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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 computationThu, 15 Dec 2016 12:09:44 +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/2016/Dec/15/t1481800208ax1ryk05lmiow95.htm/, Retrieved Fri, 03 May 2024 11:28:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299867, Retrieved Fri, 03 May 2024 11:28:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsF1 competition
Estimated Impact44
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Partial Autocorre...] [2016-12-15 11:09:44] [00d6a26c230b6c589ee3bbc701d55499] [Current]
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Dataseries X:
3840
3140
4580
4740
3920
4900
3400
3440
2600
2220
2190
2550
2720
3720
4710
5070
6030
5280
4420
3940
2750
2980
2690
2650
4000
4150
6050
6280
5520
4800
4610
3530
2790
2750
2470
2610
3680
3820
4460
4760
3290
3610
3650
3130
2850
2720
2740
2760
3330
3850
5430
5180
4770
5360
4950
3720
3330
3000
2760
3040
3260
3780
4670
4320
4080
4210
3350
3390
2630
2350
2330
2230
2830
3230
4240
3750
4160
3960
3000
2890
2300
2320
2270
1970
2920
3310
4370
3990
3970
3850
3510
2840
2130
2280
1960
1740
2370
1980
2680
3510
3350
3290
3150
2490
2490
2930
3590
2040
2480
2760
3400
3470
3130
3670
3080
2430




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=299867&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=299867&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299867&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 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
1-0.323631-3.28450.000698
2-0.082694-0.83920.201637
30.2395332.4310.008392
4-0.200707-2.0370.02211
50.0724230.7350.232001
60.0603450.61240.270798
7-0.189128-1.91940.028848
80.0686590.69680.243746
90.0276280.28040.38987
10-0.102604-1.04130.150084
110.190981.93820.027666
12-0.230323-2.33750.010673
13-0.061032-0.61940.268507
140.0800960.81290.209078
15-0.03102-0.31480.376767
16-0.131823-1.33790.091945
170.1300431.31980.094915
18-0.059679-0.60570.273031
19-0.035486-0.36010.35974
200.1411941.4330.077449
21-0.118911-1.20680.115133
22-0.042159-0.42790.334822
230.1372191.39260.083367
24-0.125863-1.27740.102171
25-0.030653-0.31110.378181
260.1230051.24840.107364
27-0.205482-2.08540.019752
280.157151.59490.0569
290.0438760.44530.328521
30-0.030253-0.3070.379718
310.0497710.50510.307276
320.0796320.80820.210427
33-0.037554-0.38110.351945
340.0417290.42350.336407
35-0.018747-0.19030.42474
36-0.070732-0.71780.237238
370.1622741.64690.051313
38-0.062186-0.63110.264682
390.0032580.03310.486844
400.0389470.39530.346731
41-0.011934-0.12110.451916
42-0.11161-1.13270.129981
430.1293431.31270.096102
