FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationThu, 07 Dec 2017 11:52:48 +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/07/t1512643988dvrlfrvfjq6ouxv.htm/, Retrieved Wed, 15 May 2024 19:28:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308682, Retrieved Wed, 15 May 2024 19:28:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98

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] [DA] [2017-12-07 10:52:48] [467f8ec0164a59d5b0902e2bf4d37c85] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
120.7
134.1
143.6
115.1
135.1
123.6
110.7
104.3
143.7
149.7
143.3
115.3
136.2
137.4
147.6
123.7
131.6
132.7
123
108.2
140.9
149.2
134.5
103.2
136.2
135.6
139.7
131
124.4
123.6
125.1
106.2
144.4
153.7
131.5
105.5
136.3
133.4
129.8
129.1
113
117.1
115.4
96.5
141
141.3
121
106
121.9
122.4
137.4
118.9
106.7
126.5
110.8
99.3
138.7
128.9
121.9
106
113.1
124.2
129.2
116.5
105.7
122
105.1
100.8
131.8
119.9
127.1
107.1
115.8
122.9
137.5
108.9
114.9
129.7
111.8
103.4
140.3
140.7
136.1
106.3
127.7
136.4
145.1
116.5
117.6
129
117.4
107.2
130.9
145.1
127.8
96.6
126
130.1
124.5
137.4
105.6
113.3
108.4
83.5
116.2
115.6
95.6
83.5
95.3
95.8
100.4
90.9
80
93.8
92.3
74.3
101.4
103.7
92.4
83.4
91.6
101.2
109.2
100.3
91
110.9
96.3
80.4
114.5
109.9
104.1
90.7
94.6
100.4
115.9
94.4
102.5
97.3
90
81.1
107.3
100.5
95.4
81.1
92.2
98.4
98.6
81.4
85.5
90.4
83.7
73.3
89.8
101.6
87.5
65.3
87.1
89.9
91.5
84.7
84.1
86.7
89.6
65.7
92.9
97.7
84.4
68.1
95
96.3
94.7
89.7
81.3
89.3
94.2
68.7
105.7
102
84.3
74.9
92.9
100.4
99.4
94.6
84
102.2
91.4
79.8
101
97.5
87.8
77.1
89.6
100.9
97.8
90.5
84.2
96.8
82.9
75.6
91.9
85.4
90.4
74
93.1
94.9
102.9
80.7
91.7
95.5
84.8
74.4

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308682&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308682&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308682&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 time1 seconds
R ServerBig Analytics Cloud Computing Center






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.552368-7.79210
2-0.017685-0.24950.401625
30.2987084.21381.9e-05
4-0.244675-3.45160.00034
5-0.009124-0.12870.44886
60.2838524.00424.4e-05
7-0.325748-4.59524e-06
80.1613922.27670.011934
90.1164361.64250.05103
10-0.249599-3.5210.000266
110.2158023.04430.001324
12-0.106822-1.50690.06671
13-0.101535-1.43230.076811
140.0890321.25590.105304
150.0954721.34680.089788
16-0.238256-3.3610.000465
170.2013392.84020.002488
18-0.077224-1.08940.138653
19-0.051408-0.72520.23459
200.0782141.10340.135604
21-0.042127-0.59430.276502
22-0.135624-1.91320.028578
230.282093.97944.8e-05
24-0.221657-3.12690.001016
25-0.066258-0.93470.175544
260.2690783.79589.8e-05
