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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, 08 Dec 2009 10:32:48 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/08/t1260293665ugx6624h6uz2xtf.htm/, Retrieved Sun, 28 Apr 2024 08:04:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64753, Retrieved Sun, 28 Apr 2024 08:04:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
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] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD    [(Partial) Autocorrelation Function] [] [2009-12-01 17:11:01] [ee35698a38947a6c6c039b1e3deafc05]
-   PD        [(Partial) Autocorrelation Function] [] [2009-12-08 17:32:48] [791a4a78a0a7ca497fb8791b982a539e] [Current]
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Dataseries X:
87.28
87.09
86.92
87.59
90.72
90.69
90.3
89.55
88.94
88.41
87.82
87.07
86.82
86.4
86.02
85.66
85.32
85
84.67
83.94
82.83
81.95
81.19
80.48
78.86
69.47
68.77
70.06
73.95
75.8
77.79
81.57
83.07
84.34
85.1
85.25
84.26
83.63
86.44
85.3
84.1
83.36
82.48
81.58
80.47
79.34
82.13
81.69
80.7
79.88
79.16
78.38
77.42
76.47
75.46
74.48
78.27
80.7
79.91
78.75
77.78
81.14
81.08
80.03
78.91
78.01
76.9
75.97
81.93
80.27
78.67
77.42
76.16
74.7
76.39
76.04
74.65
73.29
71.79
74.39
74.91
74.54
73.08
72.75
71.32
70.38
70.35
70.01
69.36
67.77
69.26
69.8
68.38
67.62
68.39
66.95
65.21
66.64
63.45
60.66
62.34
60.32
58.64
60.46
58.59
61.87
61.85
67.44
77.06
91.74
93.15
94.15
93.11
91.51
89.96
88.16
86.98
88.03
86.24
84.65
83.23
81.7
80.25
78.8
77.51
76.2
75.04
74
75.49
77.14
76.15
76.27
78.19
76.49
77.31
76.65
74.99
73.51
72.07
70.59
71.96
76.29
74.86
74.93
71.9
71.01
77.47
75.78
76.6
76.07
74.57
73.02
72.65
73.16
71.53
69.78
67.98
69.96
72.16
70.47
68.86
67.37
65.87
72.16
71.34
69.93
68.44
67.16
66.01
67.25
70.91
69.75
68.59
67.48
66.31
64.81
66.58
65.97
64.7
64.7
60.94
59.08
58.42
57.77
57.11
53.31
49.96
49.4
48.84
48.3
47.74
47.24
46.76
46.29
48.9
49.23
48.53
48.03
54.34
53.79
53.24
52.96
52.17
51.7
58.55
78.2
77.03
76.19
77.15
75.87
95.47
109.67
112.28
112.01
107.93
105.96
105.06
102.98
102.2
105.23
101.85
99.89
96.23
94.76
91.51
91.63
91.54
85.23
87.83
87.38
84.44
85.19
84.03
86.73
102.52
104.45
106.98
107.02
99.26
94.45
113.44
157.33
147.38
171.89
171.95
132.71
126.02
121.18
115.45
110.48
117.85
117.63
124.65
109.59
111.27
99.78
98.21
99.2
97.97
89.55
87.91
93.34
94.42
93.2
90.29
91.46
89.98
88.35
88.41
82.44
79.89
75.69
75.66
84.5
96.73
87.48
82.39
83.48
79.31
78.16
72.77
72.45
68.46
67.62
68.76
70.07
68.55
65.3
58.96
59.17
62.37
66.28
55.62
55.23
55.85
56.75
50.89
53.88
52.95
55.08
53.61
58.78
61.85
55.91
53.32
46.41
44.57
50
50
53.36
46.23
50.45
49.07
45.85
48.45
49.96
46.53
50.51
47.58
48.05
46.84
47.67
49.16
55.54
55.82
58.22
56.19
57.77
63.19
54.76
55.74
62.54
61.39
69.6
79.23
80
93.68
107.63
100.18
97.3
90.45
80.64
80.58
75.82
85.59
89.35
89.42
104.73
95.32
89.27
90.44
86.97
79.98
81.22
87.35
83.64
82.22
94.4
102.18




