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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 07 Dec 2010 09:31:16 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/07/t1291714162xmignqy7ydt7ome.htm/, Retrieved Fri, 03 May 2024 20:43:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106065, Retrieved Fri, 03 May 2024 20:43:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R  D      [(Partial) Autocorrelation Function] [Workshop 9; Coffe...] [2010-12-07 09:31:16] [50e0b5177c9c80b42996aa89930b928a] [Current]
-   PD        [(Partial) Autocorrelation Function] [Workshop 9; Coffe...] [2010-12-07 09:46:30] [8ffb4cfa64b4677df0d2c448735a40bb]
- R  D        [(Partial) Autocorrelation Function] [Paper; ACF Coffee...] [2010-12-21 14:55:55] [8ffb4cfa64b4677df0d2c448735a40bb]
-   P           [(Partial) Autocorrelation Function] [Paper; ACF Coffee...] [2010-12-21 15:00:10] [8ffb4cfa64b4677df0d2c448735a40bb]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
168,67
164,83
184,38
180,81
190,54
181,41
155,67
135,99
125,88
126,09
114,86
127,98
127,98
125,11
125,93
128,2
125,93
111,94
120,01
124,09
126,02
136,41
143,79
141,67
143,9
155
144,83
141,4
137
141,02
131,11
132,83
136,73
141,18
137,86
133,79
128,53
125,87
124,27
123,96
128,15
126,4
127,86
129,31
132,56
141,28
145,55
146,54
143,14
145,72
148,21
150,4
149,94
146,66
143,37
145,29
140,24
136,12
140,25
140,64
145,58
143,73
141,27
140,66
141,94
141,16
134,31
132,93
133,07
140,48
154,85
196,77
235,3
226,52
237,62
224,07
208,74
174,54
170,63
172,23
198,36
175,91
154,63
134,31
121,75
119,6
102,04
106,3
116,38
103,72
98,56
100,9
110
118,26
124,77
125,22
126,38
137,14
134,74
134,3
136,39
141,83
139,24
128,89
134,83
130,43
132,09
144,95
149,5
137,57
139,38
143,06
138,65
123,21
85,91
77,4
77,84
67,76
70,72
72,55
75,83
84,01
93,96
93,73
92,02
88,26
86,48
94,42
94,92
91,41
84,84
89,89
86,32
89,57
93,72
92,27
87,59
85,5
82,81
81,62
87,45
79,86
78,52
75,1
72,99
67,88
70,14
65,43
60,26
58,38
57,68
52,42
52,73
61,4
67,13
77,46
68,66
67,46
62,77
56,88
61,48
61,99
71,56
76,56
79,82
75,05
77,07
80
77,21
82,16
85,57
89,23
121,98
142,56
217,67
198,07
220,1
198,68
181,64
167,47
172,33
168,71
178,22
172,81
168,83
152,25
143,83
151,41
131,87
125,38
123,23
103,99
109,38
123,79
119,05
122,01
128,56
127,91
120,47
122,49
114,05
120,62
119,61
115,01
131,83
167,2
193,82
204,43
264,5
212,55
186,52
185,17
184,38
161,45
154,15
174,25
175,04
175,87
154,82
147,08
134,35
121,56
113,86
119,89
108,07
107,07
115,14
116,03
111,48
103,24
103,23
99,69
108,91
104,21
90,85
87,64
81,06
92,2
114,02
123,56
109,17
101,65
97,95
92,56
91,76
84,1
84,67
74,52
73,83
75,37
70,47
64,5
64,98
66,94
65,93
65,51
68,94
63,67
58,47
59,68
57,71
56,53
58,96
55,6
57,34
60,51
66,38
65,78
58,43
55,16
53,09
52,02
57,58
64,05
70,18
63,86
65,22
67,6
61,66
65,32
66,18
61,34
62,29
63,6
65,51
62,58
62,36
64,88
73,73
77,51
77,47
74,34
75,81
82,16
73,96
73,17
80,99
79,81
89,51
102,57
107,11
122,23
134,69
128,79
126,16
119,98
108,45
108,43
98,17
106,09
108,81
103,03
124,36
118,52
112,2
114,71
107,96
101,21
102,77
112,13
109,36
110,91
123,57
129,95
124,46
122,34
116,61
114,59
112,52
118,67
116,8
123,63
128,04
134,57
130,33
136,47
139,05
158,21
148,07
137,74
139,74
144,08
145,35
145,77
140,56
121,41
120,44
116,97
128,03
128,51
127,76
134,58
147,64
144,46
137,6
146,87
145,67
151,95
150,23
155,86
154,4
156,36
162,13
171,06
174,01
193,52
205,26
212,8
222,1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106065&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]1 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=106065&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106065&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.95140518.27590
20.89169117.12880
30.82096515.77020
40.75249714.4550
50.69033813.2610
60.64312512.3540
70.60533711.62810
80.56974710.94450
90.5357710.29180
100.4975779.55810
110.4610338.85620
120.4204518.07660
130.3839257.3750
140.3507096.73690
150.3266676.27510
160.3078125.91290
170.2957555.68130
180.2987325.73850
190.3064445.88660
200.3123145.99930
210.3178436.10560
220.3195786.13890