27-0.240868-3.39790.00041
280.0335480.47330.318274
290.1631092.30090.011216
30-0.209427-2.95430.001756
310.0151560.21380.41546
320.2027862.86060.00234
33-0.2511-3.54220.000247
340.0863211.21770.112389
350.1192611.68240.047031
36-0.21885-3.08730.001154
370.1853592.61480.004806
380.0276820.39050.348289
39-0.227302-3.20650.000783
400.195392.75630.003195
410.0367360.51820.30244
42-0.216687-3.05670.001272
430.2177493.07170.001213
44-0.031378-0.44260.329252
45-0.163553-2.30720.011036
460.2791183.93745.7e-05
47-0.104538-1.47470.070939
48-0.180889-2.55170.005735

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.552368 & -7.7921 & 0 \tabularnewline
2 & -0.017685 & -0.2495 & 0.401625 \tabularnewline
3 & 0.298708 & 4.2138 & 1.9e-05 \tabularnewline
4 & -0.244675 & -3.4516 & 0.00034 \tabularnewline
5 & -0.009124 & -0.1287 & 0.44886 \tabularnewline
6 & 0.283852 & 4.0042 & 4.4e-05 \tabularnewline
7 & -0.325748 & -4.5952 & 4e-06 \tabularnewline
8 & 0.161392 & 2.2767 & 0.011934 \tabularnewline
9 & 0.116436 & 1.6425 & 0.05103 \tabularnewline
10 & -0.249599 & -3.521 & 0.000266 \tabularnewline
11 & 0.215802 & 3.0443 & 0.001324 \tabularnewline
12 & -0.106822 & -1.5069 & 0.06671 \tabularnewline
13 & -0.101535 & -1.4323 & 0.076811 \tabularnewline
14 & 0.089032 & 1.2559 & 0.105304 \tabularnewline
15 & 0.095472 & 1.3468 & 0.089788 \tabularnewline
16 & -0.238256 & -3.361 & 0.000465 \tabularnewline
17 & 0.201339 & 2.8402 & 0.002488 \tabularnewline
18 & -0.077224 & -1.0894 & 0.138653 \tabularnewline
19 & -0.051408 & -0.7252 & 0.23459 \tabularnewline
20 & 0.078214 & 1.1034 & 0.135604 \tabularnewline
21 & -0.042127 & -0.5943 & 0.276502 \tabularnewline
22 & -0.135624 & -1.9132 & 0.028578 \tabularnewline
23 & 0.28209 & 3.9794 & 4.8e-05 \tabularnewline
24 & -0.221657 & -3.1269 & 0.001016 \tabularnewline
25 & -0.066258 & -0.9347 & 0.175544 \tabularnewline
26 & 0.269078 & 3.7958 & 9.8e-05 \tabularnewline
27 & -0.240868 & -3.3979 & 0.00041 \tabularnewline
28 & 0.033548 & 0.4733 & 0.318274 \tabularnewline
29 & 0.163109 & 2.3009 & 0.011216 \tabularnewline
30 & -0.209427 & -2.9543 & 0.001756 \tabularnewline
31 & 0.015156 & 0.2138 & 0.41546 \tabularnewline
32 & 0.202786 & 2.8606 & 0.00234 \tabularnewline
33 & -0.2511 & -3.5422 & 0.000247 \tabularnewline
34 & 0.086321 & 1.2177 & 0.112389 \tabularnewline
35 & 0.119261 & 1.6824 & 0.047031 \tabularnewline
36 & -0.21885 & -3.0873 & 0.001154 \tabularnewline
37 & 0.185359 & 2.6148 & 0.004806 \tabularnewline
38 & 0.027682 & 0.3905 & 0.348289 \tabularnewline
39 & -0.227302 & -3.2065 & 0.000783 \tabularnewline
40 & 0.19539 & 2.7563 & 0.003195 \tabularnewline
41 & 0.036736 & 0.5182 & 0.30244 \tabularnewline
