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Author's title

Paper: autocorrelation werkloosheid 31/01/2002 - 31/12/2007 met d en D = 1 ...

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 05 Dec 2008 06:14:10 -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/2008/Dec/05/t1228483800utt44bpvwvufltg.htm/, Retrieved Thu, 16 May 2024 09:29:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29246, Retrieved Thu, 16 May 2024 09:29:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact222
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [Paper: autocorrel...] [2008-12-05 10:20:24] [27f46dbe13ae2811dfd3a6f3c54d4d50]
-   P     [(Partial) Autocorrelation Function] [Paper: autocorrel...] [2008-12-05 13:14:10] [d41d8cd98f00b204e9800998ecf8427e] [Current]
F RMP       [ARIMA Backward Selection] [Paper ARIMA-model...] [2008-12-08 21:09:11] [27f46dbe13ae2811dfd3a6f3c54d4d50]
-   P         [ARIMA Backward Selection] [arma beoordeling ...] [2008-12-16 06:56:59] [090686c1af2bb318059a6f656863a319]
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Dataseries X:
95.20
95.00
94.00
92.20
91.00
91.20
103.40
105.00
104.60
103.80
101.80
102.40
103.80
103.40
102.00
101.80
100.20
101.40
113.80
116.00
115.60
113.00
109.40
111.00
112.40
112.20
111.00
108.80
107.40
108.60
118.80
122.20
122.60
122.20
118.80
119.00
118.20
117.80
116.80
114.60
113.40
113.80
124.20
125.80
125.60
122.40
119.00
119.40
118.60
118.00
116.00
114.80
114.60
114.60
124.00
125.20
124.00
117.60
113.20
111.40
112.20
109.80
106.40
105.20
102.20
99.80
111.00
113.00
108.40
105.40
102.00
102.80




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=29246&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=29246&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29246&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
10.0475790.36550.358038
20.0983050.75510.226597
3-0.054299-0.41710.339068
4-0.051074-0.39230.348121
5-0.072491-0.55680.28988
6-0.059142-0.45430.325648
7-0.012719-0.09770.461251
80.0018390.01410.49439
90.1801531.38380.085819
10-0.158128-1.21460.114677
110.0262030.20130.42059
12-0.269393-2.06920.021456
13-0.088676-0.68110.249226
140.1085190.83350.203948
15-0.008608-0.06610.473752
160.0245590.18860.42551
17-0.100869-0.77480.220779
180.15271.17290.122772
190.065810.50550.307547
200.0761880.58520.280319
210.0132750.1020.459563
220.0131790.10120.459856
230.1399311.07480.143414
24-0.145774-1.11970.133687
25-0.097161-0.74630.229223
26-0.262285-2.01470.024253
270.0418920.32180.37438
28-0.075254-0.5780.28272
290.1146180.88040.191108
30-0.08963-0.68850.24693
31-0.065636-0.50420.308013
320.0388920.29870.383096
33-0.09087-0.6980.243965
34-0.017855-0.13710.44569
35-0.032802-0.2520.400975
360.0503170.38650.350262