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64753&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64753&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1201812.27390.011781
2-0.01047-0.19810.421537
30.0725011.37180.085496
4-0.214934-4.06672.9e-05
5-0.160308-3.03320.001298
60.0435680.82430.205146
70.0771511.45980.072616
80.0190170.35980.359595
90.0370140.70030.242086
100.0471790.89270.186317
110.0364050.68880.245696
12-0.084928-1.60690.054478
13-0.004423-0.08370.466676
14-0.049981-0.94570.172476
15-0.085608-1.61980.05308
16-0.029284-0.55410.289936
17-0.013512-0.25570.399179
18-0.049324-0.93320.175661
19-0.124429-2.35430.009548
20-0.007686-0.14540.442225
210.0088890.16820.433267
220.0597371.13030.129559
230.0495450.93740.174584
240.0807771.52840.063653
25-0.011023-0.20860.417456
26-0.03657-0.69190.24471
27-0.032254-0.61030.271032
28-0.066908-1.2660.103177
290.0147250.27860.390353
300.1495432.82950.002462
310.082781.56630.059084
320.0031790.06010.476037
330.1479082.79850.002706
34-0.069774-1.32020.093808
35-0.051901-0.9820.163377
360.0764881.44720.074356
37-0.002989-0.05650.477469
380.026250.49670.309865
39-0.003792-0.07170.471422
40-0.041201-0.77960.218082
41-0.039275-0.74310.228949
42-0.029664-0.56130.287481
430.0185940.35180.362589
44-0.081008-1.53280.06311
45-0.037842-0.7160.237229
46-0.001805-0.03410.48639
470.0221640.41940.337604
48-0.055181-1.04410.148576
49-0.023893-0.45210.325747
500.020710.39190.347701
51-0.044276-0.83770.201367
52-0.037604-0.71150.238618
53-0.022911-0.43350.332455
54-0.038207-0.72290.235103
55-0.078554-1.48630.069038
56-0.025122-0.47530.317419
570.0044290.08380.466633
58-0.00338-0.0640.474521
59-0.010997-0.20810.417648
600.0432390.81810.206919

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.120181 & 2.2739 & 0.011781 \tabularnewline
2 & -0.01047 & -0.1981 & 0.421537 \tabularnewline
3 & 0.072501 & 1.3718 & 0.085496 \tabularnewline
4 & -0.214934 & -4.0667 & 2.9e-05 \tabularnewline
5 & -0.160308 & -3.0332 & 0.001298 \tabularnewline
6 & 0.043568 & 0.8243 & 0.205146 \tabularnewline
7 & 0.077151 & 1.4598 & 0.072616 \tabularnewline
8 & 0.019017 & 0.3598 & 0.359595 \tabularnewline
9 & 0.037014 & 0.7003 & 0.242086 \tabularnewline
10 & 0.047179 & 0.8927 & 0.186317 \tabularnewline
11 & 0.036405 & 0.6888 & 0.245696 \tabularnewline
12 & -0.084928 & -1.6069 & 0.054478 \tabularnewline
13 & -0.004423 & -0.0837 & 0.466676 \tabularnewline
14 & -0.049981 & -0.9457 & 0.172476 \tabularnewline
15 & -0.085608 & -1.6198 & 0.05308 \tabularnewline
16 & -0.029284 & -0.5541 & 0.289936 \tabularnewline
17 & -0.013512 & -0.2557 & 0.399179 \tabularnewline
18 & -0.049324 & -0.9332 & 0.175661 \tabularnewline
19 & -0.124429 & -2.3543 & 0.009548 \tabularnewline
20 & -0.007686 & -0.1454 & 0.442225 \tabularnewline
21 & 0.008889 & 0.1682 & 0.433267 \tabularnewline
22 & 0.059737 & 1.1303 & 0.129559 \tabularnewline
23 & 0.049545 & 0.9374 & 0.174584 \tabularnewline
24 & 0.080777 & 1.5284 & 0.063653 \tabularnewline
25 & -0.011023 & -0.2086 & 0.417456 \tabularnewline
