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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 07 May 2012 07:13:11 -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/2012/May/07/t1336389248swvi1gvgzil2mk8.htm/, Retrieved Fri, 03 May 2024 06:58:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166296, Retrieved Fri, 03 May 2024 06:58:17 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

127

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

-     [Standard Deviation Plot] [OPG8 OEF3(2)] [2012-04-29 13:29:26] [aedd9af56bfe2946a9f9da3d899aa64c]
- RMPD    [Classical Decomposition] [] [2012-05-07 11:13:11] [2d897010b3abf24abba169db0d9c5a05] [Current]
- RMPD      [Exponential Smoothing] [OPG10OEF1 single] [2012-05-27 12:08:06] [2f0f353a58a70fd7baf0f5141860d820] 
- RMPD      [Exponential Smoothing] [OPG10OEF1triple] [2012-05-27 12:09:37] [2f0f353a58a70fd7baf0f5141860d820] 
- RMP       [Exponential Smoothing] [OPG10OEF2 double] [2012-05-27 12:15:49] [2f0f353a58a70fd7baf0f5141860d820] 

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	12 seconds
R Server	'AstonUniversity' @ aston.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 & 12 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166296&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166296&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166296&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	12 seconds
R Server	'AstonUniversity' @ aston.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	67.22	NA	NA	0.0159548611111144	NA
2	67.31	NA	NA	0.0284548611111137	NA
3	67.14	NA	NA	-0.0759201388888944	NA
4	67.22	NA	NA	-0.0399826388888952	NA
5	67.17	NA	NA	0.0255381944444425	NA
6	67.27	NA	NA	-0.056336805555554	NA
7	67.27	67.2846006944444	67.2616666666666	0.0229340277777782	-0.0146006944444252
8	67.27	67.2142881944444	67.2558333333333	-0.0415451388888866	0.0557118055555605
9	67.48	67.2456423611111	67.2583333333333	-0.0126909722222249	0.234357638888895
10	67.38	67.3552256944444	67.2820833333333	0.0731423611111085	0.0247743055555532
11	67.22	67.3707465277778	67.3266666666667	0.0440798611111137	-0.150746527777784
12	67.2	67.3909548611111	67.3745833333333	0.0163715277777842	-0.190954861111109
13	67.2	67.4297048611111	67.41375	0.0159548611111144	-0.229704861111102
14	67.19	67.4759548611111	67.4475	0.0284548611111137	-0.285954861111108
15	67.32	67.4011631944444	67.4770833333333	-0.0759201388888944	-0.0811631944444429
16	67.61	67.4737673611111	67.51375	-0.0399826388888952	0.136232638888885
17	67.85	67.5917881944444	67.56625	0.0255381944444425	0.258211805555561
18	67.74	67.5719965277778	67.6283333333333	-0.056336805555554	0.168003472222225
19	67.74	67.7129340277778	67.69	0.0229340277777782	0.0270659722222177
20	67.61	67.7159548611111	67.7575	-0.0415451388888866	-0.105954861111087
21	67.85	67.8035590277778	67.81625	-0.0126909722222249	0.0464409722222285
22	67.89	67.9210590277778	67.8479166666667	0.0731423611111085	-0.031059027777772
23	67.97	67.9032465277778	67.8591666666667	0.0440798611111137	0.0667534722222172
24	67.94	67.8822048611111	67.8658333333333	0.0163715277777842	0.057795138888892
25	67.94	67.8917881944444	67.8758333333333	0.0159548611111144	0.0482118055555532
26	68.07	67.9209548611111	67.8925	0.0284548611111137	0.149045138888894
27	67.85	67.8219965277778	67.8979166666667	-0.0759201388888944	0.0280034722222098
