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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 computationMon, 18 Dec 2017 11:03:48 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/18/t1513591446b3b8vbdks3mnczh.htm/, Retrieved Mon, 13 May 2024 20:33:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310103, Retrieved Mon, 13 May 2024 20:33:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2017-12-18 10:03:48] [29a87998297b2697efa2253fad859704] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
52
54,9
60,5
54,8
60,1
60,3
49,8
53,8
64,8
62
65,2
60,1
61,2
63,6
68,6
63,1
66,5
71,9
58,1
61,5
66,2
72,3
67
62,9
66,4
65,6
70,9
68,4
66,4
67,6
64,1
62,1
70
74,4
67
64,8
70,7
64
72,5
70,4
63,6
69,8
67,7
66,4
78,9
79,9
69,1
81,2
66
71,8
86,1
76,1
70,5
83,3
74,8
73,4
86,5
82
80,8
91,5
77
72,3
83,5
79
76,7
83,1
71,1
75,5
90,9
85,4
84,8
83,8
79,3
79,9
93
78,1
82,3
87,3
74,6
80
91,3
94,2
90,9
88
81,6
77,4
91
79,9
83,4
91,6
85,2
84,1
87
92,8
89,2
87,3
89,5
86,8
92
92,2
86,4
92,9
91,2
80,3
102
99
89,2
103
80,4
83,4
97,6
87
84,4
94,1
88,9
82,3
94,7
94,5
91,6
96,8
87,9
99,9
109,5
91,2
89,4
109,7
96,9
94,1
104,4
100,8
107,4
108,9
95,2
102,7
130,9
104
106,5
106,1
97,8
112,2
114,5
105,8
101
101,2
96,5
99,5
123,8
94,6
95,8
105,4
104,4
105,2
112,7
114,8
108,9
103,8
102,5
98,1
118,2
114,8
109,9
116,7
116,9
104,4
113,5
123,8
116,4
114,1
102,8
112,7
121,1
120,8
117,8
130,4
110,9
105,4
137,6
133,3
123,3
122,8
110,2
101,4
128,7
120,6
110,1
121,6
113
115,9
131,1
127,4
123,9
120,8
108,5
112,9
129,6
121,3
119,1
140,8
127,4
128,1
136,6
126,5
120,8
144,3
116
123,4
138,6
118,3
124,2
136
127,4
131,6

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310103&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=310103&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310103&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.384161-5.58030
2-0.368032-5.3460
30.4903887.12330
4-0.313427-4.55284e-06
5-0.165749-2.40760.008458
60.5237027.60720
7-0.257636-3.74240.000117
8-0.205997-2.99230.001549
90.4238216.15640
10-0.368057-5.34630
11-0.150961-2.19280.014706
120.5981178.68820
13-0.277126-4.02554e-05
14-0.205269-2.98170.001602
150.3481655.05740
16-0.26889-3.90596.3e-05
17-0.093997-1.36540.086793
180.4031235.85570
19-0.264587-3.84338e-05
20-0.093541-1.35880.087836
210.3684085.35140
22-0.388111-5.63760
23-0.065149-0.94630.172529
240.4525256.57330
25-0.207951-3.02070.001417
26-0.170576-2.47780.007003
270.3127384.54285e-06
28-0.221842-3.22240.000736
29-0.122509-1.77950.038295
300.3469295.03941e-06
31-0.19961-2.89950.002066
32-0.066406-0.96460.167924
330.2594273.76840.000107
34-0.226736-3.29350.00058
35-0.155872-2.26420.01229
360.3607485.24020
37-0.047042-0.68330.247576
38-0.243646-3.53920.000247
390.2782784.04223.7e-05
40-0.142779-2.0740.019647
41-0.149343-2.16930.015588
420.2891844.20062e-05
43-0.106761-1.55080.061225
44-0.131074-1.9040.029138
450.2613223.79599.6e-05
46-0.173842-2.52520.006149
47-0.203197-2.95160.001759
480.4146166.02270

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.384161 & -5.5803 & 0 \tabularnewline
2 & -0.368032 & -5.346 & 0 \tabularnewline
