.6018125 & 611.7925 & 3.80931249999999 & 1.45818749999989 \tabularnewline
13 & 617.06 & 616.0023125 & 613.2975 & 2.70481249999999 & 1.05768749999993 \tabularnewline
14 & 617.06 & 616.4028125 & 614.8025 & 1.6003125 & 0.657187499999964 \tabularnewline
15 & 617.06 & 616.8033125 & 616.3075 & 0.495812499999996 & 0.256687499999998 \tabularnewline
16 & 617.06 & 616.989895833333 & 617.523333333333 & -0.533437499999983 & 0.0701041666666242 \tabularnewline
17 & 617.06 & 616.9625625 & 618.45 & -1.48743749999998 & 0.0974374999999554 \tabularnewline
18 & 617.06 & 616.935229166667 & 619.376666666667 & -2.44143749999995 & 0.1247708333334 \tabularnewline
19 & 617.06 & 616.381145833333 & 620.303333333333 & -3.92218750000001 & 0.678854166666724 \tabularnewline
20 & 617.06 & 616.2033125 & 621.23 & -5.0266875 & 0.856687500000021 \tabularnewline
21 & 617.06 & 616.025479166667 & 622.156666666667 & -6.13118750000003 & 1.03452083333332 \tabularnewline
22 & 628.18 & 629.101645833333 & 623.083333333333 & 6.01831249999999 & -0.921645833333287 \tabularnewline
23 & 628.18 & 628.9238125 & 624.01 & 4.91381249999998 & -0.743812499999876 \tabularnewline
24 & 628.18 & 628.745979166667 & 624.936666666666 & 3.80931249999999 & -0.56597916666658 \tabularnewline
25 & 628.18 & 628.568145833333 & 625.863333333333 & 2.70481249999999 & -0.388145833333169 \tabularnewline
26 & 628.18 & 628.3903125 & 626.79 & 1.6003125 & -0.210312499999759 \tabularnewline
27 & 628.18 & 628.212479166666 & 627.716666666666 & 0.495812499999996 & -0.0324791666664623 \tabularnewline
28 & 628.18 & 628.1840625 & 628.7175 & -0.533437499999983 & -0.00406249999991815 \tabularnewline
29 & 628.18 & 628.3050625 & 629.7925 & -1.48743749999998 & -0.125062500000013 \tabularnewline
30 & 628.18 & 628.4260625 & 630.8675 & -2.44143749999995 & -0.24606249999988 \tabularnewline
31 & 628.18 & 628.0203125 & 631.9425 & -3.92218750000001 & 0.159687500000132 \tabularnewline
32 & 628.18 & 627.9908125 & 633.0175 & -5.0266875 & 0.189187500000003 \tabularnewline
33 & 628.18 & 627.9613125 & 634.0925 & -6.13118750000003 & 0.218687499999987 \tabularnewline
34 & 641.08 & 641.1858125 & 635.1675 & 6.01831249999999 & -0.105812499999956 \tabularnewline
35 & 641.08 & 641.1563125 & 636.2425 & 4.91381249999998 & -0.0763124999999718 \tabularnewline
36 & 641.08 & 641.1268125 & 637.3175 & 3.80931249999999 & -0.046812500000101 \tabularnewline
37 & 641.08 & 641.0973125 & 638.3925 & 2.70481249999999 & -0.0173125000001164 \tabularnewline
38 & 641.08 & 641.0678125 & 639.4675 & 1.6003125 & 0.0121874999999818 \tabularnewline
39 & 641.08 & 641.0383125 & 640.5425 & 0.495812499999996 & 0.04168750000008 \tabularnewline
40 & 641.08 & 641.676979166667 & 642.210416666667 & -0.533437499999983 & -0.596979166666642 \tabularnewline
41 & 641.08 & 642.9838125 & 644.47125 & -1.48743749999998 & -1.90381250000007 \tabularnewline
42 & 641.08 & 644.290645833333 & 646.732083333333 & -2.44143749999995 & -3.21064583333327 \tabularnewline
43 & 641.08 & 645.070729166667 & 648.992916666667 & -3.92218750000001 & -3.9907291666666 \tabularnewline