44-0.163924-1.66360.049611
45-0.064423-0.65380.257341
460.1234621.2530.106521
47-0.102573-1.0410.150156
48-0.036286-0.36830.356718

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.323631 & -3.2845 & 0.000698 \tabularnewline
2 & -0.082694 & -0.8392 & 0.201637 \tabularnewline
3 & 0.239533 & 2.431 & 0.008392 \tabularnewline
4 & -0.200707 & -2.037 & 0.02211 \tabularnewline
5 & 0.072423 & 0.735 & 0.232001 \tabularnewline
6 & 0.060345 & 0.6124 & 0.270798 \tabularnewline
7 & -0.189128 & -1.9194 & 0.028848 \tabularnewline
8 & 0.068659 & 0.6968 & 0.243746 \tabularnewline
9 & 0.027628 & 0.2804 & 0.38987 \tabularnewline
10 & -0.102604 & -1.0413 & 0.150084 \tabularnewline
11 & 0.19098 & 1.9382 & 0.027666 \tabularnewline
12 & -0.230323 & -2.3375 & 0.010673 \tabularnewline
13 & -0.061032 & -0.6194 & 0.268507 \tabularnewline
14 & 0.080096 & 0.8129 & 0.209078 \tabularnewline
15 & -0.03102 & -0.3148 & 0.376767 \tabularnewline
16 & -0.131823 & -1.3379 & 0.091945 \tabularnewline
17 & 0.130043 & 1.3198 & 0.094915 \tabularnewline
18 & -0.059679 & -0.6057 & 0.273031 \tabularnewline
19 & -0.035486 & -0.3601 & 0.35974 \tabularnewline
20 & 0.141194 & 1.433 & 0.077449 \tabularnewline
21 & -0.118911 & -1.2068 & 0.115133 \tabularnewline
22 & -0.042159 & -0.4279 & 0.334822 \tabularnewline
23 & 0.137219 & 1.3926 & 0.083367 \tabularnewline
24 & -0.125863 & -1.2774 & 0.102171 \tabularnewline
25 & -0.030653 & -0.3111 & 0.378181 \tabularnewline
26 & 0.123005 & 1.2484 & 0.107364 \tabularnewline
27 & -0.205482 & -2.0854 & 0.019752 \tabularnewline
28 & 0.15715 & 1.5949 & 0.0569 \tabularnewline
29 & 0.043876 & 0.4453 & 0.328521 \tabularnewline
30 & -0.030253 & -0.307 & 0.379718 \tabularnewline
31 & 0.049771 & 0.5051 & 0.307276 \tabularnewline
32 & 0.079632 & 0.8082 & 0.210427 \tabularnewline
33 & -0.037554 & -0.3811 & 0.351945 \tabularnewline
34 & 0.041729 & 0.4235 & 0.336407 \tabularnewline
35 & -0.018747 & -0.1903 & 0.42474 \tabularnewline
36 & -0.070732 & -0.7178 & 0.237238 \tabularnewline
37 & 0.162274 & 1.6469 & 0.051313 \tabularnewline
38 & -0.062186 & -0.6311 & 0.264682 \tabularnewline
39 & 0.003258 & 0.0331 & 0.486844 \tabularnewline
40 & 0.038947 & 0.3953 & 0.346731 \tabularnewline
41 & -0.011934 & -0.1211 & 0.451916 \tabularnewline
42 & -0.11161 & -1.1327 & 0.129981 \tabularnewline
43 & 0.129343 & 1.3127 & 0.096102 \tabularnewline
44 & -0.163924 & -1.6636 & 0.049611 \tabularnewline
45 & -0.064423 & -0.6538 & 0.257341 \tabularnewline
46 & 0.123462 & 1.253 & 0.106521 \tabularnewline
47 & -0.102573 & -1.041 & 0.150156 \tabularnewline