26 & -0.03657 & -0.6919 & 0.24471 \tabularnewline
27 & -0.032254 & -0.6103 & 0.271032 \tabularnewline
28 & -0.066908 & -1.266 & 0.103177 \tabularnewline
29 & 0.014725 & 0.2786 & 0.390353 \tabularnewline
30 & 0.149543 & 2.8295 & 0.002462 \tabularnewline
31 & 0.08278 & 1.5663 & 0.059084 \tabularnewline
32 & 0.003179 & 0.0601 & 0.476037 \tabularnewline
33 & 0.147908 & 2.7985 & 0.002706 \tabularnewline
34 & -0.069774 & -1.3202 & 0.093808 \tabularnewline
35 & -0.051901 & -0.982 & 0.163377 \tabularnewline
36 & 0.076488 & 1.4472 & 0.074356 \tabularnewline
37 & -0.002989 & -0.0565 & 0.477469 \tabularnewline
38 & 0.02625 & 0.4967 & 0.309865 \tabularnewline
39 & -0.003792 & -0.0717 & 0.471422 \tabularnewline
40 & -0.041201 & -0.7796 & 0.218082 \tabularnewline
41 & -0.039275 & -0.7431 & 0.228949 \tabularnewline
42 & -0.029664 & -0.5613 & 0.287481 \tabularnewline
43 & 0.018594 & 0.3518 & 0.362589 \tabularnewline
44 & -0.081008 & -1.5328 & 0.06311 \tabularnewline
45 & -0.037842 & -0.716 & 0.237229 \tabularnewline
46 & -0.001805 & -0.0341 & 0.48639 \tabularnewline
47 & 0.022164 & 0.4194 & 0.337604 \tabularnewline
48 & -0.055181 & -1.0441 & 0.148576 \tabularnewline
49 & -0.023893 & -0.4521 & 0.325747 \tabularnewline
50 & 0.02071 & 0.3919 & 0.347701 \tabularnewline
51 & -0.044276 & -0.8377 & 0.201367 \tabularnewline
52 & -0.037604 & -0.7115 & 0.238618 \tabularnewline
53 & -0.022911 & -0.4335 & 0.332455 \tabularnewline
54 & -0.038207 & -0.7229 & 0.235103 \tabularnewline
55 & -0.078554 & -1.4863 & 0.069038 \tabularnewline
56 & -0.025122 & -0.4753 & 0.317419 \tabularnewline
57 & 0.004429 & 0.0838 & 0.466633 \tabularnewline
58 & -0.00338 & -0.064 & 0.474521 \tabularnewline
59 & -0.010997 & -0.2081 & 0.417648 \tabularnewline
60 & 0.043239 & 0.8181 & 0.206919 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64753&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]0.120181[/C][C]2.2739[/C][C]0.011781[/C][/ROW]
[ROW][C]2[/C][C]-0.01047[/C][C]-0.1981[/C][C]0.421537[/C][/ROW]
[ROW][C]3[/C][C]0.072501[/C][C]1.3718[/C][C]0.085496[/C][/ROW]
[ROW][C]4[/C][C]-0.214934[/C][C]-4.0667[/C][C]2.9e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.160308[/C][C]-3.0332[/C][C]0.001298[/C][/ROW]
[ROW][C]6[/C][C]0.043568[/C][C]0.8243[/C][C]0.205146[/C][/ROW]
[ROW][C]7[/C][C]0.077151[/C][C]1.4598[/C][C]0.072616[/C][/ROW]
[ROW][C]8[/C][C]0.019017[/C][C]0.3598[/C][C]0.359595[/C][/ROW]
[ROW][C]9[/C][C]0.037014[/C][C]0.7003[/C][C]0.242086[/C][/ROW]
[ROW][C]10[/C][C]0.047179[/C][C]0.8927[/C][C]0.186317[/C][/ROW]
[ROW][C]11[/C][C]0.036405[/C][C]0.6888[/C][C]0.245696[/C][/ROW]
[ROW][C]12[/C][C]-0.084928[/C][C]-1.6069[/C][C]0.054478[/C][/ROW]
[ROW][C]13[/C][C]-0.004423[/C][C]-0.0837[/C][C]0.466676[/C][/ROW]
[ROW][C]14[/C][C]-0.049981[/C][C]-0.9457[/C][C]0.172476[/C][/ROW]
[ROW][C]15[/C][C]-0.085608[/C][C]-1.6198[/C][C]0.05308[/C][/ROW]
[ROW][C]16[/C][C]-0.029284[/C][C]-0.5541[/C][C]0.289936[/C][/ROW]
[ROW][C]17[/C][C]-0.013512[/C][C]-0.2557[/C][C]0.399179[/C][/ROW]