44 & 641.08 & 646.2270625 & 651.25375 & -5.0266875 & -5.14706249999995 \tabularnewline
45 & 641.08 & 647.383395833333 & 653.514583333333 & -6.13118750000003 & -6.3033958333333 \tabularnewline
46 & 668.21 & 661.793729166667 & 655.775416666667 & 6.01831249999999 & 6.41627083333344 \tabularnewline
47 & 668.21 & 662.9500625 & 658.03625 & 4.91381249999998 & 5.25993750000009 \tabularnewline
48 & 668.21 & 664.106395833333 & 660.297083333333 & 3.80931249999999 & 4.10360416666674 \tabularnewline
49 & 668.21 & 665.262729166667 & 662.557916666667 & 2.70481249999999 & 2.94727083333339 \tabularnewline
50 & 668.21 & 666.4190625 & 664.81875 & 1.6003125 & 1.79093750000004 \tabularnewline
51 & 668.21 & 667.575395833333 & 667.079583333333 & 0.495812499999996 & 0.634604166666691 \tabularnewline
52 & 668.21 & 667.5540625 & 668.0875 & -0.533437499999983 & 0.65593750000005 \tabularnewline
53 & 668.21 & 666.3550625 & 667.8425 & -1.48743749999998 & 1.85493750000001 \tabularnewline
54 & 668.21 & 665.1560625 & 667.5975 & -2.44143749999995 & 3.05393750000007 \tabularnewline
55 & 668.21 & 663.4303125 & 667.3525 & -3.92218750000001 & 4.77968750000014 \tabularnewline
56 & 668.21 & 662.0808125 & 667.1075 & -5.0266875 & 6.12918750000006 \tabularnewline
57 & 668.21 & 660.7313125 & 666.8625 & -6.13118750000003 & 7.47868750000009 \tabularnewline
58 & 665.27 & 672.6358125 & 666.6175 & 6.01831249999999 & -7.36581249999995 \tabularnewline
59 & 665.27 & 671.2863125 & 666.3725 & 4.91381249999998 & -6.01631249999991 \tabularnewline
60 & 665.27 & 669.9368125 & 666.1275 & 3.80931249999999 & -4.66681249999999 \tabularnewline
61 & 665.27 & 668.5873125 & 665.8825 & 2.70481249999999 & -3.31731249999996 \tabularnewline
62 & 665.27 & 667.2378125 & 665.6375 & 1.6003125 & -1.96781249999992 \tabularnewline
63 & 665.27 & 665.8883125 & 665.3925 & 0.495812499999996 & -0.618312499999888 \tabularnewline
64 & 665.27 & 665.1128125 & 665.64625 & -0.533437499999983 & 0.157187500000077 \tabularnewline
65 & 665.27 & 664.9113125 & 666.39875 & -1.48743749999998 & 0.358687500000087 \tabularnewline
66 & 665.27 & 664.7098125 & 667.15125 & -2.44143749999995 & 0.560187500000097 \tabularnewline
67 & 665.27 & NA & NA & -3.92218750000001 & NA \tabularnewline
68 & 665.27 & NA & NA & -5.0266875 & NA \tabularnewline
69 & 665.27 & NA & NA & -6.13118750000003 & NA \tabularnewline
70 & 674.3 & NA & NA & 6.01831249999999 & NA \tabularnewline
71 & 674.3 & NA & NA & 4.91381249999998 & NA \tabularnewline
72 & 674.3 & NA & NA & 3.80931249999999 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208645&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]599[/C][C]NA[/C][C]NA[/C][C]2.70481249999999[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]599[/C][C]NA[/C][C]NA[/C][C]1.6003125[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]599[/C][C]NA[/C][C]NA[/C][C]0.495812499999996[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]599[/C][C]NA[/C][C]NA[/C][C]-0.533437499999983[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]599[/C][C]NA[/C][C]NA[/C][C]-1.48743749999998[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]599[/C][C]NA[/C][C]NA[/C][C]-2.44143749999995[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]599[/C][C]600.3453125[/C][C]604.2675[/C][C]-3.92218750000001[/C][C]-1.34531249999998[/C][/ROW]