370.0939240.72140.236743
380.1345781.03370.152745
39-0.113019-0.86810.194425
40-0.017193-0.13210.447691
41-0.011348-0.08720.465417
42-0.096518-0.74140.230704
430.0471890.36250.359148
44-0.061038-0.46880.320456
45-0.026289-0.20190.420332
460.0222210.17070.432529
47-0.032091-0.24650.403078
48-0.042965-0.330.371276
49-0.080695-0.61980.268879
50-0.04927-0.37840.353228
510.0541090.41560.339597
520.1005080.7720.221592
530.0037990.02920.488409
540.0865770.6650.254316
550.0097130.07460.470389
560.0377770.29020.386351
57-0.002909-0.02230.491125
580.0016470.01270.494974
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.047579 & 0.3655 & 0.358038 \tabularnewline
2 & 0.098305 & 0.7551 & 0.226597 \tabularnewline
3 & -0.054299 & -0.4171 & 0.339068 \tabularnewline
4 & -0.051074 & -0.3923 & 0.348121 \tabularnewline
5 & -0.072491 & -0.5568 & 0.28988 \tabularnewline
6 & -0.059142 & -0.4543 & 0.325648 \tabularnewline
7 & -0.012719 & -0.0977 & 0.461251 \tabularnewline
8 & 0.001839 & 0.0141 & 0.49439 \tabularnewline
9 & 0.180153 & 1.3838 & 0.085819 \tabularnewline
10 & -0.158128 & -1.2146 & 0.114677 \tabularnewline
11 & 0.026203 & 0.2013 & 0.42059 \tabularnewline
12 & -0.269393 & -2.0692 & 0.021456 \tabularnewline
13 & -0.088676 & -0.6811 & 0.249226 \tabularnewline
14 & 0.108519 & 0.8335 & 0.203948 \tabularnewline
15 & -0.008608 & -0.0661 & 0.473752 \tabularnewline
16 & 0.024559 & 0.1886 & 0.42551 \tabularnewline
17 & -0.100869 & -0.7748 & 0.220779 \tabularnewline
18 & 0.1527 & 1.1729 & 0.122772 \tabularnewline
19 & 0.06581 & 0.5055 & 0.307547 \tabularnewline
20 & 0.076188 & 0.5852 & 0.280319 \tabularnewline
21 & 0.013275 & 0.102 & 0.459563 \tabularnewline
22 & 0.013179 & 0.1012 & 0.459856 \tabularnewline
23 & 0.139931 & 1.0748 & 0.143414 \tabularnewline
24 & -0.145774 & -1.1197 & 0.133687 \tabularnewline
25 & -0.097161 & -0.7463 & 0.229223 \tabularnewline
26 & -0.262285 & -2.0147 & 0.024253 \tabularnewline
27 & 0.041892 & 0.3218 & 0.37438 \tabularnewline
28 & -0.075254 & -0.578 & 0.28272 \tabularnewline
29 & 0.114618 & 0.8804 & 0.191108 \tabularnewline
30 & -0.08963 & -0.6885 & 0.24693 \tabularnewline
31 & -0.065636 & -0.5042 & 0.308013 \tabularnewline
32 & 0.038892 & 0.2987 & 0.383096 \tabularnewline
33 & -0.09087 & -0.698 & 0.243965 \tabularnewline
34 & -0.017855 & -0.1371 & 0.44569 \tabularnewline
35 & -0.032802 & -0.252 & 0.400975 \tabularnewline
36 & 0.050317 & 0.3865 & 0.350262 \tabularnewline
37 & 0.093924 & 0.7214 & 0.236743 \tabularnewline
38 & 0.134578 & 1.0337 & 0.152745 \tabularnewline
39 & -0.113019 & -0.8681 & 0.194425 \tabularnewline
40 & -0.017193 & -0.1321 & 0.447691 \tabularnewline
41 & -0.011348 & -0.0872 & 0.465417 \tabularnewline
42 & -0.096518 & -0.7414 & 0.230704 \tabularnewline