[ROW][C]18[/C][C]-0.049324[/C][C]-0.9332[/C][C]0.175661[/C][/ROW]
[ROW][C]19[/C][C]-0.124429[/C][C]-2.3543[/C][C]0.009548[/C][/ROW]
[ROW][C]20[/C][C]-0.007686[/C][C]-0.1454[/C][C]0.442225[/C][/ROW]
[ROW][C]21[/C][C]0.008889[/C][C]0.1682[/C][C]0.433267[/C][/ROW]
[ROW][C]22[/C][C]0.059737[/C][C]1.1303[/C][C]0.129559[/C][/ROW]
[ROW][C]23[/C][C]0.049545[/C][C]0.9374[/C][C]0.174584[/C][/ROW]
[ROW][C]24[/C][C]0.080777[/C][C]1.5284[/C][C]0.063653[/C][/ROW]
[ROW][C]25[/C][C]-0.011023[/C][C]-0.2086[/C][C]0.417456[/C][/ROW]
[ROW][C]26[/C][C]-0.03657[/C][C]-0.6919[/C][C]0.24471[/C][/ROW]
[ROW][C]27[/C][C]-0.032254[/C][C]-0.6103[/C][C]0.271032[/C][/ROW]
[ROW][C]28[/C][C]-0.066908[/C][C]-1.266[/C][C]0.103177[/C][/ROW]
[ROW][C]29[/C][C]0.014725[/C][C]0.2786[/C][C]0.390353[/C][/ROW]
[ROW][C]30[/C][C]0.149543[/C][C]2.8295[/C][C]0.002462[/C][/ROW]
[ROW][C]31[/C][C]0.08278[/C][C]1.5663[/C][C]0.059084[/C][/ROW]
[ROW][C]32[/C][C]0.003179[/C][C]0.0601[/C][C]0.476037[/C][/ROW]
[ROW][C]33[/C][C]0.147908[/C][C]2.7985[/C][C]0.002706[/C][/ROW]
[ROW][C]34[/C][C]-0.069774[/C][C]-1.3202[/C][C]0.093808[/C][/ROW]
[ROW][C]35[/C][C]-0.051901[/C][C]-0.982[/C][C]0.163377[/C][/ROW]
[ROW][C]36[/C][C]0.076488[/C][C]1.4472[/C][C]0.074356[/C][/ROW]
[ROW][C]37[/C][C]-0.002989[/C][C]-0.0565[/C][C]0.477469[/C][/ROW]
[ROW][C]38[/C][C]0.02625[/C][C]0.4967[/C][C]0.309865[/C][/ROW]
[ROW][C]39[/C][C]-0.003792[/C][C]-0.0717[/C][C]0.471422[/C][/ROW]
[ROW][C]40[/C][C]-0.041201[/C][C]-0.7796[/C][C]0.218082[/C][/ROW]
[ROW][C]41[/C][C]-0.039275[/C][C]-0.7431[/C][C]0.228949[/C][/ROW]
[ROW][C]42[/C][C]-0.029664[/C][C]-0.5613[/C][C]0.287481[/C][/ROW]
[ROW][C]43[/C][C]0.018594[/C][C]0.3518[/C][C]0.362589[/C][/ROW]
[ROW][C]44[/C][C]-0.081008[/C][C]-1.5328[/C][C]0.06311[/C][/ROW]
[ROW][C]45[/C][C]-0.037842[/C][C]-0.716[/C][C]0.237229[/C][/ROW]
[ROW][C]46[/C][C]-0.001805[/C][C]-0.0341[/C][C]0.48639[/C][/ROW]
[ROW][C]47[/C][C]0.022164[/C][C]0.4194[/C][C]0.337604[/C][/ROW]
[ROW][C]48[/C][C]-0.055181[/C][C]-1.0441[/C][C]0.148576[/C][/ROW]
[ROW][C]49[/C][C]-0.023893[/C][C]-0.4521[/C][C]0.325747[/C][/ROW]
[ROW][C]50[/C][C]0.02071[/C][C]0.3919[/C][C]0.347701[/C][/ROW]
[ROW][C]51[/C][C]-0.044276[/C][C]-0.8377[/C][C]0.201367[/C][/ROW]
[ROW][C]52[/C][C]-0.037604[/C][C]-0.7115[/C][C]0.238618[/C][/ROW]
[ROW][C]53[/C][C]-0.022911[/C][C]-0.4335[/C][C]0.332455[/C][/ROW]
[ROW][C]54[/C][C]-0.038207[/C][C]-0.7229[/C][C]0.235103[/C][/ROW]
[ROW][C]55[/C][C]-0.078554[/C][C]-1.4863[/C][C]0.069038[/C][/ROW]
[ROW][C]56[/C][C]-0.025122[/C][C]-0.4753[/C][C]0.317419[/C][/ROW]
[ROW][C]57[/C][C]0.004429[/C][C]0.0838[/C][C]0.466633[/C][/ROW]
[ROW][C]58[/C][C]-0.00338[/C][C]-0.064[/C][C]0.474521[/C][/ROW]
[ROW][C]59[/C][C]-0.010997[/C][C]-0.2081[/C][C]0.417648[/C][/ROW]
[ROW][C]60[/C][C]0.043239[/C][C]0.8181[/C][C]0.206919[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64753&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1201812.27390.011781
2-0.01047-0.19810.421537
30.0725011.37180.085496