[ROW][C]8[/C][C]599[/C][C]600.7458125[/C][C]605.7725[/C][C]-5.0266875[/C][C]-1.74581250000006[/C][/ROW]
[ROW][C]9[/C][C]599[/C][C]601.1463125[/C][C]607.2775[/C][C]-6.13118750000003[/C][C]-2.14631250000002[/C][/ROW]
[ROW][C]10[/C][C]617.06[/C][C]614.8008125[/C][C]608.7825[/C][C]6.01831249999999[/C][C]2.25918749999994[/C][/ROW]
[ROW][C]11[/C][C]617.06[/C][C]615.2013125[/C][C]610.2875[/C][C]4.91381249999998[/C][C]1.85868749999997[/C][/ROW]
[ROW][C]12[/C][C]617.06[/C][C]615.6018125[/C][C]611.7925[/C][C]3.80931249999999[/C][C]1.45818749999989[/C][/ROW]
[ROW][C]13[/C][C]617.06[/C][C]616.0023125[/C][C]613.2975[/C][C]2.70481249999999[/C][C]1.05768749999993[/C][/ROW]
[ROW][C]14[/C][C]617.06[/C][C]616.4028125[/C][C]614.8025[/C][C]1.6003125[/C][C]0.657187499999964[/C][/ROW]
[ROW][C]15[/C][C]617.06[/C][C]616.8033125[/C][C]616.3075[/C][C]0.495812499999996[/C][C]0.256687499999998[/C][/ROW]
[ROW][C]16[/C][C]617.06[/C][C]616.989895833333[/C][C]617.523333333333[/C][C]-0.533437499999983[/C][C]0.0701041666666242[/C][/ROW]
[ROW][C]17[/C][C]617.06[/C][C]616.9625625[/C][C]618.45[/C][C]-1.48743749999998[/C][C]0.0974374999999554[/C][/ROW]
[ROW][C]18[/C][C]617.06[/C][C]616.935229166667[/C][C]619.376666666667[/C][C]-2.44143749999995[/C][C]0.1247708333334[/C][/ROW]
[ROW][C]19[/C][C]617.06[/C][C]616.381145833333[/C][C]620.303333333333[/C][C]-3.92218750000001[/C][C]0.678854166666724[/C][/ROW]
[ROW][C]20[/C][C]617.06[/C][C]616.2033125[/C][C]621.23[/C][C]-5.0266875[/C][C]0.856687500000021[/C][/ROW]
[ROW][C]21[/C][C]617.06[/C][C]616.025479166667[/C][C]622.156666666667[/C][C]-6.13118750000003[/C][C]1.03452083333332[/C][/ROW]
[ROW][C]22[/C][C]628.18[/C][C]629.101645833333[/C][C]623.083333333333[/C][C]6.01831249999999[/C][C]-0.921645833333287[/C][/ROW]
[ROW][C]23[/C][C]628.18[/C][C]628.9238125[/C][C]624.01[/C][C]4.91381249999998[/C][C]-0.743812499999876[/C][/ROW]
[ROW][C]24[/C][C]628.18[/C][C]628.745979166667[/C][C]624.936666666666[/C][C]3.80931249999999[/C][C]-0.56597916666658[/C][/ROW]
[ROW][C]25[/C][C]628.18[/C][C]628.568145833333[/C][C]625.863333333333[/C][C]2.70481249999999[/C][C]-0.388145833333169[/C][/ROW]
[ROW][C]26[/C][C]628.18[/C][C]628.3903125[/C][C]626.79[/C][C]1.6003125[/C][C]-0.210312499999759[/C][/ROW]
[ROW][C]27[/C][C]628.18[/C][C]628.212479166666[/C][C]627.716666666666[/C][C]0.495812499999996[/C][C]-0.0324791666664623[/C][/ROW]
[ROW][C]28[/C][C]628.18[/C][C]628.1840625[/C][C]628.7175[/C][C]-0.533437499999983[/C][C]-0.00406249999991815[/C][/ROW]
[ROW][C]29[/C][C]628.18[/C][C]628.3050625[/C][C]629.7925[/C][C]-1.48743749999998[/C][C]-0.125062500000013[/C][/ROW]
[ROW][C]30[/C][C]628.18[/C][C]628.4260625[/C][C]630.8675[/C][C]-2.44143749999995[/C][C]-0.24606249999988[/C][/ROW]
[ROW][C]31[/C][C]628.18[/C][C]628.0203125[/C][C]631.9425[/C][C]-3.92218750000001[/C][C]0.159687500000132[/C][/ROW]
[ROW][C]32[/C][C]628.18[/C][C]627.9908125[/C][C]633.0175[/C][C]-5.0266875[/C][C]0.189187500000003[/C][/ROW]