43 & 0.047189 & 0.3625 & 0.359148 \tabularnewline
44 & -0.061038 & -0.4688 & 0.320456 \tabularnewline
45 & -0.026289 & -0.2019 & 0.420332 \tabularnewline
46 & 0.022221 & 0.1707 & 0.432529 \tabularnewline
47 & -0.032091 & -0.2465 & 0.403078 \tabularnewline
48 & -0.042965 & -0.33 & 0.371276 \tabularnewline
49 & -0.080695 & -0.6198 & 0.268879 \tabularnewline
50 & -0.04927 & -0.3784 & 0.353228 \tabularnewline
51 & 0.054109 & 0.4156 & 0.339597 \tabularnewline
52 & 0.100508 & 0.772 & 0.221592 \tabularnewline
53 & 0.003799 & 0.0292 & 0.488409 \tabularnewline
54 & 0.086577 & 0.665 & 0.254316 \tabularnewline
55 & 0.009713 & 0.0746 & 0.470389 \tabularnewline
56 & 0.037777 & 0.2902 & 0.386351 \tabularnewline
57 & -0.002909 & -0.0223 & 0.491125 \tabularnewline
58 & 0.001647 & 0.0127 & 0.494974 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29246&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]0.047579[/C][C]0.3655[/C][C]0.358038[/C][/ROW]
[ROW][C]2[/C][C]0.098305[/C][C]0.7551[/C][C]0.226597[/C][/ROW]
[ROW][C]3[/C][C]-0.054299[/C][C]-0.4171[/C][C]0.339068[/C][/ROW]
[ROW][C]4[/C][C]-0.051074[/C][C]-0.3923[/C][C]0.348121[/C][/ROW]
[ROW][C]5[/C][C]-0.072491[/C][C]-0.5568[/C][C]0.28988[/C][/ROW]
[ROW][C]6[/C][C]-0.059142[/C][C]-0.4543[/C][C]0.325648[/C][/ROW]
[ROW][C]7[/C][C]-0.012719[/C][C]-0.0977[/C][C]0.461251[/C][/ROW]
[ROW][C]8[/C][C]0.001839[/C][C]0.0141[/C][C]0.49439[/C][/ROW]
[ROW][C]9[/C][C]0.180153[/C][C]1.3838[/C][C]0.085819[/C][/ROW]
[ROW][C]10[/C][C]-0.158128[/C][C]-1.2146[/C][C]0.114677[/C][/ROW]
[ROW][C]11[/C][C]0.026203[/C][C]0.2013[/C][C]0.42059[/C][/ROW]
[ROW][C]12[/C][C]-0.269393[/C][C]-2.0692[/C][C]0.021456[/C][/ROW]
[ROW][C]13[/C][C]-0.088676[/C][C]-0.6811[/C][C]0.249226[/C][/ROW]
[ROW][C]14[/C][C]0.108519[/C][C]0.8335[/C][C]0.203948[/C][/ROW]
[ROW][C]15[/C][C]-0.008608[/C][C]-0.0661[/C][C]0.473752[/C][/ROW]
[ROW][C]16[/C][C]0.024559[/C][C]0.1886[/C][C]0.42551[/C][/ROW]
[ROW][C]17[/C][C]-0.100869[/C][C]-0.7748[/C][C]0.220779[/C][/ROW]
[ROW][C]18[/C][C]0.1527[/C][C]1.1729[/C][C]0.122772[/C][/ROW]
[ROW][C]19[/C][C]0.06581[/C][C]0.5055[/C][C]0.307547[/C][/ROW]
[ROW][C]20[/C][C]0.076188[/C][C]0.5852[/C][C]0.280319[/C][/ROW]
[ROW][C]21[/C][C]0.013275[/C][C]0.102[/C][C]0.459563[/C][/ROW]
[ROW][C]22[/C][C]0.013179[/C][C]0.1012[/C][C]0.459856[/C][/ROW]
[ROW][C]23[/C][C]0.139931[/C][C]1.0748[/C][C]0.143414[/C][/ROW]
[ROW][C]24[/C][C]-0.145774[/C][C]-1.1197[/C][C]0.133687[/C][/ROW]
[ROW][C]25[/C][C]-0.097161[/C][C]-0.7463[/C][C]0.229223[/C][/ROW]
[ROW][C]26[/C][C]-0.262285[/C][C]-2.0147[/C][C]0.024253[/C][/ROW]
[ROW][C]27[/C][C]0.041892[/C][C]0.3218[/C][C]0.37438[/C][/ROW]
[ROW][C]28[/C][C]-0.075254[/C][C]-0.578[/C][C]0.28272[/C][/ROW]
[ROW][C]29[/C][C]0.114618[/C][C]0.8804[/C][C]0.191108[/C][/ROW]