3 & 0.490388 & 7.1233 & 0 \tabularnewline
4 & -0.313427 & -4.5528 & 4e-06 \tabularnewline
5 & -0.165749 & -2.4076 & 0.008458 \tabularnewline
6 & 0.523702 & 7.6072 & 0 \tabularnewline
7 & -0.257636 & -3.7424 & 0.000117 \tabularnewline
8 & -0.205997 & -2.9923 & 0.001549 \tabularnewline
9 & 0.423821 & 6.1564 & 0 \tabularnewline
10 & -0.368057 & -5.3463 & 0 \tabularnewline
11 & -0.150961 & -2.1928 & 0.014706 \tabularnewline
12 & 0.598117 & 8.6882 & 0 \tabularnewline
13 & -0.277126 & -4.0255 & 4e-05 \tabularnewline
14 & -0.205269 & -2.9817 & 0.001602 \tabularnewline
15 & 0.348165 & 5.0574 & 0 \tabularnewline
16 & -0.26889 & -3.9059 & 6.3e-05 \tabularnewline
17 & -0.093997 & -1.3654 & 0.086793 \tabularnewline
18 & 0.403123 & 5.8557 & 0 \tabularnewline
19 & -0.264587 & -3.8433 & 8e-05 \tabularnewline
20 & -0.093541 & -1.3588 & 0.087836 \tabularnewline
21 & 0.368408 & 5.3514 & 0 \tabularnewline
22 & -0.388111 & -5.6376 & 0 \tabularnewline
23 & -0.065149 & -0.9463 & 0.172529 \tabularnewline
24 & 0.452525 & 6.5733 & 0 \tabularnewline
25 & -0.207951 & -3.0207 & 0.001417 \tabularnewline
26 & -0.170576 & -2.4778 & 0.007003 \tabularnewline
27 & 0.312738 & 4.5428 & 5e-06 \tabularnewline
28 & -0.221842 & -3.2224 & 0.000736 \tabularnewline
29 & -0.122509 & -1.7795 & 0.038295 \tabularnewline
30 & 0.346929 & 5.0394 & 1e-06 \tabularnewline
31 & -0.19961 & -2.8995 & 0.002066 \tabularnewline
32 & -0.066406 & -0.9646 & 0.167924 \tabularnewline
33 & 0.259427 & 3.7684 & 0.000107 \tabularnewline
34 & -0.226736 & -3.2935 & 0.00058 \tabularnewline
35 & -0.155872 & -2.2642 & 0.01229 \tabularnewline
36 & 0.360748 & 5.2402 & 0 \tabularnewline
37 & -0.047042 & -0.6833 & 0.247576 \tabularnewline
38 & -0.243646 & -3.5392 & 0.000247 \tabularnewline
39 & 0.278278 & 4.0422 & 3.7e-05 \tabularnewline
40 & -0.142779 & -2.074 & 0.019647 \tabularnewline
41 & -0.149343 & -2.1693 & 0.015588 \tabularnewline
42 & 0.289184 & 4.2006 & 2e-05 \tabularnewline
43 & -0.106761 & -1.5508 & 0.061225 \tabularnewline
44 & -0.131074 & -1.904 & 0.029138 \tabularnewline
45 & 0.261322 & 3.7959 & 9.6e-05 \tabularnewline
46 & -0.173842 & -2.5252 & 0.006149 \tabularnewline
47 & -0.203197 & -2.9516 & 0.001759 \tabularnewline
48 & 0.414616 & 6.0227 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310103&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]-0.384161[/C][C]-5.5803[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.368032[/C][C]-5.346[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.490388[/C][C]7.1233[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]-0.313427[/C][C]-4.5528[/C][C]4e-06[/C][/ROW]
[ROW][C]5[/C][C]-0.165749[/C][C]-2.4076[/C][C]0.008458[/C][/ROW]
[ROW][C]6[/C][C]0.523702[/C][C]7.6072[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.257636[/C][C]-3.7424[/C][C]0.000117[/C][/ROW]
[ROW][C]8[/C][C]-0.205997[/C][C]-2.9923[/C][C]0.001549[/C][/ROW]
[ROW][C]9[/C][C]0.423821[/C][C]6.1564[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]-0.368057[/C][C]-5.3463[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]-0.150961[/C][C]-2.1928[/C][C]0.014706[/C][/ROW]