4-0.214934-4.06672.9e-05
5-0.160308-3.03320.001298
60.0435680.82430.205146
70.0771511.45980.072616
80.0190170.35980.359595
90.0370140.70030.242086
100.0471790.89270.186317
110.0364050.68880.245696
12-0.084928-1.60690.054478
13-0.004423-0.08370.466676
14-0.049981-0.94570.172476
15-0.085608-1.61980.05308
16-0.029284-0.55410.289936
17-0.013512-0.25570.399179
18-0.049324-0.93320.175661
19-0.124429-2.35430.009548
20-0.007686-0.14540.442225
210.0088890.16820.433267
220.0597371.13030.129559
230.0495450.93740.174584
240.0807771.52840.063653
25-0.011023-0.20860.417456
26-0.03657-0.69190.24471
27-0.032254-0.61030.271032
28-0.066908-1.2660.103177
290.0147250.27860.390353
300.1495432.82950.002462
310.082781.56630.059084
320.0031790.06010.476037
330.1479082.79850.002706
34-0.069774-1.32020.093808
35-0.051901-0.9820.163377
360.0764881.44720.074356
37-0.002989-0.05650.477469
380.026250.49670.309865
39-0.003792-0.07170.471422
40-0.041201-0.77960.218082
41-0.039275-0.74310.228949
42-0.029664-0.56130.287481
430.0185940.35180.362589
44-0.081008-1.53280.06311
45-0.037842-0.7160.237229
46-0.001805-0.03410.48639
470.0221640.41940.337604
48-0.055181-1.04410.148576
49-0.023893-0.45210.325747
500.020710.39190.347701
51-0.044276-0.83770.201367
52-0.037604-0.71150.238618
53-0.022911-0.43350.332455
54-0.038207-0.72290.235103
55-0.078554-1.48630.069038
56-0.025122-0.47530.317419
570.0044290.08380.466633
58-0.00338-0.0640.474521
59-0.010997-0.20810.417648
600.0432390.81810.206919







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1201812.27390.011781
2-0.025279-0.47830.316365
30.0780041.47590.070423
4-0.238781-4.51794e-06
5-0.104469-1.97660.024425
60.0640431.21180.113203
70.1065182.01540.022304
8-0.027529-0.52090.301389
9-0.033929-0.6420.260651
100.037050.7010.241871
110.0912181.72590.042612
12-0.087668-1.65880.04902
13-0.004979-0.09420.462499
14-0.058711-1.11090.133685
15-0.018115-0.34270.365994
16-0.046404-0.8780.190265
17-0.033658-0.63680.262318
18-0.063666-1.20460.114572
19-0.142947-2.70470.003582
20-0.001338-0.02530.489911
210.0171560.32460.372833
220.0808561.52990.063466
23-0.025857-0.48920.312487
240.0487330.92210.178554
250.0012780.02420.49036
260.0282230.5340.296838
27-0.03096-0.58580.279192
28-0.047034-0.88990.187051
290.0335130.63410.263211
300.1624653.0740.001137
310.0121220.22940.409357
32-0.067512-1.27740.101145
330.1105132.0910.018616
34-0.042407-0.80240.211432
350.0218550.41350.339739
360.0482720.91330.180838
370.0199940.37830.352715
380.0337350.63830.261842
39-0.055107-1.04270.148902
40-0.041262-0.78070.217745
410.0029160.05520.478019
420.0005190.00980.496086
430.0255840.48410.314318
44-0.145846-2.75950.003043
450.0222130.42030.337263
46-0.026074-0.49330.311039
470.0675431.2780.101043
48-0.0904-1.71040.044025
49-0.002916-0.05520.478015
500.064941.22870.109991
510.0036530.06910.472465
52-0.030005-0.56770.285288
53-0.097911-1.85260.032384
54-0.036613-0.69280.244455
55-0.057534-1.08860.138533
56-0.028766-0.54430.293297
57-0.023137-0.43780.330906