230.3177776.10430
240.316496.07960
250.3109785.97370

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.951405 & 18.2759 & 0 \tabularnewline
2 & 0.891691 & 17.1288 & 0 \tabularnewline
3 & 0.820965 & 15.7702 & 0 \tabularnewline
4 & 0.752497 & 14.455 & 0 \tabularnewline
5 & 0.690338 & 13.261 & 0 \tabularnewline
6 & 0.643125 & 12.354 & 0 \tabularnewline
7 & 0.605337 & 11.6281 & 0 \tabularnewline
8 & 0.569747 & 10.9445 & 0 \tabularnewline
9 & 0.53577 & 10.2918 & 0 \tabularnewline
10 & 0.497577 & 9.5581 & 0 \tabularnewline
11 & 0.461033 & 8.8562 & 0 \tabularnewline
12 & 0.420451 & 8.0766 & 0 \tabularnewline
13 & 0.383925 & 7.375 & 0 \tabularnewline
14 & 0.350709 & 6.7369 & 0 \tabularnewline
15 & 0.326667 & 6.2751 & 0 \tabularnewline
16 & 0.307812 & 5.9129 & 0 \tabularnewline
17 & 0.295755 & 5.6813 & 0 \tabularnewline
18 & 0.298732 & 5.7385 & 0 \tabularnewline
19 & 0.306444 & 5.8866 & 0 \tabularnewline
20 & 0.312314 & 5.9993 & 0 \tabularnewline
21 & 0.317843 & 6.1056 & 0 \tabularnewline
22 & 0.319578 & 6.1389 & 0 \tabularnewline
23 & 0.317777 & 6.1043 & 0 \tabularnewline
24 & 0.31649 & 6.0796 & 0 \tabularnewline
25 & 0.310978 & 5.9737 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106065&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.951405[/C][C]18.2759[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.891691[/C][C]17.1288[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.820965[/C][C]15.7702[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.752497[/C][C]14.455[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.690338[/C][C]13.261[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.643125[/C][C]12.354[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.605337[/C][C]11.6281[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.569747[/C][C]10.9445[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.53577[/C][C]10.2918[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.497577[/C][C]9.5581[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.461033[/C][C]8.8562[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.420451[/C][C]8.0766[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.383925[/C][C]7.375[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.350709[/C][C]6.7369[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.326667[/C][C]6.2751[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.307812[/C][C]5.9129[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.295755[/C][C]5.6813[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.298732[/C][C]5.7385[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.306444[/C][C]5.8866[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.312314[/C][C]5.9993[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.317843[/C][C]6.1056[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.319578[/C][C]6.1389[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.317777[/C][C]6.1043[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.31649[/C][C]6.0796[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.310978[/C][C]5.9737[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106065&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106065&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.95140518.27590
20.89169117.12880
30.82096515.77020
40.75249714.4550
50.69033813.2610
60.64312512.3540
70.60533711.62810
80.56974710.94450
90.5357710.29180
100.4975779.55810
110.4610338.85620
120.4204518.07660
130.3839257.3750
140.3507096.73690
150.3266676.27510
160.3078125.91290
170.2957555.68130
180.2987325.73850
190.3064445.88660
200.3123145.99930
210.3178436.10560
220.3195786.13890
230.3177776.10430
240.316496.07960
250.3109785.97370






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95140518.27590
2-0.14215-2.73060.003312
3-0.137186-2.63530.004381
40.0082760.1590.436891
50.0345750.66420.253499
60.1055882.02830.021625
70.0308840.59330.276682
8-0.047135-0.90540.182912
9-0.015944-0.30630.379784
10-0.054819-1.0530.146506
110.0241460.46380.321523
12-0.046511-0.89340.186101
130.0200210.38460.350383
140.0088060.16920.432885
150.0530451.0190.154445
