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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 05 Mar 2015 17:54:45 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Mar/05/t1425578145nkf62147gh6nxxe.htm/, Retrieved Fri, 17 May 2024 01:16:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=277975, Retrieved Fri, 17 May 2024 01:16:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66

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] [] [2015-03-05 17:54:45] [c6da619eabbd864125b02146bc2bbd84] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,69867
0,68968
0,69233
0,68293
0,68399
0,66895
0,68756
0,68527
0,6776
0,68137
0,67933
0,67922
0,68598
0,68297
0,68935
0,69463
0,6833
0,68666
0,68782
0,67669
0,67511
0,67254
0,67397
0,67286
0,66341
0,668
0,68021
0,67934
0,68136
0,67562
0,6744
0,67766
0,68887
0,69614
0,70896
0,72064
0,74725
0,75094
0,77494
0,79487
0,79209
0,79152
0,79308
0,79279
0,79924
0,78668
0,83063
0,90448
0,91819
0,88691
0,91966
0,89756
0,88445
0,8567
0,86092
0,86265
0,89135
0,91557
0,89892
0,89972
0,88305
0,87604
0,9016
0,87456
0,85714
0,82771
0,83566
0,82363
0,83987
0,87638
0,8551
0,84813
0,84712
0,84635
0,86653
0,88291
0,87788
0,88745
0,88476
0,87668
0,87172
0,87036
0,8574
0,84405
0,8321
0,83696
0,83448
0,82188
0,80371
0,80579
0,78827
0,78884
0,79821
0,80665
0,80389
0,81237
0,83271
0,8625
0,85996
0,85076
0,84914
0,85191
0,86192
0,85904
0,84171
0,8472
0,8378
0,83639
0,82674
0,8251
0,8317
0,8252
0,81535
0,80409
0,7931
0,7973
0,79113
0,78861
0,79054
0,7883

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277975&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277975&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277975&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.97627510.69460
20.94569210.35950
30.91567910.03080
40.8834779.6780
50.8520779.3340
60.8202488.98540
70.7910668.66570
80.7620218.34750
90.7304048.00120
100.6968457.63360
110.6605067.23550
120.6231966.82680
130.5803576.35750
140.5405275.92120
150.50415.52210
160.4702045.15081e-06
170.4369234.78622e-06
180.4110174.50258e-06
190.3848774.21612.4e-05
200.3564373.90467.8e-05
210.3279683.59270.000238
220.2956563.23870.000777
230.2593442.8410.002643
240.2219142.43090.008269
250.1825862.00010.023872
260.144421.5820.058136
270.1108661.21450.113475
280.0763870.83680.20219
290.040590.44460.328688
300.0038050.04170.483412
31-0.035773-0.39190.347923
32-0.072568-0.79490.214109
33-0.104212-1.14160.127949
34-0.134259-1.47070.071991
35-0.161265-1.76660.039922
36-0.187762-2.05680.020935
37-0.210964-2.3110.01127
38-0.230747-2.52770.00639
39-0.245904-2.69370.004039
40-0.258904-2.83620.002681
41-0.271445-2.97350.00178
42-0.286528-3.13880.001068
43-0.299181-3.27740.000685
44-0.30896-3.38450.000482
45-0.314969-3.45030.000387
46-0.32055-3.51140.000314
47-0.321351-3.52020.000305
48-0.312067-3.41850.00043

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.976275 & 10.6946 & 0 \tabularnewline
2 & 0.945692 & 10.3595 & 0 \tabularnewline
3 & 0.915679 & 10.0308 & 0 \tabularnewline
4 & 0.883477 & 9.678 & 0 \tabularnewline