42 & -0.216687 & -3.0567 & 0.001272 \tabularnewline
43 & 0.217749 & 3.0717 & 0.001213 \tabularnewline
44 & -0.031378 & -0.4426 & 0.329252 \tabularnewline
45 & -0.163553 & -2.3072 & 0.011036 \tabularnewline
46 & 0.279118 & 3.9374 & 5.7e-05 \tabularnewline
47 & -0.104538 & -1.4747 & 0.070939 \tabularnewline
48 & -0.180889 & -2.5517 & 0.005735 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308682&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]-0.552368[/C][C]-7.7921[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.017685[/C][C]-0.2495[/C][C]0.401625[/C][/ROW]
[ROW][C]3[/C][C]0.298708[/C][C]4.2138[/C][C]1.9e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.244675[/C][C]-3.4516[/C][C]0.00034[/C][/ROW]
[ROW][C]5[/C][C]-0.009124[/C][C]-0.1287[/C][C]0.44886[/C][/ROW]
[ROW][C]6[/C][C]0.283852[/C][C]4.0042[/C][C]4.4e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.325748[/C][C]-4.5952[/C][C]4e-06[/C][/ROW]
[ROW][C]8[/C][C]0.161392[/C][C]2.2767[/C][C]0.011934[/C][/ROW]
[ROW][C]9[/C][C]0.116436[/C][C]1.6425[/C][C]0.05103[/C][/ROW]
[ROW][C]10[/C][C]-0.249599[/C][C]-3.521[/C][C]0.000266[/C][/ROW]
[ROW][C]11[/C][C]0.215802[/C][C]3.0443[/C][C]0.001324[/C][/ROW]
[ROW][C]12[/C][C]-0.106822[/C][C]-1.5069[/C][C]0.06671[/C][/ROW]
[ROW][C]13[/C][C]-0.101535[/C][C]-1.4323[/C][C]0.076811[/C][/ROW]
[ROW][C]14[/C][C]0.089032[/C][C]1.2559[/C][C]0.105304[/C][/ROW]
[ROW][C]15[/C][C]0.095472[/C][C]1.3468[/C][C]0.089788[/C][/ROW]
[ROW][C]16[/C][C]-0.238256[/C][C]-3.361[/C][C]0.000465[/C][/ROW]
[ROW][C]17[/C][C]0.201339[/C][C]2.8402[/C][C]0.002488[/C][/ROW]
[ROW][C]18[/C][C]-0.077224[/C][C]-1.0894[/C][C]0.138653[/C][/ROW]
[ROW][C]19[/C][C]-0.051408[/C][C]-0.7252[/C][C]0.23459[/C][/ROW]
[ROW][C]20[/C][C]0.078214[/C][C]1.1034[/C][C]0.135604[/C][/ROW]
[ROW][C]21[/C][C]-0.042127[/C][C]-0.5943[/C][C]0.276502[/C][/ROW]
[ROW][C]22[/C][C]-0.135624[/C][C]-1.9132[/C][C]0.028578[/C][/ROW]
[ROW][C]23[/C][C]0.28209[/C][C]3.9794[/C][C]4.8e-05[/C][/ROW]
[ROW][C]24[/C][C]-0.221657[/C][C]-3.1269[/C][C]0.001016[/C][/ROW]
[ROW][C]25[/C][C]-0.066258[/C][C]-0.9347[/C][C]0.175544[/C][/ROW]
[ROW][C]26[/C][C]0.269078[/C][C]3.7958[/C][C]9.8e-05[/C][/ROW]
[ROW][C]27[/C][C]-0.240868[/C][C]-3.3979[/C][C]0.00041[/C][/ROW]
[ROW][C]28[/C][C]0.033548[/C][C]0.4733[/C][C]0.318274[/C][/ROW]
[ROW][C]29[/C][C]0.163109[/C][C]2.3009[/C][C]0.011216[/C][/ROW]
[ROW][C]30[/C][C]-0.209427[/C][C]-2.9543[/C][C]0.001756[/C][/ROW]
[ROW][C]31[/C][C]0.015156[/C][C]0.2138[/C][C]0.41546[/C][/ROW]
[ROW][C]32[/C][C]0.202786[/C][C]2.8606[/C][C]0.00234[/C][/ROW]
[ROW][C]33[/C][C]-0.2511[/C][C]-3.5422[/C][C]0.000247[/C][/ROW]
[ROW][C]34[/C][C]0.086321[/C][C]1.2177[/C][C]0.112389[/C][/ROW]