48 & -0.036286 & -0.3683 & 0.356718 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299867&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]-0.323631[/C][C]-3.2845[/C][C]0.000698[/C][/ROW]
[ROW][C]2[/C][C]-0.082694[/C][C]-0.8392[/C][C]0.201637[/C][/ROW]
[ROW][C]3[/C][C]0.239533[/C][C]2.431[/C][C]0.008392[/C][/ROW]
[ROW][C]4[/C][C]-0.200707[/C][C]-2.037[/C][C]0.02211[/C][/ROW]
[ROW][C]5[/C][C]0.072423[/C][C]0.735[/C][C]0.232001[/C][/ROW]
[ROW][C]6[/C][C]0.060345[/C][C]0.6124[/C][C]0.270798[/C][/ROW]
[ROW][C]7[/C][C]-0.189128[/C][C]-1.9194[/C][C]0.028848[/C][/ROW]
[ROW][C]8[/C][C]0.068659[/C][C]0.6968[/C][C]0.243746[/C][/ROW]
[ROW][C]9[/C][C]0.027628[/C][C]0.2804[/C][C]0.38987[/C][/ROW]
[ROW][C]10[/C][C]-0.102604[/C][C]-1.0413[/C][C]0.150084[/C][/ROW]
[ROW][C]11[/C][C]0.19098[/C][C]1.9382[/C][C]0.027666[/C][/ROW]
[ROW][C]12[/C][C]-0.230323[/C][C]-2.3375[/C][C]0.010673[/C][/ROW]
[ROW][C]13[/C][C]-0.061032[/C][C]-0.6194[/C][C]0.268507[/C][/ROW]
[ROW][C]14[/C][C]0.080096[/C][C]0.8129[/C][C]0.209078[/C][/ROW]
[ROW][C]15[/C][C]-0.03102[/C][C]-0.3148[/C][C]0.376767[/C][/ROW]
[ROW][C]16[/C][C]-0.131823[/C][C]-1.3379[/C][C]0.091945[/C][/ROW]
[ROW][C]17[/C][C]0.130043[/C][C]1.3198[/C][C]0.094915[/C][/ROW]
[ROW][C]18[/C][C]-0.059679[/C][C]-0.6057[/C][C]0.273031[/C][/ROW]
[ROW][C]19[/C][C]-0.035486[/C][C]-0.3601[/C][C]0.35974[/C][/ROW]
[ROW][C]20[/C][C]0.141194[/C][C]1.433[/C][C]0.077449[/C][/ROW]
[ROW][C]21[/C][C]-0.118911[/C][C]-1.2068[/C][C]0.115133[/C][/ROW]
[ROW][C]22[/C][C]-0.042159[/C][C]-0.4279[/C][C]0.334822[/C][/ROW]
[ROW][C]23[/C][C]0.137219[/C][C]1.3926[/C][C]0.083367[/C][/ROW]
[ROW][C]24[/C][C]-0.125863[/C][C]-1.2774[/C][C]0.102171[/C][/ROW]
[ROW][C]25[/C][C]-0.030653[/C][C]-0.3111[/C][C]0.378181[/C][/ROW]
[ROW][C]26[/C][C]0.123005[/C][C]1.2484[/C][C]0.107364[/C][/ROW]
[ROW][C]27[/C][C]-0.205482[/C][C]-2.0854[/C][C]0.019752[/C][/ROW]
[ROW][C]28[/C][C]0.15715[/C][C]1.5949[/C][C]0.0569[/C][/ROW]
[ROW][C]29[/C][C]0.043876[/C][C]0.4453[/C][C]0.328521[/C][/ROW]
[ROW][C]30[/C][C]-0.030253[/C][C]-0.307[/C][C]0.379718[/C][/ROW]
[ROW][C]31[/C][C]0.049771[/C][C]0.5051[/C][C]0.307276[/C][/ROW]
[ROW][C]32[/C][C]0.079632[/C][C]0.8082[/C][C]0.210427[/C][/ROW]
[ROW][C]33[/C][C]-0.037554[/C][C]-0.3811[/C][C]0.351945[/C][/ROW]
[ROW][C]34[/C][C]0.041729[/C][C]0.4235[/C][C]0.336407[/C][/ROW]
[ROW][C]35[/C][C]-0.018747[/C][C]-0.1903[/C][C]0.42474[/C][/ROW]
[ROW][C]36[/C][C]-0.070732[/C][C]-0.7178[/C][C]0.237238[/C][/ROW]
[ROW][C]37[/C][C]0.162274[/C][C]1.6469[/C][C]0.051313[/C][/ROW]
[ROW][C]38[/C][C]-0.062186[/C][C]-0.6311[/C][C]0.264682[/C][/ROW]
[ROW][C]39[/C][C]0.003258[/C][C]0.0331[/C][C]0.486844[/C][/ROW]
[ROW][C]40[/C][C]0.038947[/C][C]0.3953[/C][C]0.346731[/C][/ROW]