5 & 0.852077 & 9.334 & 0 \tabularnewline
6 & 0.820248 & 8.9854 & 0 \tabularnewline
7 & 0.791066 & 8.6657 & 0 \tabularnewline
8 & 0.762021 & 8.3475 & 0 \tabularnewline
9 & 0.730404 & 8.0012 & 0 \tabularnewline
10 & 0.696845 & 7.6336 & 0 \tabularnewline
11 & 0.660506 & 7.2355 & 0 \tabularnewline
12 & 0.623196 & 6.8268 & 0 \tabularnewline
13 & 0.580357 & 6.3575 & 0 \tabularnewline
14 & 0.540527 & 5.9212 & 0 \tabularnewline
15 & 0.5041 & 5.5221 & 0 \tabularnewline
16 & 0.470204 & 5.1508 & 1e-06 \tabularnewline
17 & 0.436923 & 4.7862 & 2e-06 \tabularnewline
18 & 0.411017 & 4.5025 & 8e-06 \tabularnewline
19 & 0.384877 & 4.2161 & 2.4e-05 \tabularnewline
20 & 0.356437 & 3.9046 & 7.8e-05 \tabularnewline
21 & 0.327968 & 3.5927 & 0.000238 \tabularnewline
22 & 0.295656 & 3.2387 & 0.000777 \tabularnewline
23 & 0.259344 & 2.841 & 0.002643 \tabularnewline
24 & 0.221914 & 2.4309 & 0.008269 \tabularnewline
25 & 0.182586 & 2.0001 & 0.023872 \tabularnewline
26 & 0.14442 & 1.582 & 0.058136 \tabularnewline
27 & 0.110866 & 1.2145 & 0.113475 \tabularnewline
28 & 0.076387 & 0.8368 & 0.20219 \tabularnewline
29 & 0.04059 & 0.4446 & 0.328688 \tabularnewline
30 & 0.003805 & 0.0417 & 0.483412 \tabularnewline
31 & -0.035773 & -0.3919 & 0.347923 \tabularnewline
32 & -0.072568 & -0.7949 & 0.214109 \tabularnewline
33 & -0.104212 & -1.1416 & 0.127949 \tabularnewline
34 & -0.134259 & -1.4707 & 0.071991 \tabularnewline
35 & -0.161265 & -1.7666 & 0.039922 \tabularnewline
36 & -0.187762 & -2.0568 & 0.020935 \tabularnewline
37 & -0.210964 & -2.311 & 0.01127 \tabularnewline
38 & -0.230747 & -2.5277 & 0.00639 \tabularnewline
39 & -0.245904 & -2.6937 & 0.004039 \tabularnewline
40 & -0.258904 & -2.8362 & 0.002681 \tabularnewline
41 & -0.271445 & -2.9735 & 0.00178 \tabularnewline
42 & -0.286528 & -3.1388 & 0.001068 \tabularnewline
43 & -0.299181 & -3.2774 & 0.000685 \tabularnewline
44 & -0.30896 & -3.3845 & 0.000482 \tabularnewline
45 & -0.314969 & -3.4503 & 0.000387 \tabularnewline
46 & -0.32055 & -3.5114 & 0.000314 \tabularnewline
47 & -0.321351 & -3.5202 & 0.000305 \tabularnewline
48 & -0.312067 & -3.4185 & 0.00043 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277975&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]0.976275[/C][C]10.6946[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.945692[/C][C]10.3595[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.915679[/C][C]10.0308[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.883477[/C][C]9.678[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.852077[/C][C]9.334[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.820248[/C][C]8.9854[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.791066[/C][C]8.6657[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.762021[/C][C]8.3475[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.730404[/C][C]8.0012[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.696845[/C][C]7.6336[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.660506[/C][C]7.2355[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.623196[/C][C]6.8268[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.580357[/C][C]6.3575[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.540527[/C][C]5.9212[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.5041[/C][C]5.5221[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.470204[/C][C]5.1508[/C][C]1e-06[/C][/ROW]