[ROW][C]30[/C][C]-0.08963[/C][C]-0.6885[/C][C]0.24693[/C][/ROW]
[ROW][C]31[/C][C]-0.065636[/C][C]-0.5042[/C][C]0.308013[/C][/ROW]
[ROW][C]32[/C][C]0.038892[/C][C]0.2987[/C][C]0.383096[/C][/ROW]
[ROW][C]33[/C][C]-0.09087[/C][C]-0.698[/C][C]0.243965[/C][/ROW]
[ROW][C]34[/C][C]-0.017855[/C][C]-0.1371[/C][C]0.44569[/C][/ROW]
[ROW][C]35[/C][C]-0.032802[/C][C]-0.252[/C][C]0.400975[/C][/ROW]
[ROW][C]36[/C][C]0.050317[/C][C]0.3865[/C][C]0.350262[/C][/ROW]
[ROW][C]37[/C][C]0.093924[/C][C]0.7214[/C][C]0.236743[/C][/ROW]
[ROW][C]38[/C][C]0.134578[/C][C]1.0337[/C][C]0.152745[/C][/ROW]
[ROW][C]39[/C][C]-0.113019[/C][C]-0.8681[/C][C]0.194425[/C][/ROW]
[ROW][C]40[/C][C]-0.017193[/C][C]-0.1321[/C][C]0.447691[/C][/ROW]
[ROW][C]41[/C][C]-0.011348[/C][C]-0.0872[/C][C]0.465417[/C][/ROW]
[ROW][C]42[/C][C]-0.096518[/C][C]-0.7414[/C][C]0.230704[/C][/ROW]
[ROW][C]43[/C][C]0.047189[/C][C]0.3625[/C][C]0.359148[/C][/ROW]
[ROW][C]44[/C][C]-0.061038[/C][C]-0.4688[/C][C]0.320456[/C][/ROW]
[ROW][C]45[/C][C]-0.026289[/C][C]-0.2019[/C][C]0.420332[/C][/ROW]
[ROW][C]46[/C][C]0.022221[/C][C]0.1707[/C][C]0.432529[/C][/ROW]
[ROW][C]47[/C][C]-0.032091[/C][C]-0.2465[/C][C]0.403078[/C][/ROW]
[ROW][C]48[/C][C]-0.042965[/C][C]-0.33[/C][C]0.371276[/C][/ROW]
[ROW][C]49[/C][C]-0.080695[/C][C]-0.6198[/C][C]0.268879[/C][/ROW]
[ROW][C]50[/C][C]-0.04927[/C][C]-0.3784[/C][C]0.353228[/C][/ROW]
[ROW][C]51[/C][C]0.054109[/C][C]0.4156[/C][C]0.339597[/C][/ROW]
[ROW][C]52[/C][C]0.100508[/C][C]0.772[/C][C]0.221592[/C][/ROW]
[ROW][C]53[/C][C]0.003799[/C][C]0.0292[/C][C]0.488409[/C][/ROW]
[ROW][C]54[/C][C]0.086577[/C][C]0.665[/C][C]0.254316[/C][/ROW]
[ROW][C]55[/C][C]0.009713[/C][C]0.0746[/C][C]0.470389[/C][/ROW]
[ROW][C]56[/C][C]0.037777[/C][C]0.2902[/C][C]0.386351[/C][/ROW]
[ROW][C]57[/C][C]-0.002909[/C][C]-0.0223[/C][C]0.491125[/C][/ROW]
[ROW][C]58[/C][C]0.001647[/C][C]0.0127[/C][C]0.494974[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29246&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29246&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
10.0475790.36550.358038
20.0983050.75510.226597
3-0.054299-0.41710.339068
4-0.051074-0.39230.348121
5-0.072491-0.55680.28988
6-0.059142-0.45430.325648
7-0.012719-0.09770.461251
80.0018390.01410.49439
90.1801531.38380.085819
10-0.158128-1.21460.114677
110.0262030.20130.42059
12-0.269393-2.06920.021456
13-0.088676-0.68110.249226
140.1085190.83350.203948
15-0.008608-0.06610.473752
160.0245590.18860.42551
17-0.100869-0.77480.220779
180.15271.17290.122772
190.065810.50550.307547
200.0761880.58520.280319
210.0132750.1020.459563
220.0131790.10120.459856
230.1399311.07480.143414
24-0.145774-1.11970.133687
25-0.097161-0.74630.229223
26-0.262285-2.01470.024253
270.0418920.32180.37438