[ROW][C]35[/C][C]0.119261[/C][C]1.6824[/C][C]0.047031[/C][/ROW]
[ROW][C]36[/C][C]-0.21885[/C][C]-3.0873[/C][C]0.001154[/C][/ROW]
[ROW][C]37[/C][C]0.185359[/C][C]2.6148[/C][C]0.004806[/C][/ROW]
[ROW][C]38[/C][C]0.027682[/C][C]0.3905[/C][C]0.348289[/C][/ROW]
[ROW][C]39[/C][C]-0.227302[/C][C]-3.2065[/C][C]0.000783[/C][/ROW]
[ROW][C]40[/C][C]0.19539[/C][C]2.7563[/C][C]0.003195[/C][/ROW]
[ROW][C]41[/C][C]0.036736[/C][C]0.5182[/C][C]0.30244[/C][/ROW]
[ROW][C]42[/C][C]-0.216687[/C][C]-3.0567[/C][C]0.001272[/C][/ROW]
[ROW][C]43[/C][C]0.217749[/C][C]3.0717[/C][C]0.001213[/C][/ROW]
[ROW][C]44[/C][C]-0.031378[/C][C]-0.4426[/C][C]0.329252[/C][/ROW]
[ROW][C]45[/C][C]-0.163553[/C][C]-2.3072[/C][C]0.011036[/C][/ROW]
[ROW][C]46[/C][C]0.279118[/C][C]3.9374[/C][C]5.7e-05[/C][/ROW]
[ROW][C]47[/C][C]-0.104538[/C][C]-1.4747[/C][C]0.070939[/C][/ROW]
[ROW][C]48[/C][C]-0.180889[/C][C]-2.5517[/C][C]0.005735[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308682&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308682&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
1-0.552368-7.79210
2-0.017685-0.24950.401625
30.2987084.21381.9e-05
4-0.244675-3.45160.00034
5-0.009124-0.12870.44886
60.2838524.00424.4e-05
7-0.325748-4.59524e-06
80.1613922.27670.011934
90.1164361.64250.05103
10-0.249599-3.5210.000266
110.2158023.04430.001324
12-0.106822-1.50690.06671
13-0.101535-1.43230.076811
140.0890321.25590.105304
150.0954721.34680.089788
16-0.238256-3.3610.000465
170.2013392.84020.002488
18-0.077224-1.08940.138653
19-0.051408-0.72520.23459
200.0782141.10340.135604
21-0.042127-0.59430.276502
22-0.135624-1.91320.028578
230.282093.97944.8e-05
24-0.221657-3.12690.001016
25-0.066258-0.93470.175544
260.2690783.79589.8e-05
27-0.240868-3.39790.00041
280.0335480.47330.318274
290.1631092.30090.011216
30-0.209427-2.95430.001756
310.0151560.21380.41546
320.2027862.86060.00234
33-0.2511-3.54220.000247
340.0863211.21770.112389
350.1192611.68240.047031
36-0.21885-3.08730.001154
370.1853592.61480.004806
380.0276820.39050.348289
39-0.227302-3.20650.000783
400.195392.75630.003195
410.0367360.51820.30244
42-0.216687-3.05670.001272
430.2177493.07170.001213
44-0.031378-0.44260.329252
45-0.163553-2.30720.011036
460.2791183.93745.7e-05
47-0.104538-1.47470.070939
48-0.180889-2.55170.005735






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.552368-7.79210
2-0.464527-6.5530
30.0510350.71990.236204
40.0194850.27490.391853
5-0.12074-1.70330.045041
60.1947082.74670.003286
7-0.006431-0.09070.463903
80.0339820.47940.316097
90.1384011.95240.026148
100.0101460.14310.443167
110.1016151.43350.076648
12-0.113021-1.59440.056222
13-0.15759-2.22310.013668