160.0145780.280.389803
170.0301830.57980.281205
180.1436872.76010.003033
190.0312090.59950.274603
20-0.03849-0.73940.230074
210.0234310.45010.326453
22-0.010821-0.20790.417726
230.0163760.31460.376629
240.0358360.68840.245822
25-0.049191-0.94490.172654

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.951405 & 18.2759 & 0 \tabularnewline
2 & -0.14215 & -2.7306 & 0.003312 \tabularnewline
3 & -0.137186 & -2.6353 & 0.004381 \tabularnewline
4 & 0.008276 & 0.159 & 0.436891 \tabularnewline
5 & 0.034575 & 0.6642 & 0.253499 \tabularnewline
6 & 0.105588 & 2.0283 & 0.021625 \tabularnewline
7 & 0.030884 & 0.5933 & 0.276682 \tabularnewline
8 & -0.047135 & -0.9054 & 0.182912 \tabularnewline
9 & -0.015944 & -0.3063 & 0.379784 \tabularnewline
10 & -0.054819 & -1.053 & 0.146506 \tabularnewline
11 & 0.024146 & 0.4638 & 0.321523 \tabularnewline
12 & -0.046511 & -0.8934 & 0.186101 \tabularnewline
13 & 0.020021 & 0.3846 & 0.350383 \tabularnewline
14 & 0.008806 & 0.1692 & 0.432885 \tabularnewline
15 & 0.053045 & 1.019 & 0.154445 \tabularnewline
16 & 0.014578 & 0.28 & 0.389803 \tabularnewline
17 & 0.030183 & 0.5798 & 0.281205 \tabularnewline
18 & 0.143687 & 2.7601 & 0.003033 \tabularnewline
19 & 0.031209 & 0.5995 & 0.274603 \tabularnewline
20 & -0.03849 & -0.7394 & 0.230074 \tabularnewline
21 & 0.023431 & 0.4501 & 0.326453 \tabularnewline
22 & -0.010821 & -0.2079 & 0.417726 \tabularnewline
23 & 0.016376 & 0.3146 & 0.376629 \tabularnewline
24 & 0.035836 & 0.6884 & 0.245822 \tabularnewline
25 & -0.049191 & -0.9449 & 0.172654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106065&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.951405[/C][C]18.2759[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.14215[/C][C]-2.7306[/C][C]0.003312[/C][/ROW]
[ROW][C]3[/C][C]-0.137186[/C][C]-2.6353[/C][C]0.004381[/C][/ROW]
[ROW][C]4[/C][C]0.008276[/C][C]0.159[/C][C]0.436891[/C][/ROW]
[ROW][C]5[/C][C]0.034575[/C][C]0.6642[/C][C]0.253499[/C][/ROW]
[ROW][C]6[/C][C]0.105588[/C][C]2.0283[/C][C]0.021625[/C][/ROW]
[ROW][C]7[/C][C]0.030884[/C][C]0.5933[/C][C]0.276682[/C][/ROW]
[ROW][C]8[/C][C]-0.047135[/C][C]-0.9054[/C][C]0.182912[/C][/ROW]
[ROW][C]9[/C][C]-0.015944[/C][C]-0.3063[/C][C]0.379784[/C][/ROW]
[ROW][C]10[/C][C]-0.054819[/C][C]-1.053[/C][C]0.146506[/C][/ROW]
[ROW][C]11[/C][C]0.024146[/C][C]0.4638[/C][C]0.321523[/C][/ROW]
[ROW][C]12[/C][C]-0.046511[/C][C]-0.8934[/C][C]0.186101[/C][/ROW]
[ROW][C]13[/C][C]0.020021[/C][C]0.3846[/C][C]0.350383[/C][/ROW]
[ROW][C]14[/C][C]0.008806[/C][C]0.1692[/C][C]0.432885[/C][/ROW]
[ROW][C]15[/C][C]0.053045[/C][C]1.019[/C][C]0.154445[/C][/ROW]
[ROW][C]16[/C][C]0.014578[/C][C]0.28[/C][C]0.389803[/C][/ROW]
[ROW][C]17[/C][C]0.030183[/C][C]0.5798[/C][C]0.281205[/C][/ROW]
[ROW][C]18[/C][C]0.143687[/C][C]2.7601[/C][C]0.003033[/C][/ROW]
[ROW][C]19[/C][C]0.031209[/C][C]0.5995[/C][C]0.274603[/C][/ROW]
[ROW][C]20[/C][C]-0.03849[/C][C]-0.7394[/C][C]0.230074[/C][/ROW]
[ROW][C]21[/C][C]0.023431[/C][C]0.4501[/C][C]0.326453[/C][/ROW]
[ROW][C]22[/C][C]-0.010821[/C][C]-0.2079[/C][C]0.417726[/C][/ROW]
[ROW][C]23[/C][C]0.016376[/C][C]0.3146[/C][C]0.376629[/C][/ROW]
[ROW][C]24[/C][C]0.035836[/C][C]0.6884[/C][C]0.245822[/C][/ROW]
[ROW][C]25[/C][C]-0.049191[/C][C]-0.9449[/C][C]0.172654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106065&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106065&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95140518.27590
2-0.14215-2.73060.003312
3-0.137186-2.63530.004381
40.0082760.1590.436891
50.0345750.66420.253499
60.1055882.02830.021625
70.0308840.59330.276682
8-0.047135-0.90540.182912
9-0.015944-0.30630.379784
10-0.054819-1.0530.146506
110.0241460.46380.321523
12-0.046511-0.89340.186101
130.0200210.38460.350383
140.0088060.16920.432885
150.0530451.0190.154445
160.0145780.280.389803
170.0301830.57980.281205
180.1436872.76010.003033
190.0312090.59950.274603
20-0.03849-0.73940.230074
210.0234310.45010.326453
22-0.010821-0.20790.417726
230.0163760.31460.376629
240.0358360.68840.245822
25-0.049191-0.94490.172654


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')