28	67.84	67.8583506944444	67.8983333333333	-0.0399826388888952	-0.018350694444436
29	67.89	67.9392881944444	67.91375	0.0255381944444425	-0.0492881944444292
30	67.86	67.8765798611111	67.9329166666667	-0.056336805555554	-0.0165798611111114
31	67.86	67.9766840277778	67.95375	0.0229340277777782	-0.116684027777779
32	67.89	67.9309548611111	67.9725	-0.0415451388888866	-0.0409548611111035
33	67.7	67.9835590277778	67.99625	-0.0126909722222249	-0.28355902777777
34	68.05	68.0973090277778	68.0241666666667	0.0731423611111085	-0.0473090277777715
35	68.18	68.1003298611111	68.05625	0.0440798611111137	0.0796701388889005
36	68.19	68.1122048611111	68.0958333333333	0.0163715277777842	0.0777951388889022
37	68.19	68.1517881944444	68.1358333333333	0.0159548611111144	0.0382118055555623
38	68.27	68.1988715277778	68.1704166666667	0.0284548611111137	0.0711284722222132
39	68.22	68.1274131944444	68.2033333333333	-0.0759201388888944	0.0925868055555554
40	68.14	68.1891840277778	68.2291666666667	-0.0399826388888952	-0.0491840277777555
41	68.36	68.2584548611111	68.2329166666667	0.0255381944444425	0.101545138888895
42	68.34	68.1661631944444	68.2225	-0.056336805555554	0.173836805555567
43	68.34	68.2321006944445	68.2091666666667	0.0229340277777782	0.107899305555549
44	68.24	68.1451215277778	68.1866666666667	-0.0415451388888866	0.09487847222222
45	68.14	68.1335590277778	68.14625	-0.0126909722222249	0.0064409722222365
46	68.23	68.1727256944445	68.0995833333333	0.0731423611111085	0.057274305555552
47	68.09	68.0819965277778	68.0379166666667	0.0440798611111137	0.00800347222222797
48	68.03	67.9709548611111	67.9545833333333	0.0163715277777842	0.0590451388889051
49	68.03	67.8830381944444	67.8670833333333	0.0159548611111144	0.146961805555563
50	67.89	67.8205381944444	67.7920833333333	0.0284548611111137	0.0694618055555623
51	67.63	67.6657465277778	67.7416666666667	-0.0759201388888944	-0.0357465277777749
52	67.61	67.6750173611111	67.715	-0.0399826388888952	-0.0650173611111029
53	67.41	67.7167881944444	67.69125	0.0255381944444425	-0.306788194444437
54	67.29	67.6115798611111	67.6679166666667	-0.056336805555554	-0.32157986111109
55	67.29	NA	NA	0.0229340277777782	NA
56	67.49	NA	NA	-0.0415451388888866	NA
57	67.68	NA	NA	-0.0126909722222249	NA
58	68.05	NA	NA	0.0731423611111085	NA
59	67.7	NA	NA	0.0440798611111137	NA
60	67.86	NA	NA	0.0163715277777842	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 67.22 & NA & NA & 0.0159548611111144 & NA \tabularnewline
2 & 67.31 & NA & NA & 0.0284548611111137 & NA \tabularnewline
3 & 67.14 & NA & NA & -0.0759201388888944 & NA \tabularnewline
4 & 67.22 & NA & NA & -0.0399826388888952 & NA \tabularnewline
5 & 67.17 & NA & NA & 0.0255381944444425 & NA \tabularnewline
6 & 67.27 & NA & NA & -0.056336805555554 & NA \tabularnewline
7 & 67.27 & 67.2846006944444 & 67.2616666666666 & 0.0229340277777782 & -0.0146006944444252 \tabularnewline
8 & 67.27 & 67.2142881944444 & 67.2558333333333 & -0.0415451388888866 & 0.0557118055555605 \tabularnewline
9 & 67.48 & 67.2456423611111 & 67.2583333333333 & -0.0126909722222249 & 0.234357638888895 \tabularnewline
10 & 67.38 & 67.3552256944444 & 67.2820833333333 & 0.0731423611111085 & 0.0247743055555532 \tabularnewline
11 & 67.22 & 67.3707465277778 & 67.3266666666667 & 0.0440798611111137 & -0.150746527777784 \tabularnewline