14-0.282517-3.98544.7e-05
150.0426260.60130.274156
16-0.068191-0.9620.16862
17-0.04612-0.65060.258027
18-0.00606-0.08550.465982
190.0330660.46650.320699
200.0355830.5020.308126
210.0100540.14180.443678
22-0.150536-2.12360.017471
230.1280981.8070.036133
24-0.020229-0.28540.387832
25-0.252623-3.56370.000229
26-0.112214-1.5830.057508
27-0.009541-0.13460.446537
28-0.021026-0.29660.383535
29-0.011972-0.16890.43303
300.004140.05840.476743
31-0.082245-1.16020.123676
320.0006770.00950.496196
330.0225210.31770.375523
34-0.184647-2.60480.004944
350.0305030.43030.33372
36-0.048983-0.6910.245189
37-0.000946-0.01330.494683
380.0237330.33480.369067
39-0.007283-0.10270.459136
40-0.01592-0.22460.411268
410.0711221.00330.158468
42-0.027484-0.38770.349321
43-0.100968-1.42430.077959
440.0371830.52450.300248
45-0.069263-0.97710.16486
46-0.000997-0.01410.494396
470.2003422.82620.002596
48-0.042925-0.60550.272759

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.552368 & -7.7921 & 0 \tabularnewline
2 & -0.464527 & -6.553 & 0 \tabularnewline
3 & 0.051035 & 0.7199 & 0.236204 \tabularnewline
4 & 0.019485 & 0.2749 & 0.391853 \tabularnewline
5 & -0.12074 & -1.7033 & 0.045041 \tabularnewline
6 & 0.194708 & 2.7467 & 0.003286 \tabularnewline
7 & -0.006431 & -0.0907 & 0.463903 \tabularnewline
8 & 0.033982 & 0.4794 & 0.316097 \tabularnewline
9 & 0.138401 & 1.9524 & 0.026148 \tabularnewline
10 & 0.010146 & 0.1431 & 0.443167 \tabularnewline
11 & 0.101615 & 1.4335 & 0.076648 \tabularnewline
12 & -0.113021 & -1.5944 & 0.056222 \tabularnewline
13 & -0.15759 & -2.2231 & 0.013668 \tabularnewline
14 & -0.282517 & -3.9854 & 4.7e-05 \tabularnewline
15 & 0.042626 & 0.6013 & 0.274156 \tabularnewline
16 & -0.068191 & -0.962 & 0.16862 \tabularnewline
17 & -0.04612 & -0.6506 & 0.258027 \tabularnewline
18 & -0.00606 & -0.0855 & 0.465982 \tabularnewline
19 & 0.033066 & 0.4665 & 0.320699 \tabularnewline
20 & 0.035583 & 0.502 & 0.308126 \tabularnewline
21 & 0.010054 & 0.1418 & 0.443678 \tabularnewline
22 & -0.150536 & -2.1236 & 0.017471 \tabularnewline
23 & 0.128098 & 1.807 & 0.036133 \tabularnewline
24 & -0.020229 & -0.2854 & 0.387832 \tabularnewline
25 & -0.252623 & -3.5637 & 0.000229 \tabularnewline
26 & -0.112214 & -1.583 & 0.057508 \tabularnewline
27 & -0.009541 & -0.1346 & 0.446537 \tabularnewline
28 & -0.021026 & -0.2966 & 0.383535 \tabularnewline
29 & -0.011972 & -0.1689 & 0.43303 \tabularnewline
30 & 0.00414 & 0.0584 & 0.476743 \tabularnewline
31 & -0.082245 & -1.1602 & 0.123676 \tabularnewline
32 & 0.000677 & 0.0095 & 0.496196 \tabularnewline
33 & 0.022521 & 0.3177 & 0.375523 \tabularnewline
34 & -0.184647 & -2.6048 & 0.004944 \tabularnewline