28-0.075254-0.5780.28272
290.1146180.88040.191108
30-0.08963-0.68850.24693
31-0.065636-0.50420.308013
320.0388920.29870.383096
33-0.09087-0.6980.243965
34-0.017855-0.13710.44569
35-0.032802-0.2520.400975
360.0503170.38650.350262
370.0939240.72140.236743
380.1345781.03370.152745
39-0.113019-0.86810.194425
40-0.017193-0.13210.447691
41-0.011348-0.08720.465417
42-0.096518-0.74140.230704
430.0471890.36250.359148
44-0.061038-0.46880.320456
45-0.026289-0.20190.420332
460.0222210.17070.432529
47-0.032091-0.24650.403078
48-0.042965-0.330.371276
49-0.080695-0.61980.268879
50-0.04927-0.37840.353228
510.0541090.41560.339597
520.1005080.7720.221592
530.0037990.02920.488409
540.0865770.6650.254316
550.0097130.07460.470389
560.0377770.29020.386351
57-0.002909-0.02230.491125
580.0016470.01270.494974
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0475790.36550.358038
20.096260.73940.231303
3-0.06384-0.49040.312846
4-0.055971-0.42990.33441
5-0.056878-0.43690.331894
6-0.046972-0.36080.359771
7-0.001213-0.00930.496297
80.0032670.02510.490034
90.1731831.33020.094278
10-0.19269-1.48010.072086
110.0041590.03190.487311
12-0.243798-1.87270.033037
13-0.067303-0.5170.303558
140.1935061.48630.071256
15-0.040734-0.31290.377736
16-0.031929-0.24530.403557
17-0.166986-1.28260.102317
180.1344221.03250.153022
190.1629261.25150.107854
200.0097810.07510.470184
210.1142980.87790.191769
22-0.121804-0.93560.176649
230.1251310.96110.1702
24-0.186631-1.43350.078492
25-0.145155-1.1150.134695
26-0.102182-0.78490.217833
270.0038710.02970.48819
28-0.01817-0.13960.444737
290.0007430.00570.497733
30-0.108281-0.83170.20446
310.0075470.0580.476986
320.0035570.02730.489146
330.0267520.20550.418951
34-0.076035-0.5840.280711
350.1172750.90080.185678
36-0.087434-0.67160.252233
37-0.00567-0.04360.482704
38-0.023231-0.17840.429495
39-0.133964-1.0290.15384
400.0533420.40970.341746
41-0.090164-0.69260.24565
42-0.124867-0.95910.170707
430.0164850.12660.449833
44-0.002117-0.01630.493542
450.0605520.46510.321783
46-0.079866-0.61350.270965
470.0234370.180.428876
480.0002440.00190.499256
49-0.076813-0.590.278717
50-0.079822-0.61310.271075
51-0.013634-0.10470.458476
520.0173670.13340.447166
530.0745180.57240.284618
54-0.036967-0.28390.388723
55-0.038235-0.29370.385014
56-0.049229-0.37810.353344
570.0346880.26640.395412
580.0096410.07410.47061
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.047579 & 0.3655 & 0.358038 \tabularnewline
2 & 0.09626 & 0.7394 & 0.231303 \tabularnewline
3 & -0.06384 & -0.4904 & 0.312846 \tabularnewline
4 & -0.055971 & -0.4299 & 0.33441 \tabularnewline
5 & -0.056878 & -0.4369 & 0.331894 \tabularnewline
6 & -0.046972 & -0.3608 & 0.359771 \tabularnewline
7 & -0.001213 & -0.0093 & 0.496297 \tabularnewline