12 & 67.2 & 67.3909548611111 & 67.3745833333333 & 0.0163715277777842 & -0.190954861111109 \tabularnewline
13 & 67.2 & 67.4297048611111 & 67.41375 & 0.0159548611111144 & -0.229704861111102 \tabularnewline
14 & 67.19 & 67.4759548611111 & 67.4475 & 0.0284548611111137 & -0.285954861111108 \tabularnewline
15 & 67.32 & 67.4011631944444 & 67.4770833333333 & -0.0759201388888944 & -0.0811631944444429 \tabularnewline
16 & 67.61 & 67.4737673611111 & 67.51375 & -0.0399826388888952 & 0.136232638888885 \tabularnewline
17 & 67.85 & 67.5917881944444 & 67.56625 & 0.0255381944444425 & 0.258211805555561 \tabularnewline
18 & 67.74 & 67.5719965277778 & 67.6283333333333 & -0.056336805555554 & 0.168003472222225 \tabularnewline
19 & 67.74 & 67.7129340277778 & 67.69 & 0.0229340277777782 & 0.0270659722222177 \tabularnewline
20 & 67.61 & 67.7159548611111 & 67.7575 & -0.0415451388888866 & -0.105954861111087 \tabularnewline
21 & 67.85 & 67.8035590277778 & 67.81625 & -0.0126909722222249 & 0.0464409722222285 \tabularnewline
22 & 67.89 & 67.9210590277778 & 67.8479166666667 & 0.0731423611111085 & -0.031059027777772 \tabularnewline
23 & 67.97 & 67.9032465277778 & 67.8591666666667 & 0.0440798611111137 & 0.0667534722222172 \tabularnewline
24 & 67.94 & 67.8822048611111 & 67.8658333333333 & 0.0163715277777842 & 0.057795138888892 \tabularnewline
25 & 67.94 & 67.8917881944444 & 67.8758333333333 & 0.0159548611111144 & 0.0482118055555532 \tabularnewline
26 & 68.07 & 67.9209548611111 & 67.8925 & 0.0284548611111137 & 0.149045138888894 \tabularnewline
27 & 67.85 & 67.8219965277778 & 67.8979166666667 & -0.0759201388888944 & 0.0280034722222098 \tabularnewline
28 & 67.84 & 67.8583506944444 & 67.8983333333333 & -0.0399826388888952 & -0.018350694444436 \tabularnewline
29 & 67.89 & 67.9392881944444 & 67.91375 & 0.0255381944444425 & -0.0492881944444292 \tabularnewline
30 & 67.86 & 67.8765798611111 & 67.9329166666667 & -0.056336805555554 & -0.0165798611111114 \tabularnewline
31 & 67.86 & 67.9766840277778 & 67.95375 & 0.0229340277777782 & -0.116684027777779 \tabularnewline
32 & 67.89 & 67.9309548611111 & 67.9725 & -0.0415451388888866 & -0.0409548611111035 \tabularnewline
33 & 67.7 & 67.9835590277778 & 67.99625 & -0.0126909722222249 & -0.28355902777777 \tabularnewline
34 & 68.05 & 68.0973090277778 & 68.0241666666667 & 0.0731423611111085 & -0.0473090277777715 \tabularnewline
35 & 68.18 & 68.1003298611111 & 68.05625 & 0.0440798611111137 & 0.0796701388889005 \tabularnewline
36 & 68.19 & 68.1122048611111 & 68.0958333333333 & 0.0163715277777842 & 0.0777951388889022 \tabularnewline
37 & 68.19 & 68.1517881944444 & 68.1358333333333 & 0.0159548611111144 & 0.0382118055555623 \tabularnewline
38 & 68.27 & 68.1988715277778 & 68.1704166666667 & 0.0284548611111137 & 0.0711284722222132 \tabularnewline
39 & 68.22 & 68.1274131944444 & 68.2033333333333 & -0.0759201388888944 & 0.0925868055555554 \tabularnewline
40 & 68.14 & 68.1891840277778 & 68.2291666666667 & -0.0399826388888952 & -0.0491840277777555 \tabularnewline
41 & 68.36 & 68.2584548611111 & 68.2329166666667 & 0.0255381944444425 & 0.101545138888895 \tabularnewline
42 & 68.34 & 68.1661631944444 & 68.2225 & -0.056336805555554 & 0.173836805555567 \tabularnewline
43 & 68.34 & 68.2321006944445 & 68.2091666666667 & 0.0229340277777782 & 0.107899305555549 \tabularnewline