[ROW][C]12[/C][C]0.598117[/C][C]8.6882[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.277126[/C][C]-4.0255[/C][C]4e-05[/C][/ROW]
[ROW][C]14[/C][C]-0.205269[/C][C]-2.9817[/C][C]0.001602[/C][/ROW]
[ROW][C]15[/C][C]0.348165[/C][C]5.0574[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]-0.26889[/C][C]-3.9059[/C][C]6.3e-05[/C][/ROW]
[ROW][C]17[/C][C]-0.093997[/C][C]-1.3654[/C][C]0.086793[/C][/ROW]
[ROW][C]18[/C][C]0.403123[/C][C]5.8557[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]-0.264587[/C][C]-3.8433[/C][C]8e-05[/C][/ROW]
[ROW][C]20[/C][C]-0.093541[/C][C]-1.3588[/C][C]0.087836[/C][/ROW]
[ROW][C]21[/C][C]0.368408[/C][C]5.3514[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]-0.388111[/C][C]-5.6376[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]-0.065149[/C][C]-0.9463[/C][C]0.172529[/C][/ROW]
[ROW][C]24[/C][C]0.452525[/C][C]6.5733[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.207951[/C][C]-3.0207[/C][C]0.001417[/C][/ROW]
[ROW][C]26[/C][C]-0.170576[/C][C]-2.4778[/C][C]0.007003[/C][/ROW]
[ROW][C]27[/C][C]0.312738[/C][C]4.5428[/C][C]5e-06[/C][/ROW]
[ROW][C]28[/C][C]-0.221842[/C][C]-3.2224[/C][C]0.000736[/C][/ROW]
[ROW][C]29[/C][C]-0.122509[/C][C]-1.7795[/C][C]0.038295[/C][/ROW]
[ROW][C]30[/C][C]0.346929[/C][C]5.0394[/C][C]1e-06[/C][/ROW]
[ROW][C]31[/C][C]-0.19961[/C][C]-2.8995[/C][C]0.002066[/C][/ROW]
[ROW][C]32[/C][C]-0.066406[/C][C]-0.9646[/C][C]0.167924[/C][/ROW]
[ROW][C]33[/C][C]0.259427[/C][C]3.7684[/C][C]0.000107[/C][/ROW]
[ROW][C]34[/C][C]-0.226736[/C][C]-3.2935[/C][C]0.00058[/C][/ROW]
[ROW][C]35[/C][C]-0.155872[/C][C]-2.2642[/C][C]0.01229[/C][/ROW]
[ROW][C]36[/C][C]0.360748[/C][C]5.2402[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.047042[/C][C]-0.6833[/C][C]0.247576[/C][/ROW]
[ROW][C]38[/C][C]-0.243646[/C][C]-3.5392[/C][C]0.000247[/C][/ROW]
[ROW][C]39[/C][C]0.278278[/C][C]4.0422[/C][C]3.7e-05[/C][/ROW]
[ROW][C]40[/C][C]-0.142779[/C][C]-2.074[/C][C]0.019647[/C][/ROW]
[ROW][C]41[/C][C]-0.149343[/C][C]-2.1693[/C][C]0.015588[/C][/ROW]
[ROW][C]42[/C][C]0.289184[/C][C]4.2006[/C][C]2e-05[/C][/ROW]
[ROW][C]43[/C][C]-0.106761[/C][C]-1.5508[/C][C]0.061225[/C][/ROW]
[ROW][C]44[/C][C]-0.131074[/C][C]-1.904[/C][C]0.029138[/C][/ROW]
[ROW][C]45[/C][C]0.261322[/C][C]3.7959[/C][C]9.6e-05[/C][/ROW]
[ROW][C]46[/C][C]-0.173842[/C][C]-2.5252[/C][C]0.006149[/C][/ROW]
[ROW][C]47[/C][C]-0.203197[/C][C]-2.9516[/C][C]0.001759[/C][/ROW]
[ROW][C]48[/C][C]0.414616[/C][C]6.0227[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310103&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310103&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
1-0.384161-5.58030
2-0.368032-5.3460
30.4903887.12330
4-0.313427-4.55284e-06
5-0.165749-2.40760.008458
60.5237027.60720
7-0.257636-3.74240.000117
8-0.205997-2.99230.001549
90.4238216.15640
10-0.368057-5.34630
11-0.150961-2.19280.014706
120.5981178.68820
13-0.277126-4.02554e-05
14-0.205269-2.98170.001602
150.3481655.05740
16-0.26889-3.90596.3e-05
17-0.093997-1.36540.086793
180.4031235.85570
19-0.264587-3.84338e-05
20-0.093541-1.35880.087836
210.3684085.35140
22-0.388111-5.63760