[ROW][C]17[/C][C]0.436923[/C][C]4.7862[/C][C]2e-06[/C][/ROW]
[ROW][C]18[/C][C]0.411017[/C][C]4.5025[/C][C]8e-06[/C][/ROW]
[ROW][C]19[/C][C]0.384877[/C][C]4.2161[/C][C]2.4e-05[/C][/ROW]
[ROW][C]20[/C][C]0.356437[/C][C]3.9046[/C][C]7.8e-05[/C][/ROW]
[ROW][C]21[/C][C]0.327968[/C][C]3.5927[/C][C]0.000238[/C][/ROW]
[ROW][C]22[/C][C]0.295656[/C][C]3.2387[/C][C]0.000777[/C][/ROW]
[ROW][C]23[/C][C]0.259344[/C][C]2.841[/C][C]0.002643[/C][/ROW]
[ROW][C]24[/C][C]0.221914[/C][C]2.4309[/C][C]0.008269[/C][/ROW]
[ROW][C]25[/C][C]0.182586[/C][C]2.0001[/C][C]0.023872[/C][/ROW]
[ROW][C]26[/C][C]0.14442[/C][C]1.582[/C][C]0.058136[/C][/ROW]
[ROW][C]27[/C][C]0.110866[/C][C]1.2145[/C][C]0.113475[/C][/ROW]
[ROW][C]28[/C][C]0.076387[/C][C]0.8368[/C][C]0.20219[/C][/ROW]
[ROW][C]29[/C][C]0.04059[/C][C]0.4446[/C][C]0.328688[/C][/ROW]
[ROW][C]30[/C][C]0.003805[/C][C]0.0417[/C][C]0.483412[/C][/ROW]
[ROW][C]31[/C][C]-0.035773[/C][C]-0.3919[/C][C]0.347923[/C][/ROW]
[ROW][C]32[/C][C]-0.072568[/C][C]-0.7949[/C][C]0.214109[/C][/ROW]
[ROW][C]33[/C][C]-0.104212[/C][C]-1.1416[/C][C]0.127949[/C][/ROW]
[ROW][C]34[/C][C]-0.134259[/C][C]-1.4707[/C][C]0.071991[/C][/ROW]
[ROW][C]35[/C][C]-0.161265[/C][C]-1.7666[/C][C]0.039922[/C][/ROW]
[ROW][C]36[/C][C]-0.187762[/C][C]-2.0568[/C][C]0.020935[/C][/ROW]
[ROW][C]37[/C][C]-0.210964[/C][C]-2.311[/C][C]0.01127[/C][/ROW]
[ROW][C]38[/C][C]-0.230747[/C][C]-2.5277[/C][C]0.00639[/C][/ROW]
[ROW][C]39[/C][C]-0.245904[/C][C]-2.6937[/C][C]0.004039[/C][/ROW]
[ROW][C]40[/C][C]-0.258904[/C][C]-2.8362[/C][C]0.002681[/C][/ROW]
[ROW][C]41[/C][C]-0.271445[/C][C]-2.9735[/C][C]0.00178[/C][/ROW]
[ROW][C]42[/C][C]-0.286528[/C][C]-3.1388[/C][C]0.001068[/C][/ROW]
[ROW][C]43[/C][C]-0.299181[/C][C]-3.2774[/C][C]0.000685[/C][/ROW]
[ROW][C]44[/C][C]-0.30896[/C][C]-3.3845[/C][C]0.000482[/C][/ROW]
[ROW][C]45[/C][C]-0.314969[/C][C]-3.4503[/C][C]0.000387[/C][/ROW]
[ROW][C]46[/C][C]-0.32055[/C][C]-3.5114[/C][C]0.000314[/C][/ROW]
[ROW][C]47[/C][C]-0.321351[/C][C]-3.5202[/C][C]0.000305[/C][/ROW]
[ROW][C]48[/C][C]-0.312067[/C][C]-3.4185[/C][C]0.00043[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277975&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277975&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
10.97627510.69460
20.94569210.35950
30.91567910.03080
40.8834779.6780
50.8520779.3340
60.8202488.98540
70.7910668.66570
80.7620218.34750
90.7304048.00120
100.6968457.63360
110.6605067.23550
120.6231966.82680
130.5803576.35750
140.5405275.92120
150.50415.52210
160.4702045.15081e-06
170.4369234.78622e-06
180.4110174.50258e-06
190.3848774.21612.4e-05
200.3564373.90467.8e-05
210.3279683.59270.000238
220.2956563.23870.000777
230.2593442.8410.002643
240.2219142.43090.008269
250.1825862.00010.023872