[ROW][C]33[/C][C]628.18[/C][C]627.9613125[/C][C]634.0925[/C][C]-6.13118750000003[/C][C]0.218687499999987[/C][/ROW]
[ROW][C]34[/C][C]641.08[/C][C]641.1858125[/C][C]635.1675[/C][C]6.01831249999999[/C][C]-0.105812499999956[/C][/ROW]
[ROW][C]35[/C][C]641.08[/C][C]641.1563125[/C][C]636.2425[/C][C]4.91381249999998[/C][C]-0.0763124999999718[/C][/ROW]
[ROW][C]36[/C][C]641.08[/C][C]641.1268125[/C][C]637.3175[/C][C]3.80931249999999[/C][C]-0.046812500000101[/C][/ROW]
[ROW][C]37[/C][C]641.08[/C][C]641.0973125[/C][C]638.3925[/C][C]2.70481249999999[/C][C]-0.0173125000001164[/C][/ROW]
[ROW][C]38[/C][C]641.08[/C][C]641.0678125[/C][C]639.4675[/C][C]1.6003125[/C][C]0.0121874999999818[/C][/ROW]
[ROW][C]39[/C][C]641.08[/C][C]641.0383125[/C][C]640.5425[/C][C]0.495812499999996[/C][C]0.04168750000008[/C][/ROW]
[ROW][C]40[/C][C]641.08[/C][C]641.676979166667[/C][C]642.210416666667[/C][C]-0.533437499999983[/C][C]-0.596979166666642[/C][/ROW]
[ROW][C]41[/C][C]641.08[/C][C]642.9838125[/C][C]644.47125[/C][C]-1.48743749999998[/C][C]-1.90381250000007[/C][/ROW]
[ROW][C]42[/C][C]641.08[/C][C]644.290645833333[/C][C]646.732083333333[/C][C]-2.44143749999995[/C][C]-3.21064583333327[/C][/ROW]
[ROW][C]43[/C][C]641.08[/C][C]645.070729166667[/C][C]648.992916666667[/C][C]-3.92218750000001[/C][C]-3.9907291666666[/C][/ROW]
[ROW][C]44[/C][C]641.08[/C][C]646.2270625[/C][C]651.25375[/C][C]-5.0266875[/C][C]-5.14706249999995[/C][/ROW]
[ROW][C]45[/C][C]641.08[/C][C]647.383395833333[/C][C]653.514583333333[/C][C]-6.13118750000003[/C][C]-6.3033958333333[/C][/ROW]
[ROW][C]46[/C][C]668.21[/C][C]661.793729166667[/C][C]655.775416666667[/C][C]6.01831249999999[/C][C]6.41627083333344[/C][/ROW]
[ROW][C]47[/C][C]668.21[/C][C]662.9500625[/C][C]658.03625[/C][C]4.91381249999998[/C][C]5.25993750000009[/C][/ROW]
[ROW][C]48[/C][C]668.21[/C][C]664.106395833333[/C][C]660.297083333333[/C][C]3.80931249999999[/C][C]4.10360416666674[/C][/ROW]
[ROW][C]49[/C][C]668.21[/C][C]665.262729166667[/C][C]662.557916666667[/C][C]2.70481249999999[/C][C]2.94727083333339[/C][/ROW]
[ROW][C]50[/C][C]668.21[/C][C]666.4190625[/C][C]664.81875[/C][C]1.6003125[/C][C]1.79093750000004[/C][/ROW]
[ROW][C]51[/C][C]668.21[/C][C]667.575395833333[/C][C]667.079583333333[/C][C]0.495812499999996[/C][C]0.634604166666691[/C][/ROW]
[ROW][C]52[/C][C]668.21[/C][C]667.5540625[/C][C]668.0875[/C][C]-0.533437499999983[/C][C]0.65593750000005[/C][/ROW]
[ROW][C]53[/C][C]668.21[/C][C]666.3550625[/C][C]667.8425[/C][C]-1.48743749999998[/C][C]1.85493750000001[/C][/ROW]
[ROW][C]54[/C][C]668.21[/C][C]665.1560625[/C][C]667.5975[/C][C]-2.44143749999995[/C][C]3.05393750000007[/C][/ROW]
[ROW][C]55[/C][C]668.21[/C][C]663.4303125[/C][C]667.3525[/C][C]-3.92218750000001[/C][C]4.77968750000014[/C][/ROW]
[ROW][C]56[/C][C]668.21[/C][C]662.0808125[/C][C]667.1075[/C][C]-5.0266875[/C][C]6.12918750000006[/C][/ROW]
[ROW][C]57[/C][C]668.21[/C][C]660.7313125[/C][C]666.8625[/C][C]-6.13118750000003[/C][C]7.47868750000009[/C][/ROW]
[ROW][C]58[/C][C]665.27[/C][C]672.6358125[/C][C]666.6175[/C][C]6.01831249999999[/C][C]-7.36581249999995[/C][/ROW]
[ROW][C]59[/C][C]665.27[/C][C]671.2863125[/C][C]666.3725[/C][C]4.91381249999998[/C][C]-6.01631249999991[/C][/ROW]