44 & 68.24 & 68.1451215277778 & 68.1866666666667 & -0.0415451388888866 & 0.09487847222222 \tabularnewline
45 & 68.14 & 68.1335590277778 & 68.14625 & -0.0126909722222249 & 0.0064409722222365 \tabularnewline
46 & 68.23 & 68.1727256944445 & 68.0995833333333 & 0.0731423611111085 & 0.057274305555552 \tabularnewline
47 & 68.09 & 68.0819965277778 & 68.0379166666667 & 0.0440798611111137 & 0.00800347222222797 \tabularnewline
48 & 68.03 & 67.9709548611111 & 67.9545833333333 & 0.0163715277777842 & 0.0590451388889051 \tabularnewline
49 & 68.03 & 67.8830381944444 & 67.8670833333333 & 0.0159548611111144 & 0.146961805555563 \tabularnewline
50 & 67.89 & 67.8205381944444 & 67.7920833333333 & 0.0284548611111137 & 0.0694618055555623 \tabularnewline
51 & 67.63 & 67.6657465277778 & 67.7416666666667 & -0.0759201388888944 & -0.0357465277777749 \tabularnewline
52 & 67.61 & 67.6750173611111 & 67.715 & -0.0399826388888952 & -0.0650173611111029 \tabularnewline
53 & 67.41 & 67.7167881944444 & 67.69125 & 0.0255381944444425 & -0.306788194444437 \tabularnewline
54 & 67.29 & 67.6115798611111 & 67.6679166666667 & -0.056336805555554 & -0.32157986111109 \tabularnewline
55 & 67.29 & NA & NA & 0.0229340277777782 & NA \tabularnewline
56 & 67.49 & NA & NA & -0.0415451388888866 & NA \tabularnewline
57 & 67.68 & NA & NA & -0.0126909722222249 & NA \tabularnewline
58 & 68.05 & NA & NA & 0.0731423611111085 & NA \tabularnewline
59 & 67.7 & NA & NA & 0.0440798611111137 & NA \tabularnewline
60 & 67.86 & NA & NA & 0.0163715277777842 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166296&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]67.22[/C][C]NA[/C][C]NA[/C][C]0.0159548611111144[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]67.31[/C][C]NA[/C][C]NA[/C][C]0.0284548611111137[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]67.14[/C][C]NA[/C][C]NA[/C][C]-0.0759201388888944[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]67.22[/C][C]NA[/C][C]NA[/C][C]-0.0399826388888952[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]67.17[/C][C]NA[/C][C]NA[/C][C]0.0255381944444425[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]67.27[/C][C]NA[/C][C]NA[/C][C]-0.056336805555554[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]67.27[/C][C]67.2846006944444[/C][C]67.2616666666666[/C][C]0.0229340277777782[/C][C]-0.0146006944444252[/C][/ROW]
[ROW][C]8[/C][C]67.27[/C][C]67.2142881944444[/C][C]67.2558333333333[/C][C]-0.0415451388888866[/C][C]0.0557118055555605[/C][/ROW]
[ROW][C]9[/C][C]67.48[/C][C]67.2456423611111[/C][C]67.2583333333333[/C][C]-0.0126909722222249[/C][C]0.234357638888895[/C][/ROW]
[ROW][C]10[/C][C]67.38[/C][C]67.3552256944444[/C][C]67.2820833333333[/C][C]0.0731423611111085[/C][C]0.0247743055555532[/C][/ROW]
[ROW][C]11[/C][C]67.22[/C][C]67.3707465277778[/C][C]67.3266666666667[/C][C]0.0440798611111137[/C][C]-0.150746527777784[/C][/ROW]
[ROW][C]12[/C][C]67.2[/C][C]67.3909548611111[/C][C]67.3745833333333[/C][C]0.0163715277777842[/C][C]-0.190954861111109[/C][/ROW]
[ROW][C]13[/C][C]67.2[/C][C]67.4297048611111[/C][C]67.41375[/C][C]0.0159548611111144[/C][C]-0.229704861111102[/C][/ROW]
[ROW][C]14[/C][C]67.19[/C][C]67.4759548611111[/C][C]67.4475[/C][C]0.0284548611111137[/C][C]-0.285954861111108[/C][/ROW]
[ROW][C]15[/C][C]67.32[/C][C]67.4011631944444[/C][C]67.4770833333333[/C][C]-0.0759201388888944[/C][C]-0.0811631944444429[/C][/ROW]