260.144421.5820.058136
270.1108661.21450.113475
280.0763870.83680.20219
290.040590.44460.328688
300.0038050.04170.483412
31-0.035773-0.39190.347923
32-0.072568-0.79490.214109
33-0.104212-1.14160.127949
34-0.134259-1.47070.071991
35-0.161265-1.76660.039922
36-0.187762-2.05680.020935
37-0.210964-2.3110.01127
38-0.230747-2.52770.00639
39-0.245904-2.69370.004039
40-0.258904-2.83620.002681
41-0.271445-2.97350.00178
42-0.286528-3.13880.001068
43-0.299181-3.27740.000685
44-0.30896-3.38450.000482
45-0.314969-3.45030.000387
46-0.32055-3.51140.000314
47-0.321351-3.52020.000305
48-0.312067-3.41850.00043






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.97627510.69460
2-0.158263-1.73370.042771
30.0178170.19520.422795
4-0.070286-0.76990.221423
50.0159880.17510.430632
6-0.036654-0.40150.344374
70.0491520.53840.295638
8-0.035571-0.38970.348738
9-0.064599-0.70760.24027
10-0.053552-0.58660.279276
11-0.069183-0.75790.225008
12-0.026707-0.29260.38518
13-0.14181-1.55350.061474
140.0803340.880.190305
150.0079960.08760.465172
160.0343610.37640.353641
17-0.043038-0.47150.319085
180.1578881.72960.043139
19-0.096019-1.05180.147495
20-0.027939-0.30610.380045
21-0.0175-0.19170.42415
22-0.093563-1.02490.153728
23-0.10066-1.10270.136188
24-0.03598-0.39410.347089
25-0.061464-0.67330.251024
26-0.045938-0.50320.307862
270.0673930.73830.2309
28-0.108013-1.18320.119529
29-0.025032-0.27420.392198
30-0.103492-1.13370.12959
31-0.030834-0.33780.368064
320.0508160.55670.289399
330.1026161.12410.131606
34-0.021933-0.24030.405268
350.0712050.780.21846
36-0.082346-0.90210.184417
370.0279710.30640.379913
380.0249630.27350.392485
390.0442380.48460.314421
40-0.009828-0.10770.457221
41-0.007579-0.0830.466984
42-0.122307-1.33980.091419
430.0363180.39780.345726
440.0353050.38670.349815
450.0131430.1440.442883
46-0.017784-0.19480.422936
470.0928831.01750.155485
480.1780811.95080.026707

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.976275 & 10.6946 & 0 \tabularnewline
2 & -0.158263 & -1.7337 & 0.042771 \tabularnewline
3 & 0.017817 & 0.1952 & 0.422795 \tabularnewline
4 & -0.070286 & -0.7699 & 0.221423 \tabularnewline
5 & 0.015988 & 0.1751 & 0.430632 \tabularnewline
6 & -0.036654 & -0.4015 & 0.344374 \tabularnewline
7 & 0.049152 & 0.5384 & 0.295638 \tabularnewline
8 & -0.035571 & -0.3897 & 0.348738 \tabularnewline
9 & -0.064599 & -0.7076 & 0.24027 \tabularnewline
10 & -0.053552 & -0.5866 & 0.279276 \tabularnewline
11 & -0.069183 & -0.7579 & 0.225008 \tabularnewline
12 & -0.026707 & -0.2926 & 0.38518 \tabularnewline
13 & -0.14181 & -1.5535 & 0.061474 \tabularnewline
14 & 0.080334 & 0.88 & 0.190305 \tabularnewline
15 & 0.007996 & 0.0876 & 0.465172 \tabularnewline
16 & 0.034361 & 0.3764 & 0.353641 \tabularnewline
17 & -0.043038 & -0.4715 & 0.319085 \tabularnewline
18 & 0.157888 & 1.7296 & 0.043139 \tabularnewline
19 & -0.096019 & -1.0518 & 0.147495 \tabularnewline
20 & -0.027939 & -0.3061 & 0.380045 \tabularnewline
21 & -0.0175 & -0.1917 & 0.42415 \tabularnewline
22 & -0.093563 & -1.0249 & 0.153728 \tabularnewline