58-0.029666-0.56130.287471
59-0.069204-1.30940.095618
60-0.01408-0.26640.395042

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.120181 & 2.2739 & 0.011781 \tabularnewline
2 & -0.025279 & -0.4783 & 0.316365 \tabularnewline
3 & 0.078004 & 1.4759 & 0.070423 \tabularnewline
4 & -0.238781 & -4.5179 & 4e-06 \tabularnewline
5 & -0.104469 & -1.9766 & 0.024425 \tabularnewline
6 & 0.064043 & 1.2118 & 0.113203 \tabularnewline
7 & 0.106518 & 2.0154 & 0.022304 \tabularnewline
8 & -0.027529 & -0.5209 & 0.301389 \tabularnewline
9 & -0.033929 & -0.642 & 0.260651 \tabularnewline
10 & 0.03705 & 0.701 & 0.241871 \tabularnewline
11 & 0.091218 & 1.7259 & 0.042612 \tabularnewline
12 & -0.087668 & -1.6588 & 0.04902 \tabularnewline
13 & -0.004979 & -0.0942 & 0.462499 \tabularnewline
14 & -0.058711 & -1.1109 & 0.133685 \tabularnewline
15 & -0.018115 & -0.3427 & 0.365994 \tabularnewline
16 & -0.046404 & -0.878 & 0.190265 \tabularnewline
17 & -0.033658 & -0.6368 & 0.262318 \tabularnewline
18 & -0.063666 & -1.2046 & 0.114572 \tabularnewline
19 & -0.142947 & -2.7047 & 0.003582 \tabularnewline
20 & -0.001338 & -0.0253 & 0.489911 \tabularnewline
21 & 0.017156 & 0.3246 & 0.372833 \tabularnewline
22 & 0.080856 & 1.5299 & 0.063466 \tabularnewline
23 & -0.025857 & -0.4892 & 0.312487 \tabularnewline
24 & 0.048733 & 0.9221 & 0.178554 \tabularnewline
25 & 0.001278 & 0.0242 & 0.49036 \tabularnewline
26 & 0.028223 & 0.534 & 0.296838 \tabularnewline
27 & -0.03096 & -0.5858 & 0.279192 \tabularnewline
28 & -0.047034 & -0.8899 & 0.187051 \tabularnewline
29 & 0.033513 & 0.6341 & 0.263211 \tabularnewline
30 & 0.162465 & 3.074 & 0.001137 \tabularnewline
31 & 0.012122 & 0.2294 & 0.409357 \tabularnewline
32 & -0.067512 & -1.2774 & 0.101145 \tabularnewline
33 & 0.110513 & 2.091 & 0.018616 \tabularnewline
34 & -0.042407 & -0.8024 & 0.211432 \tabularnewline
35 & 0.021855 & 0.4135 & 0.339739 \tabularnewline
36 & 0.048272 & 0.9133 & 0.180838 \tabularnewline
37 & 0.019994 & 0.3783 & 0.352715 \tabularnewline
38 & 0.033735 & 0.6383 & 0.261842 \tabularnewline
39 & -0.055107 & -1.0427 & 0.148902 \tabularnewline
40 & -0.041262 & -0.7807 & 0.217745 \tabularnewline
41 & 0.002916 & 0.0552 & 0.478019 \tabularnewline
42 & 0.000519 & 0.0098 & 0.496086 \tabularnewline
43 & 0.025584 & 0.4841 & 0.314318 \tabularnewline
44 & -0.145846 & -2.7595 & 0.003043 \tabularnewline
45 & 0.022213 & 0.4203 & 0.337263 \tabularnewline
46 & -0.026074 & -0.4933 & 0.311039 \tabularnewline
47 & 0.067543 & 1.278 & 0.101043 \tabularnewline
48 & -0.0904 & -1.7104 & 0.044025 \tabularnewline
49 & -0.002916 & -0.0552 & 0.478015 \tabularnewline
50 & 0.06494 & 1.2287 & 0.109991 \tabularnewline
51 & 0.003653 & 0.0691 & 0.472465 \tabularnewline
52 & -0.030005 & -0.5677 & 0.285288 \tabularnewline
53 & -0.097911 & -1.8526 & 0.032384 \tabularnewline
54 & -0.036613 & -0.6928 & 0.244455 \tabularnewline
55 & -0.057534 & -1.0886 & 0.138533 \tabularnewline
56 & -0.028766 & -0.5443 & 0.293297 \tabularnewline