8 & 0.003267 & 0.0251 & 0.490034 \tabularnewline
9 & 0.173183 & 1.3302 & 0.094278 \tabularnewline
10 & -0.19269 & -1.4801 & 0.072086 \tabularnewline
11 & 0.004159 & 0.0319 & 0.487311 \tabularnewline
12 & -0.243798 & -1.8727 & 0.033037 \tabularnewline
13 & -0.067303 & -0.517 & 0.303558 \tabularnewline
14 & 0.193506 & 1.4863 & 0.071256 \tabularnewline
15 & -0.040734 & -0.3129 & 0.377736 \tabularnewline
16 & -0.031929 & -0.2453 & 0.403557 \tabularnewline
17 & -0.166986 & -1.2826 & 0.102317 \tabularnewline
18 & 0.134422 & 1.0325 & 0.153022 \tabularnewline
19 & 0.162926 & 1.2515 & 0.107854 \tabularnewline
20 & 0.009781 & 0.0751 & 0.470184 \tabularnewline
21 & 0.114298 & 0.8779 & 0.191769 \tabularnewline
22 & -0.121804 & -0.9356 & 0.176649 \tabularnewline
23 & 0.125131 & 0.9611 & 0.1702 \tabularnewline
24 & -0.186631 & -1.4335 & 0.078492 \tabularnewline
25 & -0.145155 & -1.115 & 0.134695 \tabularnewline
26 & -0.102182 & -0.7849 & 0.217833 \tabularnewline
27 & 0.003871 & 0.0297 & 0.48819 \tabularnewline
28 & -0.01817 & -0.1396 & 0.444737 \tabularnewline
29 & 0.000743 & 0.0057 & 0.497733 \tabularnewline
30 & -0.108281 & -0.8317 & 0.20446 \tabularnewline
31 & 0.007547 & 0.058 & 0.476986 \tabularnewline
32 & 0.003557 & 0.0273 & 0.489146 \tabularnewline
33 & 0.026752 & 0.2055 & 0.418951 \tabularnewline
34 & -0.076035 & -0.584 & 0.280711 \tabularnewline
35 & 0.117275 & 0.9008 & 0.185678 \tabularnewline
36 & -0.087434 & -0.6716 & 0.252233 \tabularnewline
37 & -0.00567 & -0.0436 & 0.482704 \tabularnewline
38 & -0.023231 & -0.1784 & 0.429495 \tabularnewline
39 & -0.133964 & -1.029 & 0.15384 \tabularnewline
40 & 0.053342 & 0.4097 & 0.341746 \tabularnewline
41 & -0.090164 & -0.6926 & 0.24565 \tabularnewline
42 & -0.124867 & -0.9591 & 0.170707 \tabularnewline
43 & 0.016485 & 0.1266 & 0.449833 \tabularnewline
44 & -0.002117 & -0.0163 & 0.493542 \tabularnewline
45 & 0.060552 & 0.4651 & 0.321783 \tabularnewline
46 & -0.079866 & -0.6135 & 0.270965 \tabularnewline
47 & 0.023437 & 0.18 & 0.428876 \tabularnewline
48 & 0.000244 & 0.0019 & 0.499256 \tabularnewline
49 & -0.076813 & -0.59 & 0.278717 \tabularnewline
50 & -0.079822 & -0.6131 & 0.271075 \tabularnewline
51 & -0.013634 & -0.1047 & 0.458476 \tabularnewline
52 & 0.017367 & 0.1334 & 0.447166 \tabularnewline
53 & 0.074518 & 0.5724 & 0.284618 \tabularnewline
54 & -0.036967 & -0.2839 & 0.388723 \tabularnewline
55 & -0.038235 & -0.2937 & 0.385014 \tabularnewline
56 & -0.049229 & -0.3781 & 0.353344 \tabularnewline
57 & 0.034688 & 0.2664 & 0.395412 \tabularnewline
58 & 0.009641 & 0.0741 & 0.47061 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29246&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]0.047579[/C][C]0.3655[/C][C]0.358038[/C][/ROW]