[ROW][C]60[/C][C]665.27[/C][C]669.9368125[/C][C]666.1275[/C][C]3.80931249999999[/C][C]-4.66681249999999[/C][/ROW]
[ROW][C]61[/C][C]665.27[/C][C]668.5873125[/C][C]665.8825[/C][C]2.70481249999999[/C][C]-3.31731249999996[/C][/ROW]
[ROW][C]62[/C][C]665.27[/C][C]667.2378125[/C][C]665.6375[/C][C]1.6003125[/C][C]-1.96781249999992[/C][/ROW]
[ROW][C]63[/C][C]665.27[/C][C]665.8883125[/C][C]665.3925[/C][C]0.495812499999996[/C][C]-0.618312499999888[/C][/ROW]
[ROW][C]64[/C][C]665.27[/C][C]665.1128125[/C][C]665.64625[/C][C]-0.533437499999983[/C][C]0.157187500000077[/C][/ROW]
[ROW][C]65[/C][C]665.27[/C][C]664.9113125[/C][C]666.39875[/C][C]-1.48743749999998[/C][C]0.358687500000087[/C][/ROW]
[ROW][C]66[/C][C]665.27[/C][C]664.7098125[/C][C]667.15125[/C][C]-2.44143749999995[/C][C]0.560187500000097[/C][/ROW]
[ROW][C]67[/C][C]665.27[/C][C]NA[/C][C]NA[/C][C]-3.92218750000001[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]665.27[/C][C]NA[/C][C]NA[/C][C]-5.0266875[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]665.27[/C][C]NA[/C][C]NA[/C][C]-6.13118750000003[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]674.3[/C][C]NA[/C][C]NA[/C][C]6.01831249999999[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]674.3[/C][C]NA[/C][C]NA[/C][C]4.91381249999998[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]674.3[/C][C]NA[/C][C]NA[/C][C]3.80931249999999[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208645&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208645&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	599	NA	NA	2.70481249999999	NA
2	599	NA	NA	1.6003125	NA
3	599	NA	NA	0.495812499999996	NA
4	599	NA	NA	-0.533437499999983	NA
5	599	NA	NA	-1.48743749999998	NA
6	599	NA	NA	-2.44143749999995	NA
7	599	600.3453125	604.2675	-3.92218750000001	-1.34531249999998
8	599	600.7458125	605.7725	-5.0266875	-1.74581250000006
9	599	601.1463125	607.2775	-6.13118750000003	-2.14631250000002
10	617.06	614.8008125	608.7825	6.01831249999999	2.25918749999994
11	617.06	615.2013125	610.2875	4.91381249999998	1.85868749999997
12	617.06	615.6018125	611.7925	3.80931249999999	1.45818749999989
13	617.06	616.0023125	613.2975	2.70481249999999	1.05768749999993
14	617.06	616.4028125	614.8025	1.6003125	0.657187499999964
15	617.06	616.8033125	616.3075	0.495812499999996	0.256687499999998
16	617.06	616.989895833333	617.523333333333	-0.533437499999983	0.0701041666666242
17	617.06	616.9625625	618.45	-1.48743749999998	0.0974374999999554
18	617.06	616.935229166667	619.376666666667	-2.44143749999995	0.1247708333334
19	617.06	616.381145833333	620.303333333333	-3.92218750000001	0.678854166666724
20	617.06	616.2033125	621.23	-5.0266875	0.856687500000021
21	617.06	616.025479166667	622.156666666667	-6.13118750000003	1.03452083333332
22	628.18	629.101645833333	623.083333333333	6.01831249999999	-0.921645833333287
23	628.18	628.9238125	624.01	4.91381249999998	-0.743812499999876
24	628.18	628.745979166667	624.936666666666	3.80931249999999	-0.56597916666658
25	628.18	628.568145833333	625.863333333333	2.70481249999999	-0.388145833333169