23-0.065149-0.94630.172529
240.4525256.57330
25-0.207951-3.02070.001417
26-0.170576-2.47780.007003
270.3127384.54285e-06
28-0.221842-3.22240.000736
29-0.122509-1.77950.038295
300.3469295.03941e-06
31-0.19961-2.89950.002066
32-0.066406-0.96460.167924
330.2594273.76840.000107
34-0.226736-3.29350.00058
35-0.155872-2.26420.01229
360.3607485.24020
37-0.047042-0.68330.247576
38-0.243646-3.53920.000247
390.2782784.04223.7e-05
40-0.142779-2.0740.019647
41-0.149343-2.16930.015588
420.2891844.20062e-05
43-0.106761-1.55080.061225
44-0.131074-1.9040.029138
450.2613223.79599.6e-05
46-0.173842-2.52520.006149
47-0.203197-2.95160.001759
480.4146166.02270






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.384161-5.58030
2-0.604879-8.78640
30.0575610.83610.202016
4-0.400193-5.81310
5-0.371563-5.39730
60.0024270.03530.485954
7-0.040824-0.5930.276905
8-0.087162-1.26610.103435
90.1428852.07550.019575
10-0.208206-3.02440.0014
11-0.350183-5.08670
120.0183640.26680.394961
130.07311.06180.144762
140.0759291.10290.135657
15-0.000627-0.00910.496373
160.0389560.56590.286043
17-0.006321-0.09180.463466
18-0.015679-0.22780.410029
19-0.118406-1.71990.043454
20-0.093728-1.36150.087407
210.0650160.94440.173021
22-0.109558-1.59140.056506
23-0.157901-2.29360.011398
24-0.148087-2.15110.016303
250.0651460.94630.172541
26-0.115553-1.67850.047365
27-0.018437-0.26780.394555
280.0699321.01580.15544
29-0.016582-0.24090.404945
30-0.070348-1.02190.154008
31-0.037411-0.54340.293706
320.014210.20640.418336
33-0.103278-1.50020.067528
340.088641.28760.099652
35-0.139368-2.02440.022093
36-0.102948-1.49540.068151
370.0826471.20050.115641
38-0.07457-1.08320.13998
39-0.00471-0.06840.47276
40-0.049463-0.71850.236623
410.0356140.51730.302738
42-0.042511-0.61750.268785
430.0499710.72590.234361
44-0.036547-0.53090.298031
450.0311950.45310.32546
46-0.008086-0.11740.453308
47-0.029094-0.42260.336501
480.1431732.07970.019381

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.384161 & -5.5803 & 0 \tabularnewline
2 & -0.604879 & -8.7864 & 0 \tabularnewline
3 & 0.057561 & 0.8361 & 0.202016 \tabularnewline
4 & -0.400193 & -5.8131 & 0 \tabularnewline
5 & -0.371563 & -5.3973 & 0 \tabularnewline
6 & 0.002427 & 0.0353 & 0.485954 \tabularnewline
7 & -0.040824 & -0.593 & 0.276905 \tabularnewline
8 & -0.087162 & -1.2661 & 0.103435 \tabularnewline
9 & 0.142885 & 2.0755 & 0.019575 \tabularnewline
10 & -0.208206 & -3.0244 & 0.0014 \tabularnewline
11 & -0.350183 & -5.0867 & 0 \tabularnewline
12 & 0.018364 & 0.2668 & 0.394961 \tabularnewline
13 & 0.0731 & 1.0618 & 0.144762 \tabularnewline
14 & 0.075929 & 1.1029 & 0.135657 \tabularnewline
15 & -0.000627 & -0.0091 & 0.496373 \tabularnewline
16 & 0.038956 & 0.5659 & 0.286043 \tabularnewline
17 & -0.006321 & -0.0918 & 0.463466 \tabularnewline
18 & -0.015679 & -0.2278 & 0.410029 \tabularnewline
19 & -0.118406 & -1.7199 & 0.043454 \tabularnewline
20 & -0.093728 & -1.3615 & 0.087407 \tabularnewline
21 & 0.065016 & 0.9444 & 0.173021 \tabularnewline
22 & -0.109558 & -1.5914 & 0.056506 \tabularnewline
23 & -0.157901 & -2.2936 & 0.011398 \tabularnewline