[ROW][C]2[/C][C]0.09626[/C][C]0.7394[/C][C]0.231303[/C][/ROW]
[ROW][C]3[/C][C]-0.06384[/C][C]-0.4904[/C][C]0.312846[/C][/ROW]
[ROW][C]4[/C][C]-0.055971[/C][C]-0.4299[/C][C]0.33441[/C][/ROW]
[ROW][C]5[/C][C]-0.056878[/C][C]-0.4369[/C][C]0.331894[/C][/ROW]
[ROW][C]6[/C][C]-0.046972[/C][C]-0.3608[/C][C]0.359771[/C][/ROW]
[ROW][C]7[/C][C]-0.001213[/C][C]-0.0093[/C][C]0.496297[/C][/ROW]
[ROW][C]8[/C][C]0.003267[/C][C]0.0251[/C][C]0.490034[/C][/ROW]
[ROW][C]9[/C][C]0.173183[/C][C]1.3302[/C][C]0.094278[/C][/ROW]
[ROW][C]10[/C][C]-0.19269[/C][C]-1.4801[/C][C]0.072086[/C][/ROW]
[ROW][C]11[/C][C]0.004159[/C][C]0.0319[/C][C]0.487311[/C][/ROW]
[ROW][C]12[/C][C]-0.243798[/C][C]-1.8727[/C][C]0.033037[/C][/ROW]
[ROW][C]13[/C][C]-0.067303[/C][C]-0.517[/C][C]0.303558[/C][/ROW]
[ROW][C]14[/C][C]0.193506[/C][C]1.4863[/C][C]0.071256[/C][/ROW]
[ROW][C]15[/C][C]-0.040734[/C][C]-0.3129[/C][C]0.377736[/C][/ROW]
[ROW][C]16[/C][C]-0.031929[/C][C]-0.2453[/C][C]0.403557[/C][/ROW]
[ROW][C]17[/C][C]-0.166986[/C][C]-1.2826[/C][C]0.102317[/C][/ROW]
[ROW][C]18[/C][C]0.134422[/C][C]1.0325[/C][C]0.153022[/C][/ROW]
[ROW][C]19[/C][C]0.162926[/C][C]1.2515[/C][C]0.107854[/C][/ROW]
[ROW][C]20[/C][C]0.009781[/C][C]0.0751[/C][C]0.470184[/C][/ROW]
[ROW][C]21[/C][C]0.114298[/C][C]0.8779[/C][C]0.191769[/C][/ROW]
[ROW][C]22[/C][C]-0.121804[/C][C]-0.9356[/C][C]0.176649[/C][/ROW]
[ROW][C]23[/C][C]0.125131[/C][C]0.9611[/C][C]0.1702[/C][/ROW]
[ROW][C]24[/C][C]-0.186631[/C][C]-1.4335[/C][C]0.078492[/C][/ROW]
[ROW][C]25[/C][C]-0.145155[/C][C]-1.115[/C][C]0.134695[/C][/ROW]
[ROW][C]26[/C][C]-0.102182[/C][C]-0.7849[/C][C]0.217833[/C][/ROW]
[ROW][C]27[/C][C]0.003871[/C][C]0.0297[/C][C]0.48819[/C][/ROW]
[ROW][C]28[/C][C]-0.01817[/C][C]-0.1396[/C][C]0.444737[/C][/ROW]
[ROW][C]29[/C][C]0.000743[/C][C]0.0057[/C][C]0.497733[/C][/ROW]
[ROW][C]30[/C][C]-0.108281[/C][C]-0.8317[/C][C]0.20446[/C][/ROW]
[ROW][C]31[/C][C]0.007547[/C][C]0.058[/C][C]0.476986[/C][/ROW]
[ROW][C]32[/C][C]0.003557[/C][C]0.0273[/C][C]0.489146[/C][/ROW]
[ROW][C]33[/C][C]0.026752[/C][C]0.2055[/C][C]0.418951[/C][/ROW]
[ROW][C]34[/C][C]-0.076035[/C][C]-0.584[/C][C]0.280711[/C][/ROW]
[ROW][C]35[/C][C]0.117275[/C][C]0.9008[/C][C]0.185678[/C][/ROW]
[ROW][C]36[/C][C]-0.087434[/C][C]-0.6716[/C][C]0.252233[/C][/ROW]
[ROW][C]37[/C][C]-0.00567[/C][C]-0.0436[/C][C]0.482704[/C][/ROW]
[ROW][C]38[/C][C]-0.023231[/C][C]-0.1784[/C][C]0.429495[/C][/ROW]
[ROW][C]39[/C][C]-0.133964[/C][C]-1.029[/C][C]0.15384[/C][/ROW]
[ROW][C]40[/C][C]0.053342[/C][C]0.4097[/C][C]0.341746[/C][/ROW]
[ROW][C]41[/C][C]-0.090164[/C][C]-0.6926[/C][C]0.24565[/C][/ROW]
[ROW][C]42[/C][C]-0.124867[/C][C]-0.9591[/C][C]0.170707[/C][/ROW]
[ROW][C]43[/C][C]0.016485[/C][C]0.1266[/C][C]0.449833[/C][/ROW]
[ROW][C]44[/C][C]-0.002117[/C][C]-0.0163[/C][C]0.493542[/C][/ROW]