57 & -0.023137 & -0.4378 & 0.330906 \tabularnewline
58 & -0.029666 & -0.5613 & 0.287471 \tabularnewline
59 & -0.069204 & -1.3094 & 0.095618 \tabularnewline
60 & -0.01408 & -0.2664 & 0.395042 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64753&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]0.120181[/C][C]2.2739[/C][C]0.011781[/C][/ROW]
[ROW][C]2[/C][C]-0.025279[/C][C]-0.4783[/C][C]0.316365[/C][/ROW]
[ROW][C]3[/C][C]0.078004[/C][C]1.4759[/C][C]0.070423[/C][/ROW]
[ROW][C]4[/C][C]-0.238781[/C][C]-4.5179[/C][C]4e-06[/C][/ROW]
[ROW][C]5[/C][C]-0.104469[/C][C]-1.9766[/C][C]0.024425[/C][/ROW]
[ROW][C]6[/C][C]0.064043[/C][C]1.2118[/C][C]0.113203[/C][/ROW]
[ROW][C]7[/C][C]0.106518[/C][C]2.0154[/C][C]0.022304[/C][/ROW]
[ROW][C]8[/C][C]-0.027529[/C][C]-0.5209[/C][C]0.301389[/C][/ROW]
[ROW][C]9[/C][C]-0.033929[/C][C]-0.642[/C][C]0.260651[/C][/ROW]
[ROW][C]10[/C][C]0.03705[/C][C]0.701[/C][C]0.241871[/C][/ROW]
[ROW][C]11[/C][C]0.091218[/C][C]1.7259[/C][C]0.042612[/C][/ROW]
[ROW][C]12[/C][C]-0.087668[/C][C]-1.6588[/C][C]0.04902[/C][/ROW]
[ROW][C]13[/C][C]-0.004979[/C][C]-0.0942[/C][C]0.462499[/C][/ROW]
[ROW][C]14[/C][C]-0.058711[/C][C]-1.1109[/C][C]0.133685[/C][/ROW]
[ROW][C]15[/C][C]-0.018115[/C][C]-0.3427[/C][C]0.365994[/C][/ROW]
[ROW][C]16[/C][C]-0.046404[/C][C]-0.878[/C][C]0.190265[/C][/ROW]
[ROW][C]17[/C][C]-0.033658[/C][C]-0.6368[/C][C]0.262318[/C][/ROW]
[ROW][C]18[/C][C]-0.063666[/C][C]-1.2046[/C][C]0.114572[/C][/ROW]
[ROW][C]19[/C][C]-0.142947[/C][C]-2.7047[/C][C]0.003582[/C][/ROW]
[ROW][C]20[/C][C]-0.001338[/C][C]-0.0253[/C][C]0.489911[/C][/ROW]
[ROW][C]21[/C][C]0.017156[/C][C]0.3246[/C][C]0.372833[/C][/ROW]
[ROW][C]22[/C][C]0.080856[/C][C]1.5299[/C][C]0.063466[/C][/ROW]
[ROW][C]23[/C][C]-0.025857[/C][C]-0.4892[/C][C]0.312487[/C][/ROW]
[ROW][C]24[/C][C]0.048733[/C][C]0.9221[/C][C]0.178554[/C][/ROW]
[ROW][C]25[/C][C]0.001278[/C][C]0.0242[/C][C]0.49036[/C][/ROW]
[ROW][C]26[/C][C]0.028223[/C][C]0.534[/C][C]0.296838[/C][/ROW]
[ROW][C]27[/C][C]-0.03096[/C][C]-0.5858[/C][C]0.279192[/C][/ROW]
[ROW][C]28[/C][C]-0.047034[/C][C]-0.8899[/C][C]0.187051[/C][/ROW]
[ROW][C]29[/C][C]0.033513[/C][C]0.6341[/C][C]0.263211[/C][/ROW]
[ROW][C]30[/C][C]0.162465[/C][C]3.074[/C][C]0.001137[/C][/ROW]
[ROW][C]31[/C][C]0.012122[/C][C]0.2294[/C][C]0.409357[/C][/ROW]
[ROW][C]32[/C][C]-0.067512[/C][C]-1.2774[/C][C]0.101145[/C][/ROW]
[ROW][C]33[/C][C]0.110513[/C][C]2.091[/C][C]0.018616[/C][/ROW]
[ROW][C]34[/C][C]-0.042407[/C][C]-0.8024[/C][C]0.211432[/C][/ROW]
[ROW][C]35[/C][C]0.021855[/C][C]0.4135[/C][C]0.339739[/C][/ROW]
[ROW][C]36[/C][C]0.048272[/C][C]0.9133[/C][C]0.180838[/C][/ROW]
[ROW][C]37[/C][C]0.019994[/C][C]0.3783[/C][C]0.352715[/C][/ROW]
[ROW][C]38[/C][C]0.033735[/C][C]0.6383[/C][C]0.261842[/C][/ROW]
[ROW][C]39[/C][C]-0.055107[/C][C]-1.0427[/C][C]0.148902[/C][/ROW]
[ROW][C]40[/C][C]-0.041262[/C][C]-0.7807[/C][C]0.217745[/C][/ROW]
[ROW][C]41[/C][C]0.002916[/C][C]0.0552[/C][C]0.478019[/C][/ROW]
[ROW][C]42[/C][C]0.000519[/C][C]0.0098[/C][C]0.496086[/C][/ROW]