[ROW][C]41[/C][C]-0.011934[/C][C]-0.1211[/C][C]0.451916[/C][/ROW]
[ROW][C]42[/C][C]-0.11161[/C][C]-1.1327[/C][C]0.129981[/C][/ROW]
[ROW][C]43[/C][C]0.129343[/C][C]1.3127[/C][C]0.096102[/C][/ROW]
[ROW][C]44[/C][C]-0.163924[/C][C]-1.6636[/C][C]0.049611[/C][/ROW]
[ROW][C]45[/C][C]-0.064423[/C][C]-0.6538[/C][C]0.257341[/C][/ROW]
[ROW][C]46[/C][C]0.123462[/C][C]1.253[/C][C]0.106521[/C][/ROW]
[ROW][C]47[/C][C]-0.102573[/C][C]-1.041[/C][C]0.150156[/C][/ROW]
[ROW][C]48[/C][C]-0.036286[/C][C]-0.3683[/C][C]0.356718[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299867&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299867&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
1-0.323631-3.28450.000698
2-0.082694-0.83920.201637
30.2395332.4310.008392
4-0.200707-2.0370.02211
50.0724230.7350.232001
60.0603450.61240.270798
7-0.189128-1.91940.028848
80.0686590.69680.243746
90.0276280.28040.38987
10-0.102604-1.04130.150084
110.190981.93820.027666
12-0.230323-2.33750.010673
13-0.061032-0.61940.268507
140.0800960.81290.209078
15-0.03102-0.31480.376767
16-0.131823-1.33790.091945
170.1300431.31980.094915
18-0.059679-0.60570.273031
19-0.035486-0.36010.35974
200.1411941.4330.077449
21-0.118911-1.20680.115133
22-0.042159-0.42790.334822
230.1372191.39260.083367
24-0.125863-1.27740.102171
25-0.030653-0.31110.378181
260.1230051.24840.107364
27-0.205482-2.08540.019752
280.157151.59490.0569
290.0438760.44530.328521
30-0.030253-0.3070.379718
310.0497710.50510.307276
320.0796320.80820.210427
33-0.037554-0.38110.351945
340.0417290.42350.336407
35-0.018747-0.19030.42474
36-0.070732-0.71780.237238
370.1622741.64690.051313
38-0.062186-0.63110.264682
390.0032580.03310.486844
400.0389470.39530.346731
41-0.011934-0.12110.451916
42-0.11161-1.13270.129981
430.1293431.31270.096102
44-0.163924-1.66360.049611
45-0.064423-0.65380.257341
460.1234621.2530.106521
47-0.102573-1.0410.150156
48-0.036286-0.36830.356718







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.323631-3.28450.000698
2-0.209358-2.12480.018
30.1628611.65290.050702
4-0.089352-0.90680.183308
50.0284760.2890.38658
60.0273440.27750.390974
7-0.121803-1.23620.109604
8-0.06336-0.6430.260814
9-0.003127-0.03170.487372
10-0.041546-0.42160.33708
110.1414521.43560.077075
12-0.173517-1.7610.040603
13-0.15743-1.59770.056582
14-0.137133-1.39170.083499
150.0443390.450.32683
16-0.177201-1.79840.037522
170.0294890.29930.382666
18-0.022915-0.23260.40828
19-0.049877-0.50620.306902
200.0019450.01970.492144
21-0.046231-0.46920.319962
22-0.138886-1.40950.080844
230.0697180.70760.240408
24-0.089705-0.91040.182367
25-0.139338-1.41410.08017
26-0.055108-0.55930.288592
27-0.135633-1.37650.085823