35 & 0.030503 & 0.4303 & 0.33372 \tabularnewline
36 & -0.048983 & -0.691 & 0.245189 \tabularnewline
37 & -0.000946 & -0.0133 & 0.494683 \tabularnewline
38 & 0.023733 & 0.3348 & 0.369067 \tabularnewline
39 & -0.007283 & -0.1027 & 0.459136 \tabularnewline
40 & -0.01592 & -0.2246 & 0.411268 \tabularnewline
41 & 0.071122 & 1.0033 & 0.158468 \tabularnewline
42 & -0.027484 & -0.3877 & 0.349321 \tabularnewline
43 & -0.100968 & -1.4243 & 0.077959 \tabularnewline
44 & 0.037183 & 0.5245 & 0.300248 \tabularnewline
45 & -0.069263 & -0.9771 & 0.16486 \tabularnewline
46 & -0.000997 & -0.0141 & 0.494396 \tabularnewline
47 & 0.200342 & 2.8262 & 0.002596 \tabularnewline
48 & -0.042925 & -0.6055 & 0.272759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308682&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]-0.552368[/C][C]-7.7921[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.464527[/C][C]-6.553[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.051035[/C][C]0.7199[/C][C]0.236204[/C][/ROW]
[ROW][C]4[/C][C]0.019485[/C][C]0.2749[/C][C]0.391853[/C][/ROW]
[ROW][C]5[/C][C]-0.12074[/C][C]-1.7033[/C][C]0.045041[/C][/ROW]
[ROW][C]6[/C][C]0.194708[/C][C]2.7467[/C][C]0.003286[/C][/ROW]
[ROW][C]7[/C][C]-0.006431[/C][C]-0.0907[/C][C]0.463903[/C][/ROW]
[ROW][C]8[/C][C]0.033982[/C][C]0.4794[/C][C]0.316097[/C][/ROW]
[ROW][C]9[/C][C]0.138401[/C][C]1.9524[/C][C]0.026148[/C][/ROW]
[ROW][C]10[/C][C]0.010146[/C][C]0.1431[/C][C]0.443167[/C][/ROW]
[ROW][C]11[/C][C]0.101615[/C][C]1.4335[/C][C]0.076648[/C][/ROW]
[ROW][C]12[/C][C]-0.113021[/C][C]-1.5944[/C][C]0.056222[/C][/ROW]
[ROW][C]13[/C][C]-0.15759[/C][C]-2.2231[/C][C]0.013668[/C][/ROW]
[ROW][C]14[/C][C]-0.282517[/C][C]-3.9854[/C][C]4.7e-05[/C][/ROW]
[ROW][C]15[/C][C]0.042626[/C][C]0.6013[/C][C]0.274156[/C][/ROW]
[ROW][C]16[/C][C]-0.068191[/C][C]-0.962[/C][C]0.16862[/C][/ROW]
[ROW][C]17[/C][C]-0.04612[/C][C]-0.6506[/C][C]0.258027[/C][/ROW]
[ROW][C]18[/C][C]-0.00606[/C][C]-0.0855[/C][C]0.465982[/C][/ROW]
[ROW][C]19[/C][C]0.033066[/C][C]0.4665[/C][C]0.320699[/C][/ROW]
[ROW][C]20[/C][C]0.035583[/C][C]0.502[/C][C]0.308126[/C][/ROW]
[ROW][C]21[/C][C]0.010054[/C][C]0.1418[/C][C]0.443678[/C][/ROW]
[ROW][C]22[/C][C]-0.150536[/C][C]-2.1236[/C][C]0.017471[/C][/ROW]
[ROW][C]23[/C][C]0.128098[/C][C]1.807[/C][C]0.036133[/C][/ROW]
[ROW][C]24[/C][C]-0.020229[/C][C]-0.2854[/C][C]0.387832[/C][/ROW]
[ROW][C]25[/C][C]-0.252623[/C][C]-3.5637[/C][C]0.000229[/C][/ROW]
[ROW][C]26[/C][C]-0.112214[/C][C]-1.583[/C][C]0.057508[/C][/ROW]
[ROW][C]27[/C][C]-0.009541[/C][C]-0.1346[/C][C]0.446537[/C][/ROW]
[ROW][C]28[/C][C]-0.021026[/C][C]-0.2966[/C][C]0.383535[/C][/ROW]
[ROW][C]29[/C][C]-0.011972[/C][C]-0.1689[/C][C]0.43303[/C][/ROW]