[ROW][C]16[/C][C]67.61[/C][C]67.4737673611111[/C][C]67.51375[/C][C]-0.0399826388888952[/C][C]0.136232638888885[/C][/ROW]
[ROW][C]17[/C][C]67.85[/C][C]67.5917881944444[/C][C]67.56625[/C][C]0.0255381944444425[/C][C]0.258211805555561[/C][/ROW]
[ROW][C]18[/C][C]67.74[/C][C]67.5719965277778[/C][C]67.6283333333333[/C][C]-0.056336805555554[/C][C]0.168003472222225[/C][/ROW]
[ROW][C]19[/C][C]67.74[/C][C]67.7129340277778[/C][C]67.69[/C][C]0.0229340277777782[/C][C]0.0270659722222177[/C][/ROW]
[ROW][C]20[/C][C]67.61[/C][C]67.7159548611111[/C][C]67.7575[/C][C]-0.0415451388888866[/C][C]-0.105954861111087[/C][/ROW]
[ROW][C]21[/C][C]67.85[/C][C]67.8035590277778[/C][C]67.81625[/C][C]-0.0126909722222249[/C][C]0.0464409722222285[/C][/ROW]
[ROW][C]22[/C][C]67.89[/C][C]67.9210590277778[/C][C]67.8479166666667[/C][C]0.0731423611111085[/C][C]-0.031059027777772[/C][/ROW]
[ROW][C]23[/C][C]67.97[/C][C]67.9032465277778[/C][C]67.8591666666667[/C][C]0.0440798611111137[/C][C]0.0667534722222172[/C][/ROW]
[ROW][C]24[/C][C]67.94[/C][C]67.8822048611111[/C][C]67.8658333333333[/C][C]0.0163715277777842[/C][C]0.057795138888892[/C][/ROW]
[ROW][C]25[/C][C]67.94[/C][C]67.8917881944444[/C][C]67.8758333333333[/C][C]0.0159548611111144[/C][C]0.0482118055555532[/C][/ROW]
[ROW][C]26[/C][C]68.07[/C][C]67.9209548611111[/C][C]67.8925[/C][C]0.0284548611111137[/C][C]0.149045138888894[/C][/ROW]
[ROW][C]27[/C][C]67.85[/C][C]67.8219965277778[/C][C]67.8979166666667[/C][C]-0.0759201388888944[/C][C]0.0280034722222098[/C][/ROW]
[ROW][C]28[/C][C]67.84[/C][C]67.8583506944444[/C][C]67.8983333333333[/C][C]-0.0399826388888952[/C][C]-0.018350694444436[/C][/ROW]
[ROW][C]29[/C][C]67.89[/C][C]67.9392881944444[/C][C]67.91375[/C][C]0.0255381944444425[/C][C]-0.0492881944444292[/C][/ROW]
[ROW][C]30[/C][C]67.86[/C][C]67.8765798611111[/C][C]67.9329166666667[/C][C]-0.056336805555554[/C][C]-0.0165798611111114[/C][/ROW]
[ROW][C]31[/C][C]67.86[/C][C]67.9766840277778[/C][C]67.95375[/C][C]0.0229340277777782[/C][C]-0.116684027777779[/C][/ROW]
[ROW][C]32[/C][C]67.89[/C][C]67.9309548611111[/C][C]67.9725[/C][C]-0.0415451388888866[/C][C]-0.0409548611111035[/C][/ROW]
[ROW][C]33[/C][C]67.7[/C][C]67.9835590277778[/C][C]67.99625[/C][C]-0.0126909722222249[/C][C]-0.28355902777777[/C][/ROW]
[ROW][C]34[/C][C]68.05[/C][C]68.0973090277778[/C][C]68.0241666666667[/C][C]0.0731423611111085[/C][C]-0.0473090277777715[/C][/ROW]
[ROW][C]35[/C][C]68.18[/C][C]68.1003298611111[/C][C]68.05625[/C][C]0.0440798611111137[/C][C]0.0796701388889005[/C][/ROW]
[ROW][C]36[/C][C]68.19[/C][C]68.1122048611111[/C][C]68.0958333333333[/C][C]0.0163715277777842[/C][C]0.0777951388889022[/C][/ROW]
[ROW][C]37[/C][C]68.19[/C][C]68.1517881944444[/C][C]68.1358333333333[/C][C]0.0159548611111144[/C][C]0.0382118055555623[/C][/ROW]
[ROW][C]38[/C][C]68.27[/C][C]68.1988715277778[/C][C]68.1704166666667[/C][C]0.0284548611111137[/C][C]0.0711284722222132[/C][/ROW]
[ROW][C]39[/C][C]68.22[/C][C]68.1274131944444[/C][C]68.2033333333333[/C][C]-0.0759201388888944[/C][C]0.0925868055555554[/C][/ROW]
[ROW][C]40[/C][C]68.14[/C][C]68.1891840277778[/C][C]68.2291666666667[/C][C]-0.0399826388888952[/C][C]-0.0491840277777555[/C][/ROW]
[ROW][C]41[/C][C]68.36[/C][C]68.2584548611111[/C][C]68.2329166666667[/C][C]0.0255381944444425[/C][C]0.101545138888895[/C][/ROW]