28-0.056718-0.57560.283064
290.0063820.06480.474241
300.1046261.06180.145396
31-0.046454-0.47150.319158
320.1275431.29440.099208
330.0436190.44270.32946
34-0.04603-0.46720.32069
35-0.00968-0.09820.460964
36-0.035436-0.35960.359929
370.0587380.59610.276201
380.0604170.61320.27056
390.0325460.33030.370922
40-0.031862-0.32340.373538
410.0629840.63920.26205
42-0.054135-0.54940.291957
430.0248680.25240.400625
44-0.019333-0.19620.422415
45-0.038042-0.38610.350116
46-0.00211-0.02140.491479
470.0207380.21050.416859
48-0.134365-1.36370.087825

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.323631 & -3.2845 & 0.000698 \tabularnewline
2 & -0.209358 & -2.1248 & 0.018 \tabularnewline
3 & 0.162861 & 1.6529 & 0.050702 \tabularnewline
4 & -0.089352 & -0.9068 & 0.183308 \tabularnewline
5 & 0.028476 & 0.289 & 0.38658 \tabularnewline
6 & 0.027344 & 0.2775 & 0.390974 \tabularnewline
7 & -0.121803 & -1.2362 & 0.109604 \tabularnewline
8 & -0.06336 & -0.643 & 0.260814 \tabularnewline
9 & -0.003127 & -0.0317 & 0.487372 \tabularnewline
10 & -0.041546 & -0.4216 & 0.33708 \tabularnewline
11 & 0.141452 & 1.4356 & 0.077075 \tabularnewline
12 & -0.173517 & -1.761 & 0.040603 \tabularnewline
13 & -0.15743 & -1.5977 & 0.056582 \tabularnewline
14 & -0.137133 & -1.3917 & 0.083499 \tabularnewline
15 & 0.044339 & 0.45 & 0.32683 \tabularnewline
16 & -0.177201 & -1.7984 & 0.037522 \tabularnewline
17 & 0.029489 & 0.2993 & 0.382666 \tabularnewline
18 & -0.022915 & -0.2326 & 0.40828 \tabularnewline
19 & -0.049877 & -0.5062 & 0.306902 \tabularnewline
20 & 0.001945 & 0.0197 & 0.492144 \tabularnewline
21 & -0.046231 & -0.4692 & 0.319962 \tabularnewline
22 & -0.138886 & -1.4095 & 0.080844 \tabularnewline
23 & 0.069718 & 0.7076 & 0.240408 \tabularnewline
24 & -0.089705 & -0.9104 & 0.182367 \tabularnewline
25 & -0.139338 & -1.4141 & 0.08017 \tabularnewline
26 & -0.055108 & -0.5593 & 0.288592 \tabularnewline
27 & -0.135633 & -1.3765 & 0.085823 \tabularnewline
28 & -0.056718 & -0.5756 & 0.283064 \tabularnewline
29 & 0.006382 & 0.0648 & 0.474241 \tabularnewline
30 & 0.104626 & 1.0618 & 0.145396 \tabularnewline
31 & -0.046454 & -0.4715 & 0.319158 \tabularnewline
32 & 0.127543 & 1.2944 & 0.099208 \tabularnewline
33 & 0.043619 & 0.4427 & 0.32946 \tabularnewline
34 & -0.04603 & -0.4672 & 0.32069 \tabularnewline
35 & -0.00968 & -0.0982 & 0.460964 \tabularnewline
36 & -0.035436 & -0.3596 & 0.359929 \tabularnewline
37 & 0.058738 & 0.5961 & 0.276201 \tabularnewline
38 & 0.060417 & 0.6132 & 0.27056 \tabularnewline
39 & 0.032546 & 0.3303 & 0.370922 \tabularnewline
40 & -0.031862 & -0.3234 & 0.373538 \tabularnewline
41 & 0.062984 & 0.6392 & 0.26205 \tabularnewline