[ROW][C]43[/C][C]0.025584[/C][C]0.4841[/C][C]0.314318[/C][/ROW]
[ROW][C]44[/C][C]-0.145846[/C][C]-2.7595[/C][C]0.003043[/C][/ROW]
[ROW][C]45[/C][C]0.022213[/C][C]0.4203[/C][C]0.337263[/C][/ROW]
[ROW][C]46[/C][C]-0.026074[/C][C]-0.4933[/C][C]0.311039[/C][/ROW]
[ROW][C]47[/C][C]0.067543[/C][C]1.278[/C][C]0.101043[/C][/ROW]
[ROW][C]48[/C][C]-0.0904[/C][C]-1.7104[/C][C]0.044025[/C][/ROW]
[ROW][C]49[/C][C]-0.002916[/C][C]-0.0552[/C][C]0.478015[/C][/ROW]
[ROW][C]50[/C][C]0.06494[/C][C]1.2287[/C][C]0.109991[/C][/ROW]
[ROW][C]51[/C][C]0.003653[/C][C]0.0691[/C][C]0.472465[/C][/ROW]
[ROW][C]52[/C][C]-0.030005[/C][C]-0.5677[/C][C]0.285288[/C][/ROW]
[ROW][C]53[/C][C]-0.097911[/C][C]-1.8526[/C][C]0.032384[/C][/ROW]
[ROW][C]54[/C][C]-0.036613[/C][C]-0.6928[/C][C]0.244455[/C][/ROW]
[ROW][C]55[/C][C]-0.057534[/C][C]-1.0886[/C][C]0.138533[/C][/ROW]
[ROW][C]56[/C][C]-0.028766[/C][C]-0.5443[/C][C]0.293297[/C][/ROW]
[ROW][C]57[/C][C]-0.023137[/C][C]-0.4378[/C][C]0.330906[/C][/ROW]
[ROW][C]58[/C][C]-0.029666[/C][C]-0.5613[/C][C]0.287471[/C][/ROW]
[ROW][C]59[/C][C]-0.069204[/C][C]-1.3094[/C][C]0.095618[/C][/ROW]
[ROW][C]60[/C][C]-0.01408[/C][C]-0.2664[/C][C]0.395042[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64753&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64753&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1201812.27390.011781
2-0.025279-0.47830.316365
30.0780041.47590.070423
4-0.238781-4.51794e-06
5-0.104469-1.97660.024425
60.0640431.21180.113203
70.1065182.01540.022304
8-0.027529-0.52090.301389
9-0.033929-0.6420.260651
100.037050.7010.241871
110.0912181.72590.042612
12-0.087668-1.65880.04902
13-0.004979-0.09420.462499
14-0.058711-1.11090.133685
15-0.018115-0.34270.365994
16-0.046404-0.8780.190265
17-0.033658-0.63680.262318
18-0.063666-1.20460.114572
19-0.142947-2.70470.003582
20-0.001338-0.02530.489911
210.0171560.32460.372833
220.0808561.52990.063466
23-0.025857-0.48920.312487
240.0487330.92210.178554
250.0012780.02420.49036
260.0282230.5340.296838
27-0.03096-0.58580.279192
28-0.047034-0.88990.187051
290.0335130.63410.263211
300.1624653.0740.001137
310.0121220.22940.409357
32-0.067512-1.27740.101145
330.1105132.0910.018616
34-0.042407-0.80240.211432
350.0218550.41350.339739
360.0482720.91330.180838
370.0199940.37830.352715
380.0337350.63830.261842
39-0.055107-1.04270.148902
40-0.041262-0.78070.217745
410.0029160.05520.478019
420.0005190.00980.496086
430.0255840.48410.314318
44-0.145846-2.75950.003043
450.0222130.42030.337263
46-0.026074-0.49330.311039
470.0675431.2780.101043
48-0.0904-1.71040.044025
49-0.002916-0.05520.478015
500.064941.22870.109991
510.0036530.06910.472465
52-0.030005-0.56770.285288
53-0.097911-1.85260.032384
54-0.036613-0.69280.244455
55-0.057534-1.08860.138533
56-0.028766-0.54430.293297
57-0.023137-0.43780.330906
58-0.029666-0.56130.287471
59-0.069204-1.30940.095618
60-0.01408-0.26640.395042



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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')