[ROW][C]42[/C][C]68.34[/C][C]68.1661631944444[/C][C]68.2225[/C][C]-0.056336805555554[/C][C]0.173836805555567[/C][/ROW]
[ROW][C]43[/C][C]68.34[/C][C]68.2321006944445[/C][C]68.2091666666667[/C][C]0.0229340277777782[/C][C]0.107899305555549[/C][/ROW]
[ROW][C]44[/C][C]68.24[/C][C]68.1451215277778[/C][C]68.1866666666667[/C][C]-0.0415451388888866[/C][C]0.09487847222222[/C][/ROW]
[ROW][C]45[/C][C]68.14[/C][C]68.1335590277778[/C][C]68.14625[/C][C]-0.0126909722222249[/C][C]0.0064409722222365[/C][/ROW]
[ROW][C]46[/C][C]68.23[/C][C]68.1727256944445[/C][C]68.0995833333333[/C][C]0.0731423611111085[/C][C]0.057274305555552[/C][/ROW]
[ROW][C]47[/C][C]68.09[/C][C]68.0819965277778[/C][C]68.0379166666667[/C][C]0.0440798611111137[/C][C]0.00800347222222797[/C][/ROW]
[ROW][C]48[/C][C]68.03[/C][C]67.9709548611111[/C][C]67.9545833333333[/C][C]0.0163715277777842[/C][C]0.0590451388889051[/C][/ROW]
[ROW][C]49[/C][C]68.03[/C][C]67.8830381944444[/C][C]67.8670833333333[/C][C]0.0159548611111144[/C][C]0.146961805555563[/C][/ROW]
[ROW][C]50[/C][C]67.89[/C][C]67.8205381944444[/C][C]67.7920833333333[/C][C]0.0284548611111137[/C][C]0.0694618055555623[/C][/ROW]
[ROW][C]51[/C][C]67.63[/C][C]67.6657465277778[/C][C]67.7416666666667[/C][C]-0.0759201388888944[/C][C]-0.0357465277777749[/C][/ROW]
[ROW][C]52[/C][C]67.61[/C][C]67.6750173611111[/C][C]67.715[/C][C]-0.0399826388888952[/C][C]-0.0650173611111029[/C][/ROW]
[ROW][C]53[/C][C]67.41[/C][C]67.7167881944444[/C][C]67.69125[/C][C]0.0255381944444425[/C][C]-0.306788194444437[/C][/ROW]
[ROW][C]54[/C][C]67.29[/C][C]67.6115798611111[/C][C]67.6679166666667[/C][C]-0.056336805555554[/C][C]-0.32157986111109[/C][/ROW]
[ROW][C]55[/C][C]67.29[/C][C]NA[/C][C]NA[/C][C]0.0229340277777782[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]67.49[/C][C]NA[/C][C]NA[/C][C]-0.0415451388888866[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]67.68[/C][C]NA[/C][C]NA[/C][C]-0.0126909722222249[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]68.05[/C][C]NA[/C][C]NA[/C][C]0.0731423611111085[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]67.7[/C][C]NA[/C][C]NA[/C][C]0.0440798611111137[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]67.86[/C][C]NA[/C][C]NA[/C][C]0.0163715277777842[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166296&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166296&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	67.22	NA	NA	0.0159548611111144	NA
2	67.31	NA	NA	0.0284548611111137	NA
3	67.14	NA	NA	-0.0759201388888944	NA
4	67.22	NA	NA	-0.0399826388888952	NA
5	67.17	NA	NA	0.0255381944444425	NA
6	67.27	NA	NA	-0.056336805555554	NA
7	67.27	67.2846006944444	67.2616666666666	0.0229340277777782	-0.0146006944444252
8	67.27	67.2142881944444	67.2558333333333	-0.0415451388888866	0.0557118055555605
9	67.48	67.2456423611111	67.2583333333333	-0.0126909722222249	0.234357638888895
10	67.38	67.3552256944444	67.2820833333333	0.0731423611111085	0.0247743055555532
11	67.22	67.3707465277778	67.3266666666667	0.0440798611111137	-0.150746527777784
12	67.2	67.3909548611111	67.3745833333333	0.0163715277777842	-0.190954861111109
13	67.2	67.4297048611111	67.41375	0.0159548611111144	-0.229704861111102
14	67.19	67.4759548611111	67.4475	0.0284548611111137	-0.285954861111108
15	67.32	67.4011631944444	67.4770833333333	-0.0759201388888944	-0.0811631944444429