24 & -0.148087 & -2.1511 & 0.016303 \tabularnewline
25 & 0.065146 & 0.9463 & 0.172541 \tabularnewline
26 & -0.115553 & -1.6785 & 0.047365 \tabularnewline
27 & -0.018437 & -0.2678 & 0.394555 \tabularnewline
28 & 0.069932 & 1.0158 & 0.15544 \tabularnewline
29 & -0.016582 & -0.2409 & 0.404945 \tabularnewline
30 & -0.070348 & -1.0219 & 0.154008 \tabularnewline
31 & -0.037411 & -0.5434 & 0.293706 \tabularnewline
32 & 0.01421 & 0.2064 & 0.418336 \tabularnewline
33 & -0.103278 & -1.5002 & 0.067528 \tabularnewline
34 & 0.08864 & 1.2876 & 0.099652 \tabularnewline
35 & -0.139368 & -2.0244 & 0.022093 \tabularnewline
36 & -0.102948 & -1.4954 & 0.068151 \tabularnewline
37 & 0.082647 & 1.2005 & 0.115641 \tabularnewline
38 & -0.07457 & -1.0832 & 0.13998 \tabularnewline
39 & -0.00471 & -0.0684 & 0.47276 \tabularnewline
40 & -0.049463 & -0.7185 & 0.236623 \tabularnewline
41 & 0.035614 & 0.5173 & 0.302738 \tabularnewline
42 & -0.042511 & -0.6175 & 0.268785 \tabularnewline
43 & 0.049971 & 0.7259 & 0.234361 \tabularnewline
44 & -0.036547 & -0.5309 & 0.298031 \tabularnewline
45 & 0.031195 & 0.4531 & 0.32546 \tabularnewline
46 & -0.008086 & -0.1174 & 0.453308 \tabularnewline
47 & -0.029094 & -0.4226 & 0.336501 \tabularnewline
48 & 0.143173 & 2.0797 & 0.019381 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310103&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]-0.384161[/C][C]-5.5803[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.604879[/C][C]-8.7864[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.057561[/C][C]0.8361[/C][C]0.202016[/C][/ROW]
[ROW][C]4[/C][C]-0.400193[/C][C]-5.8131[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]-0.371563[/C][C]-5.3973[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.002427[/C][C]0.0353[/C][C]0.485954[/C][/ROW]
[ROW][C]7[/C][C]-0.040824[/C][C]-0.593[/C][C]0.276905[/C][/ROW]
[ROW][C]8[/C][C]-0.087162[/C][C]-1.2661[/C][C]0.103435[/C][/ROW]
[ROW][C]9[/C][C]0.142885[/C][C]2.0755[/C][C]0.019575[/C][/ROW]
[ROW][C]10[/C][C]-0.208206[/C][C]-3.0244[/C][C]0.0014[/C][/ROW]
[ROW][C]11[/C][C]-0.350183[/C][C]-5.0867[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.018364[/C][C]0.2668[/C][C]0.394961[/C][/ROW]
[ROW][C]13[/C][C]0.0731[/C][C]1.0618[/C][C]0.144762[/C][/ROW]
[ROW][C]14[/C][C]0.075929[/C][C]1.1029[/C][C]0.135657[/C][/ROW]
[ROW][C]15[/C][C]-0.000627[/C][C]-0.0091[/C][C]0.496373[/C][/ROW]
[ROW][C]16[/C][C]0.038956[/C][C]0.5659[/C][C]0.286043[/C][/ROW]
[ROW][C]17[/C][C]-0.006321[/C][C]-0.0918[/C][C]0.463466[/C][/ROW]
[ROW][C]18[/C][C]-0.015679[/C][C]-0.2278[/C][C]0.410029[/C][/ROW]
[ROW][C]19[/C][C]-0.118406[/C][C]-1.7199[/C][C]0.043454[/C][/ROW]
[ROW][C]20[/C][C]-0.093728[/C][C]-1.3615[/C][C]0.087407[/C][/ROW]
[ROW][C]21[/C][C]0.065016[/C][C]0.9444[/C][C]0.173021[/C][/ROW]
[ROW][C]22[/C][C]-0.109558[/C][C]-1.5914[/C][C]0.056506[/C][/ROW]
[ROW][C]23[/C][C]-0.157901[/C][C]-2.2936[/C][C]0.011398[/C][/ROW]
[ROW][C]24[/C][C]-0.148087[/C][C]-2.1511[/C][C]0.016303[/C][/ROW]
[ROW][C]25[/C][C]0.065146[/C][C]0.9463[/C][C]0.172541[/C][/ROW]
[ROW][C]26[/C][C]-0.115553[/C][C]-1.6785[/C][C]0.047365[/C][/ROW]