23 & -0.10066 & -1.1027 & 0.136188 \tabularnewline
24 & -0.03598 & -0.3941 & 0.347089 \tabularnewline
25 & -0.061464 & -0.6733 & 0.251024 \tabularnewline
26 & -0.045938 & -0.5032 & 0.307862 \tabularnewline
27 & 0.067393 & 0.7383 & 0.2309 \tabularnewline
28 & -0.108013 & -1.1832 & 0.119529 \tabularnewline
29 & -0.025032 & -0.2742 & 0.392198 \tabularnewline
30 & -0.103492 & -1.1337 & 0.12959 \tabularnewline
31 & -0.030834 & -0.3378 & 0.368064 \tabularnewline
32 & 0.050816 & 0.5567 & 0.289399 \tabularnewline
33 & 0.102616 & 1.1241 & 0.131606 \tabularnewline
34 & -0.021933 & -0.2403 & 0.405268 \tabularnewline
35 & 0.071205 & 0.78 & 0.21846 \tabularnewline
36 & -0.082346 & -0.9021 & 0.184417 \tabularnewline
37 & 0.027971 & 0.3064 & 0.379913 \tabularnewline
38 & 0.024963 & 0.2735 & 0.392485 \tabularnewline
39 & 0.044238 & 0.4846 & 0.314421 \tabularnewline
40 & -0.009828 & -0.1077 & 0.457221 \tabularnewline
41 & -0.007579 & -0.083 & 0.466984 \tabularnewline
42 & -0.122307 & -1.3398 & 0.091419 \tabularnewline
43 & 0.036318 & 0.3978 & 0.345726 \tabularnewline
44 & 0.035305 & 0.3867 & 0.349815 \tabularnewline
45 & 0.013143 & 0.144 & 0.442883 \tabularnewline
46 & -0.017784 & -0.1948 & 0.422936 \tabularnewline
47 & 0.092883 & 1.0175 & 0.155485 \tabularnewline
48 & 0.178081 & 1.9508 & 0.026707 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277975&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]0.976275[/C][C]10.6946[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.158263[/C][C]-1.7337[/C][C]0.042771[/C][/ROW]
[ROW][C]3[/C][C]0.017817[/C][C]0.1952[/C][C]0.422795[/C][/ROW]
[ROW][C]4[/C][C]-0.070286[/C][C]-0.7699[/C][C]0.221423[/C][/ROW]
[ROW][C]5[/C][C]0.015988[/C][C]0.1751[/C][C]0.430632[/C][/ROW]
[ROW][C]6[/C][C]-0.036654[/C][C]-0.4015[/C][C]0.344374[/C][/ROW]
[ROW][C]7[/C][C]0.049152[/C][C]0.5384[/C][C]0.295638[/C][/ROW]
[ROW][C]8[/C][C]-0.035571[/C][C]-0.3897[/C][C]0.348738[/C][/ROW]
[ROW][C]9[/C][C]-0.064599[/C][C]-0.7076[/C][C]0.24027[/C][/ROW]
[ROW][C]10[/C][C]-0.053552[/C][C]-0.5866[/C][C]0.279276[/C][/ROW]
[ROW][C]11[/C][C]-0.069183[/C][C]-0.7579[/C][C]0.225008[/C][/ROW]
[ROW][C]12[/C][C]-0.026707[/C][C]-0.2926[/C][C]0.38518[/C][/ROW]
[ROW][C]13[/C][C]-0.14181[/C][C]-1.5535[/C][C]0.061474[/C][/ROW]
[ROW][C]14[/C][C]0.080334[/C][C]0.88[/C][C]0.190305[/C][/ROW]
[ROW][C]15[/C][C]0.007996[/C][C]0.0876[/C][C]0.465172[/C][/ROW]
[ROW][C]16[/C][C]0.034361[/C][C]0.3764[/C][C]0.353641[/C][/ROW]
[ROW][C]17[/C][C]-0.043038[/C][C]-0.4715[/C][C]0.319085[/C][/ROW]
[ROW][C]18[/C][C]0.157888[/C][C]1.7296[/C][C]0.043139[/C][/ROW]
[ROW][C]19[/C][C]-0.096019[/C][C]-1.0518[/C][C]0.147495[/C][/ROW]
[ROW][C]20[/C][C]-0.027939[/C][C]-0.3061[/C][C]0.380045[/C][/ROW]
[ROW][C]21[/C][C]-0.0175[/C][C]-0.1917[/C][C]0.42415[/C][/ROW]
[ROW][C]22[/C][C]-0.093563[/C][C]-1.0249[/C][C]0.153728[/C][/ROW]
[ROW][C]23[/C][C]-0.10066[/C][C]-1.1027[/C][C]0.136188[/C][/ROW]
[ROW][C]24[/C][C]-0.03598[/C][C]-0.3941[/C][C]0.347089[/C][/ROW]
[ROW][C]25[/C][C]-0.061464[/C][C]-0.6733[/C][C]0.251024[/C][/ROW]
[ROW][C]26[/C][C]-0.045938[/C][C]-0.5032[/C][C]0.307862[/C][/ROW]