[ROW][C]45[/C][C]0.060552[/C][C]0.4651[/C][C]0.321783[/C][/ROW]
[ROW][C]46[/C][C]-0.079866[/C][C]-0.6135[/C][C]0.270965[/C][/ROW]
[ROW][C]47[/C][C]0.023437[/C][C]0.18[/C][C]0.428876[/C][/ROW]
[ROW][C]48[/C][C]0.000244[/C][C]0.0019[/C][C]0.499256[/C][/ROW]
[ROW][C]49[/C][C]-0.076813[/C][C]-0.59[/C][C]0.278717[/C][/ROW]
[ROW][C]50[/C][C]-0.079822[/C][C]-0.6131[/C][C]0.271075[/C][/ROW]
[ROW][C]51[/C][C]-0.013634[/C][C]-0.1047[/C][C]0.458476[/C][/ROW]
[ROW][C]52[/C][C]0.017367[/C][C]0.1334[/C][C]0.447166[/C][/ROW]
[ROW][C]53[/C][C]0.074518[/C][C]0.5724[/C][C]0.284618[/C][/ROW]
[ROW][C]54[/C][C]-0.036967[/C][C]-0.2839[/C][C]0.388723[/C][/ROW]
[ROW][C]55[/C][C]-0.038235[/C][C]-0.2937[/C][C]0.385014[/C][/ROW]
[ROW][C]56[/C][C]-0.049229[/C][C]-0.3781[/C][C]0.353344[/C][/ROW]
[ROW][C]57[/C][C]0.034688[/C][C]0.2664[/C][C]0.395412[/C][/ROW]
[ROW][C]58[/C][C]0.009641[/C][C]0.0741[/C][C]0.47061[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29246&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29246&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
10.0475790.36550.358038
20.096260.73940.231303
3-0.06384-0.49040.312846
4-0.055971-0.42990.33441
5-0.056878-0.43690.331894
6-0.046972-0.36080.359771
7-0.001213-0.00930.496297
80.0032670.02510.490034
90.1731831.33020.094278
10-0.19269-1.48010.072086
110.0041590.03190.487311
12-0.243798-1.87270.033037
13-0.067303-0.5170.303558
140.1935061.48630.071256
15-0.040734-0.31290.377736
16-0.031929-0.24530.403557
17-0.166986-1.28260.102317
180.1344221.03250.153022
190.1629261.25150.107854
200.0097810.07510.470184
210.1142980.87790.191769
22-0.121804-0.93560.176649
230.1251310.96110.1702
24-0.186631-1.43350.078492
25-0.145155-1.1150.134695
26-0.102182-0.78490.217833
270.0038710.02970.48819
28-0.01817-0.13960.444737
290.0007430.00570.497733
30-0.108281-0.83170.20446
310.0075470.0580.476986
320.0035570.02730.489146
330.0267520.20550.418951
34-0.076035-0.5840.280711
350.1172750.90080.185678
36-0.087434-0.67160.252233
37-0.00567-0.04360.482704
38-0.023231-0.17840.429495
39-0.133964-1.0290.15384
400.0533420.40970.341746
41-0.090164-0.69260.24565
42-0.124867-0.95910.170707
430.0164850.12660.449833
44-0.002117-0.01630.493542
450.0605520.46510.321783
46-0.079866-0.61350.270965
470.0234370.180.428876
480.0002440.00190.499256
49-0.076813-0.590.278717
50-0.079822-0.61310.271075
51-0.013634-0.10470.458476
520.0173670.13340.447166
530.0745180.57240.284618
54-0.036967-0.28390.388723
55-0.038235-0.29370.385014
56-0.049229-0.37810.353344
570.0346880.26640.395412
580.0096410.07410.47061
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1.9 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1.9 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')