26	628.18	628.3903125	626.79	1.6003125	-0.210312499999759
27	628.18	628.212479166666	627.716666666666	0.495812499999996	-0.0324791666664623
28	628.18	628.1840625	628.7175	-0.533437499999983	-0.00406249999991815
29	628.18	628.3050625	629.7925	-1.48743749999998	-0.125062500000013
30	628.18	628.4260625	630.8675	-2.44143749999995	-0.24606249999988
31	628.18	628.0203125	631.9425	-3.92218750000001	0.159687500000132
32	628.18	627.9908125	633.0175	-5.0266875	0.189187500000003
33	628.18	627.9613125	634.0925	-6.13118750000003	0.218687499999987
34	641.08	641.1858125	635.1675	6.01831249999999	-0.105812499999956
35	641.08	641.1563125	636.2425	4.91381249999998	-0.0763124999999718
36	641.08	641.1268125	637.3175	3.80931249999999	-0.046812500000101
37	641.08	641.0973125	638.3925	2.70481249999999	-0.0173125000001164
38	641.08	641.0678125	639.4675	1.6003125	0.0121874999999818
39	641.08	641.0383125	640.5425	0.495812499999996	0.04168750000008
40	641.08	641.676979166667	642.210416666667	-0.533437499999983	-0.596979166666642
41	641.08	642.9838125	644.47125	-1.48743749999998	-1.90381250000007
42	641.08	644.290645833333	646.732083333333	-2.44143749999995	-3.21064583333327
43	641.08	645.070729166667	648.992916666667	-3.92218750000001	-3.9907291666666
44	641.08	646.2270625	651.25375	-5.0266875	-5.14706249999995
45	641.08	647.383395833333	653.514583333333	-6.13118750000003	-6.3033958333333
46	668.21	661.793729166667	655.775416666667	6.01831249999999	6.41627083333344
47	668.21	662.9500625	658.03625	4.91381249999998	5.25993750000009
48	668.21	664.106395833333	660.297083333333	3.80931249999999	4.10360416666674
49	668.21	665.262729166667	662.557916666667	2.70481249999999	2.94727083333339
50	668.21	666.4190625	664.81875	1.6003125	1.79093750000004
51	668.21	667.575395833333	667.079583333333	0.495812499999996	0.634604166666691
52	668.21	667.5540625	668.0875	-0.533437499999983	0.65593750000005
53	668.21	666.3550625	667.8425	-1.48743749999998	1.85493750000001
54	668.21	665.1560625	667.5975	-2.44143749999995	3.05393750000007
55	668.21	663.4303125	667.3525	-3.92218750000001	4.77968750000014
56	668.21	662.0808125	667.1075	-5.0266875	6.12918750000006
57	668.21	660.7313125	666.8625	-6.13118750000003	7.47868750000009
58	665.27	672.6358125	666.6175	6.01831249999999	-7.36581249999995
59	665.27	671.2863125	666.3725	4.91381249999998	-6.01631249999991
60	665.27	669.9368125	666.1275	3.80931249999999	-4.66681249999999
61	665.27	668.5873125	665.8825	2.70481249999999	-3.31731249999996
62	665.27	667.2378125	665.6375	1.6003125	-1.96781249999992
63	665.27	665.8883125	665.3925	0.495812499999996	-0.618312499999888
64	665.27	665.1128125	665.64625	-0.533437499999983	0.157187500000077
65	665.27	664.9113125	666.39875	-1.48743749999998	0.358687500000087
66	665.27	664.7098125	667.15125	-2.44143749999995	0.560187500000097
67	665.27	NA	NA	-3.92218750000001	NA
68	665.27	NA	NA	-5.0266875	NA
69	665.27	NA	NA	-6.13118750000003	NA
70	674.3	NA	NA	6.01831249999999	NA
71	674.3	NA	NA	4.91381249999998	NA
72	674.3	NA	NA	3.80931249999999	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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