16	67.61	67.4737673611111	67.51375	-0.0399826388888952	0.136232638888885
17	67.85	67.5917881944444	67.56625	0.0255381944444425	0.258211805555561
18	67.74	67.5719965277778	67.6283333333333	-0.056336805555554	0.168003472222225
19	67.74	67.7129340277778	67.69	0.0229340277777782	0.0270659722222177
20	67.61	67.7159548611111	67.7575	-0.0415451388888866	-0.105954861111087
21	67.85	67.8035590277778	67.81625	-0.0126909722222249	0.0464409722222285
22	67.89	67.9210590277778	67.8479166666667	0.0731423611111085	-0.031059027777772
23	67.97	67.9032465277778	67.8591666666667	0.0440798611111137	0.0667534722222172
24	67.94	67.8822048611111	67.8658333333333	0.0163715277777842	0.057795138888892
25	67.94	67.8917881944444	67.8758333333333	0.0159548611111144	0.0482118055555532
26	68.07	67.9209548611111	67.8925	0.0284548611111137	0.149045138888894
27	67.85	67.8219965277778	67.8979166666667	-0.0759201388888944	0.0280034722222098
28	67.84	67.8583506944444	67.8983333333333	-0.0399826388888952	-0.018350694444436
29	67.89	67.9392881944444	67.91375	0.0255381944444425	-0.0492881944444292
30	67.86	67.8765798611111	67.9329166666667	-0.056336805555554	-0.0165798611111114
31	67.86	67.9766840277778	67.95375	0.0229340277777782	-0.116684027777779
32	67.89	67.9309548611111	67.9725	-0.0415451388888866	-0.0409548611111035
33	67.7	67.9835590277778	67.99625	-0.0126909722222249	-0.28355902777777
34	68.05	68.0973090277778	68.0241666666667	0.0731423611111085	-0.0473090277777715
35	68.18	68.1003298611111	68.05625	0.0440798611111137	0.0796701388889005
36	68.19	68.1122048611111	68.0958333333333	0.0163715277777842	0.0777951388889022
37	68.19	68.1517881944444	68.1358333333333	0.0159548611111144	0.0382118055555623
38	68.27	68.1988715277778	68.1704166666667	0.0284548611111137	0.0711284722222132
39	68.22	68.1274131944444	68.2033333333333	-0.0759201388888944	0.0925868055555554
40	68.14	68.1891840277778	68.2291666666667	-0.0399826388888952	-0.0491840277777555
41	68.36	68.2584548611111	68.2329166666667	0.0255381944444425	0.101545138888895
42	68.34	68.1661631944444	68.2225	-0.056336805555554	0.173836805555567
43	68.34	68.2321006944445	68.2091666666667	0.0229340277777782	0.107899305555549
44	68.24	68.1451215277778	68.1866666666667	-0.0415451388888866	0.09487847222222
45	68.14	68.1335590277778	68.14625	-0.0126909722222249	0.0064409722222365
46	68.23	68.1727256944445	68.0995833333333	0.0731423611111085	0.057274305555552
47	68.09	68.0819965277778	68.0379166666667	0.0440798611111137	0.00800347222222797
48	68.03	67.9709548611111	67.9545833333333	0.0163715277777842	0.0590451388889051
49	68.03	67.8830381944444	67.8670833333333	0.0159548611111144	0.146961805555563
50	67.89	67.8205381944444	67.7920833333333	0.0284548611111137	0.0694618055555623
51	67.63	67.6657465277778	67.7416666666667	-0.0759201388888944	-0.0357465277777749
52	67.61	67.6750173611111	67.715	-0.0399826388888952	-0.0650173611111029
53	67.41	67.7167881944444	67.69125	0.0255381944444425	-0.306788194444437
54	67.29	67.6115798611111	67.6679166666667	-0.056336805555554	-0.32157986111109
55	67.29	NA	NA	0.0229340277777782	NA
56	67.49	NA	NA	-0.0415451388888866	NA
57	67.68	NA	NA	-0.0126909722222249	NA
58	68.05	NA	NA	0.0731423611111085	NA
59	67.7	NA	NA	0.0440798611111137	NA
60	67.86	NA	NA	0.0163715277777842	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