42 & -0.054135 & -0.5494 & 0.291957 \tabularnewline
43 & 0.024868 & 0.2524 & 0.400625 \tabularnewline
44 & -0.019333 & -0.1962 & 0.422415 \tabularnewline
45 & -0.038042 & -0.3861 & 0.350116 \tabularnewline
46 & -0.00211 & -0.0214 & 0.491479 \tabularnewline
47 & 0.020738 & 0.2105 & 0.416859 \tabularnewline
48 & -0.134365 & -1.3637 & 0.087825 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299867&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]-0.323631[/C][C]-3.2845[/C][C]0.000698[/C][/ROW]
[ROW][C]2[/C][C]-0.209358[/C][C]-2.1248[/C][C]0.018[/C][/ROW]
[ROW][C]3[/C][C]0.162861[/C][C]1.6529[/C][C]0.050702[/C][/ROW]
[ROW][C]4[/C][C]-0.089352[/C][C]-0.9068[/C][C]0.183308[/C][/ROW]
[ROW][C]5[/C][C]0.028476[/C][C]0.289[/C][C]0.38658[/C][/ROW]
[ROW][C]6[/C][C]0.027344[/C][C]0.2775[/C][C]0.390974[/C][/ROW]
[ROW][C]7[/C][C]-0.121803[/C][C]-1.2362[/C][C]0.109604[/C][/ROW]
[ROW][C]8[/C][C]-0.06336[/C][C]-0.643[/C][C]0.260814[/C][/ROW]
[ROW][C]9[/C][C]-0.003127[/C][C]-0.0317[/C][C]0.487372[/C][/ROW]
[ROW][C]10[/C][C]-0.041546[/C][C]-0.4216[/C][C]0.33708[/C][/ROW]
[ROW][C]11[/C][C]0.141452[/C][C]1.4356[/C][C]0.077075[/C][/ROW]
[ROW][C]12[/C][C]-0.173517[/C][C]-1.761[/C][C]0.040603[/C][/ROW]
[ROW][C]13[/C][C]-0.15743[/C][C]-1.5977[/C][C]0.056582[/C][/ROW]
[ROW][C]14[/C][C]-0.137133[/C][C]-1.3917[/C][C]0.083499[/C][/ROW]
[ROW][C]15[/C][C]0.044339[/C][C]0.45[/C][C]0.32683[/C][/ROW]
[ROW][C]16[/C][C]-0.177201[/C][C]-1.7984[/C][C]0.037522[/C][/ROW]
[ROW][C]17[/C][C]0.029489[/C][C]0.2993[/C][C]0.382666[/C][/ROW]
[ROW][C]18[/C][C]-0.022915[/C][C]-0.2326[/C][C]0.40828[/C][/ROW]
[ROW][C]19[/C][C]-0.049877[/C][C]-0.5062[/C][C]0.306902[/C][/ROW]
[ROW][C]20[/C][C]0.001945[/C][C]0.0197[/C][C]0.492144[/C][/ROW]
[ROW][C]21[/C][C]-0.046231[/C][C]-0.4692[/C][C]0.319962[/C][/ROW]
[ROW][C]22[/C][C]-0.138886[/C][C]-1.4095[/C][C]0.080844[/C][/ROW]
[ROW][C]23[/C][C]0.069718[/C][C]0.7076[/C][C]0.240408[/C][/ROW]
[ROW][C]24[/C][C]-0.089705[/C][C]-0.9104[/C][C]0.182367[/C][/ROW]
[ROW][C]25[/C][C]-0.139338[/C][C]-1.4141[/C][C]0.08017[/C][/ROW]
[ROW][C]26[/C][C]-0.055108[/C][C]-0.5593[/C][C]0.288592[/C][/ROW]
[ROW][C]27[/C][C]-0.135633[/C][C]-1.3765[/C][C]0.085823[/C][/ROW]
[ROW][C]28[/C][C]-0.056718[/C][C]-0.5756[/C][C]0.283064[/C][/ROW]
[ROW][C]29[/C][C]0.006382[/C][C]0.0648[/C][C]0.474241[/C][/ROW]
[ROW][C]30[/C][C]0.104626[/C][C]1.0618[/C][C]0.145396[/C][/ROW]
[ROW][C]31[/C][C]-0.046454[/C][C]-0.4715[/C][C]0.319158[/C][/ROW]
[ROW][C]32[/C][C]0.127543[/C][C]1.2944[/C][C]0.099208[/C][/ROW]
[ROW][C]33[/C][C]0.043619[/C][C]0.4427[/C][C]0.32946[/C][/ROW]
[ROW][C]34[/C][C]-0.04603[/C][C]-0.4672[/C][C]0.32069[/C][/ROW]