[ROW][C]30[/C][C]0.00414[/C][C]0.0584[/C][C]0.476743[/C][/ROW]
[ROW][C]31[/C][C]-0.082245[/C][C]-1.1602[/C][C]0.123676[/C][/ROW]
[ROW][C]32[/C][C]0.000677[/C][C]0.0095[/C][C]0.496196[/C][/ROW]
[ROW][C]33[/C][C]0.022521[/C][C]0.3177[/C][C]0.375523[/C][/ROW]
[ROW][C]34[/C][C]-0.184647[/C][C]-2.6048[/C][C]0.004944[/C][/ROW]
[ROW][C]35[/C][C]0.030503[/C][C]0.4303[/C][C]0.33372[/C][/ROW]
[ROW][C]36[/C][C]-0.048983[/C][C]-0.691[/C][C]0.245189[/C][/ROW]
[ROW][C]37[/C][C]-0.000946[/C][C]-0.0133[/C][C]0.494683[/C][/ROW]
[ROW][C]38[/C][C]0.023733[/C][C]0.3348[/C][C]0.369067[/C][/ROW]
[ROW][C]39[/C][C]-0.007283[/C][C]-0.1027[/C][C]0.459136[/C][/ROW]
[ROW][C]40[/C][C]-0.01592[/C][C]-0.2246[/C][C]0.411268[/C][/ROW]
[ROW][C]41[/C][C]0.071122[/C][C]1.0033[/C][C]0.158468[/C][/ROW]
[ROW][C]42[/C][C]-0.027484[/C][C]-0.3877[/C][C]0.349321[/C][/ROW]
[ROW][C]43[/C][C]-0.100968[/C][C]-1.4243[/C][C]0.077959[/C][/ROW]
[ROW][C]44[/C][C]0.037183[/C][C]0.5245[/C][C]0.300248[/C][/ROW]
[ROW][C]45[/C][C]-0.069263[/C][C]-0.9771[/C][C]0.16486[/C][/ROW]
[ROW][C]46[/C][C]-0.000997[/C][C]-0.0141[/C][C]0.494396[/C][/ROW]
[ROW][C]47[/C][C]0.200342[/C][C]2.8262[/C][C]0.002596[/C][/ROW]
[ROW][C]48[/C][C]-0.042925[/C][C]-0.6055[/C][C]0.272759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308682&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308682&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
1-0.552368-7.79210
2-0.464527-6.5530
30.0510350.71990.236204
40.0194850.27490.391853
5-0.12074-1.70330.045041
60.1947082.74670.003286
7-0.006431-0.09070.463903
80.0339820.47940.316097
90.1384011.95240.026148
100.0101460.14310.443167
110.1016151.43350.076648
12-0.113021-1.59440.056222
13-0.15759-2.22310.013668
14-0.282517-3.98544.7e-05
150.0426260.60130.274156
16-0.068191-0.9620.16862
17-0.04612-0.65060.258027
18-0.00606-0.08550.465982
190.0330660.46650.320699
200.0355830.5020.308126
210.0100540.14180.443678
22-0.150536-2.12360.017471
230.1280981.8070.036133
24-0.020229-0.28540.387832
25-0.252623-3.56370.000229
26-0.112214-1.5830.057508
27-0.009541-0.13460.446537
28-0.021026-0.29660.383535
29-0.011972-0.16890.43303
300.004140.05840.476743
31-0.082245-1.16020.123676
320.0006770.00950.496196
330.0225210.31770.375523
34-0.184647-2.60480.004944
350.0305030.43030.33372
36-0.048983-0.6910.245189
37-0.000946-0.01330.494683
380.0237330.33480.369067
39-0.007283-0.10270.459136
40-0.01592-0.22460.411268
410.0711221.00330.158468
42-0.027484-0.38770.349321
43-0.100968-1.42430.077959
440.0371830.52450.300248
45-0.069263-0.97710.16486
46-0.000997-0.01410.494396
470.2003422.82620.002596
48-0.042925-0.60550.272759


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')