[ROW][C]27[/C][C]-0.018437[/C][C]-0.2678[/C][C]0.394555[/C][/ROW]
[ROW][C]28[/C][C]0.069932[/C][C]1.0158[/C][C]0.15544[/C][/ROW]
[ROW][C]29[/C][C]-0.016582[/C][C]-0.2409[/C][C]0.404945[/C][/ROW]
[ROW][C]30[/C][C]-0.070348[/C][C]-1.0219[/C][C]0.154008[/C][/ROW]
[ROW][C]31[/C][C]-0.037411[/C][C]-0.5434[/C][C]0.293706[/C][/ROW]
[ROW][C]32[/C][C]0.01421[/C][C]0.2064[/C][C]0.418336[/C][/ROW]
[ROW][C]33[/C][C]-0.103278[/C][C]-1.5002[/C][C]0.067528[/C][/ROW]
[ROW][C]34[/C][C]0.08864[/C][C]1.2876[/C][C]0.099652[/C][/ROW]
[ROW][C]35[/C][C]-0.139368[/C][C]-2.0244[/C][C]0.022093[/C][/ROW]
[ROW][C]36[/C][C]-0.102948[/C][C]-1.4954[/C][C]0.068151[/C][/ROW]
[ROW][C]37[/C][C]0.082647[/C][C]1.2005[/C][C]0.115641[/C][/ROW]
[ROW][C]38[/C][C]-0.07457[/C][C]-1.0832[/C][C]0.13998[/C][/ROW]
[ROW][C]39[/C][C]-0.00471[/C][C]-0.0684[/C][C]0.47276[/C][/ROW]
[ROW][C]40[/C][C]-0.049463[/C][C]-0.7185[/C][C]0.236623[/C][/ROW]
[ROW][C]41[/C][C]0.035614[/C][C]0.5173[/C][C]0.302738[/C][/ROW]
[ROW][C]42[/C][C]-0.042511[/C][C]-0.6175[/C][C]0.268785[/C][/ROW]
[ROW][C]43[/C][C]0.049971[/C][C]0.7259[/C][C]0.234361[/C][/ROW]
[ROW][C]44[/C][C]-0.036547[/C][C]-0.5309[/C][C]0.298031[/C][/ROW]
[ROW][C]45[/C][C]0.031195[/C][C]0.4531[/C][C]0.32546[/C][/ROW]
[ROW][C]46[/C][C]-0.008086[/C][C]-0.1174[/C][C]0.453308[/C][/ROW]
[ROW][C]47[/C][C]-0.029094[/C][C]-0.4226[/C][C]0.336501[/C][/ROW]
[ROW][C]48[/C][C]0.143173[/C][C]2.0797[/C][C]0.019381[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310103&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310103&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
1-0.384161-5.58030
2-0.604879-8.78640
30.0575610.83610.202016
4-0.400193-5.81310
5-0.371563-5.39730
60.0024270.03530.485954
7-0.040824-0.5930.276905
8-0.087162-1.26610.103435
90.1428852.07550.019575
10-0.208206-3.02440.0014
11-0.350183-5.08670
120.0183640.26680.394961
130.07311.06180.144762
140.0759291.10290.135657
15-0.000627-0.00910.496373
160.0389560.56590.286043
17-0.006321-0.09180.463466
18-0.015679-0.22780.410029
19-0.118406-1.71990.043454
20-0.093728-1.36150.087407
210.0650160.94440.173021
22-0.109558-1.59140.056506
23-0.157901-2.29360.011398
24-0.148087-2.15110.016303
250.0651460.94630.172541
26-0.115553-1.67850.047365
27-0.018437-0.26780.394555
280.0699321.01580.15544
29-0.016582-0.24090.404945
30-0.070348-1.02190.154008
31-0.037411-0.54340.293706
320.014210.20640.418336
33-0.103278-1.50020.067528
340.088641.28760.099652
35-0.139368-2.02440.022093
36-0.102948-1.49540.068151
370.0826471.20050.115641
38-0.07457-1.08320.13998
39-0.00471-0.06840.47276
40-0.049463-0.71850.236623
410.0356140.51730.302738
42-0.042511-0.61750.268785
430.0499710.72590.234361
44-0.036547-0.53090.298031
450.0311950.45310.32546
46-0.008086-0.11740.453308
47-0.029094-0.42260.336501
480.1431732.07970.019381


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
x <- na.omit(x)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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,'ACF(k)',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,'PACF(k)',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')