[ROW][C]35[/C][C]-0.00968[/C][C]-0.0982[/C][C]0.460964[/C][/ROW]
[ROW][C]36[/C][C]-0.035436[/C][C]-0.3596[/C][C]0.359929[/C][/ROW]
[ROW][C]37[/C][C]0.058738[/C][C]0.5961[/C][C]0.276201[/C][/ROW]
[ROW][C]38[/C][C]0.060417[/C][C]0.6132[/C][C]0.27056[/C][/ROW]
[ROW][C]39[/C][C]0.032546[/C][C]0.3303[/C][C]0.370922[/C][/ROW]
[ROW][C]40[/C][C]-0.031862[/C][C]-0.3234[/C][C]0.373538[/C][/ROW]
[ROW][C]41[/C][C]0.062984[/C][C]0.6392[/C][C]0.26205[/C][/ROW]
[ROW][C]42[/C][C]-0.054135[/C][C]-0.5494[/C][C]0.291957[/C][/ROW]
[ROW][C]43[/C][C]0.024868[/C][C]0.2524[/C][C]0.400625[/C][/ROW]
[ROW][C]44[/C][C]-0.019333[/C][C]-0.1962[/C][C]0.422415[/C][/ROW]
[ROW][C]45[/C][C]-0.038042[/C][C]-0.3861[/C][C]0.350116[/C][/ROW]
[ROW][C]46[/C][C]-0.00211[/C][C]-0.0214[/C][C]0.491479[/C][/ROW]
[ROW][C]47[/C][C]0.020738[/C][C]0.2105[/C][C]0.416859[/C][/ROW]
[ROW][C]48[/C][C]-0.134365[/C][C]-1.3637[/C][C]0.087825[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299867&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299867&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
1-0.323631-3.28450.000698
2-0.209358-2.12480.018
30.1628611.65290.050702
4-0.089352-0.90680.183308
50.0284760.2890.38658
60.0273440.27750.390974
7-0.121803-1.23620.109604
8-0.06336-0.6430.260814
9-0.003127-0.03170.487372
10-0.041546-0.42160.33708
110.1414521.43560.077075
12-0.173517-1.7610.040603
13-0.15743-1.59770.056582
14-0.137133-1.39170.083499
150.0443390.450.32683
16-0.177201-1.79840.037522
170.0294890.29930.382666
18-0.022915-0.23260.40828
19-0.049877-0.50620.306902
200.0019450.01970.492144
21-0.046231-0.46920.319962
22-0.138886-1.40950.080844
230.0697180.70760.240408
24-0.089705-0.91040.182367
25-0.139338-1.41410.08017
26-0.055108-0.55930.288592
27-0.135633-1.37650.085823
28-0.056718-0.57560.283064
290.0063820.06480.474241
300.1046261.06180.145396
31-0.046454-0.47150.319158
320.1275431.29440.099208
330.0436190.44270.32946
34-0.04603-0.46720.32069
35-0.00968-0.09820.460964
36-0.035436-0.35960.359929
370.0587380.59610.276201
380.0604170.61320.27056
390.0325460.33030.370922
40-0.031862-0.32340.373538
410.0629840.63920.26205
42-0.054135-0.54940.291957
430.0248680.25240.400625
44-0.019333-0.19620.422415
45-0.038042-0.38610.350116
46-0.00211-0.02140.491479
470.0207380.21050.416859
48-0.134365-1.36370.087825



Parameters (Session):
par1 = TRUE ; par2 = -0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
Parameters (R input):
par1 = 48 ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
par8 <- ''
par7 <- ''
par6 <- 'White Noise'
par5 <- '12'
par4 <- '1'
par3 <- '1'
par2 <- '0.0'
par1 <- '48'
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')