[ROW][C]27[/C][C]0.067393[/C][C]0.7383[/C][C]0.2309[/C][/ROW]
[ROW][C]28[/C][C]-0.108013[/C][C]-1.1832[/C][C]0.119529[/C][/ROW]
[ROW][C]29[/C][C]-0.025032[/C][C]-0.2742[/C][C]0.392198[/C][/ROW]
[ROW][C]30[/C][C]-0.103492[/C][C]-1.1337[/C][C]0.12959[/C][/ROW]
[ROW][C]31[/C][C]-0.030834[/C][C]-0.3378[/C][C]0.368064[/C][/ROW]
[ROW][C]32[/C][C]0.050816[/C][C]0.5567[/C][C]0.289399[/C][/ROW]
[ROW][C]33[/C][C]0.102616[/C][C]1.1241[/C][C]0.131606[/C][/ROW]
[ROW][C]34[/C][C]-0.021933[/C][C]-0.2403[/C][C]0.405268[/C][/ROW]
[ROW][C]35[/C][C]0.071205[/C][C]0.78[/C][C]0.21846[/C][/ROW]
[ROW][C]36[/C][C]-0.082346[/C][C]-0.9021[/C][C]0.184417[/C][/ROW]
[ROW][C]37[/C][C]0.027971[/C][C]0.3064[/C][C]0.379913[/C][/ROW]
[ROW][C]38[/C][C]0.024963[/C][C]0.2735[/C][C]0.392485[/C][/ROW]
[ROW][C]39[/C][C]0.044238[/C][C]0.4846[/C][C]0.314421[/C][/ROW]
[ROW][C]40[/C][C]-0.009828[/C][C]-0.1077[/C][C]0.457221[/C][/ROW]
[ROW][C]41[/C][C]-0.007579[/C][C]-0.083[/C][C]0.466984[/C][/ROW]
[ROW][C]42[/C][C]-0.122307[/C][C]-1.3398[/C][C]0.091419[/C][/ROW]
[ROW][C]43[/C][C]0.036318[/C][C]0.3978[/C][C]0.345726[/C][/ROW]
[ROW][C]44[/C][C]0.035305[/C][C]0.3867[/C][C]0.349815[/C][/ROW]
[ROW][C]45[/C][C]0.013143[/C][C]0.144[/C][C]0.442883[/C][/ROW]
[ROW][C]46[/C][C]-0.017784[/C][C]-0.1948[/C][C]0.422936[/C][/ROW]
[ROW][C]47[/C][C]0.092883[/C][C]1.0175[/C][C]0.155485[/C][/ROW]
[ROW][C]48[/C][C]0.178081[/C][C]1.9508[/C][C]0.026707[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277975&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277975&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
10.97627510.69460
2-0.158263-1.73370.042771
30.0178170.19520.422795
4-0.070286-0.76990.221423
50.0159880.17510.430632
6-0.036654-0.40150.344374
70.0491520.53840.295638
8-0.035571-0.38970.348738
9-0.064599-0.70760.24027
10-0.053552-0.58660.279276
11-0.069183-0.75790.225008
12-0.026707-0.29260.38518
13-0.14181-1.55350.061474
140.0803340.880.190305
150.0079960.08760.465172
160.0343610.37640.353641
17-0.043038-0.47150.319085
180.1578881.72960.043139
19-0.096019-1.05180.147495
20-0.027939-0.30610.380045
21-0.0175-0.19170.42415
22-0.093563-1.02490.153728
23-0.10066-1.10270.136188
24-0.03598-0.39410.347089
25-0.061464-0.67330.251024
26-0.045938-0.50320.307862
270.0673930.73830.2309
28-0.108013-1.18320.119529
29-0.025032-0.27420.392198
30-0.103492-1.13370.12959
31-0.030834-0.33780.368064
320.0508160.55670.289399
330.1026161.12410.131606
34-0.021933-0.24030.405268
350.0712050.780.21846
36-0.082346-0.90210.184417
370.0279710.30640.379913
380.0249630.27350.392485
390.0442380.48460.314421
40-0.009828-0.10770.457221
41-0.007579-0.0830.466984
42-0.122307-1.33980.091419
430.0363180.39780.345726
440.0353050.38670.349815
450.0131430.1440.442883
46-0.017784-0.19480.422936
470.0928831.01750.155485
480.1780811.95080.026707


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; 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)
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,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')