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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, 14 Dec 2017 10:27:42 +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/14/t1513243730lu94fkgt0uc6ozz.htm/, Retrieved Tue, 14 May 2024 06:54:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309420, Retrieved Tue, 14 May 2024 06:54:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [autocorrelatie fu...] [2017-12-14 09:27:42] [5c76e56d84d1440d36aad135bd2f9339] [Current]
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Dataseries X:
18142
8613
8347
7054
5179
6785
7887
6926
6355
7533
6727
8215
13880
10484
9847
6952
9393
12870
9330
14726
10176.66667
7815
6419
9900
9999.833333
14523
12419
8923
11857
12676
14873
11711
15243
9751
7631
8161
10435
15188
10237
11642
16513
18632
15526
14991
10365
10369
10912
14476.83333
19891
17448
17876
11414
9452
15509
11286
13318
9298.833333
6850
4497
4333
7301
4323
6033
4513
4442
7666
6260
5339
3686
4549
3675
7356
8341
20001
9554
6334
4313
4161
7835
9109
7691
5091
7407
11632
17611
9481
7603
4485
10381
8796
10132
10163
17969
6695




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=309420&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=309420&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309420&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
1-0.227684-2.19570.0153
2-0.008753-0.08440.466454
3-0.248511-2.39660.009275
4-0.045299-0.43680.331617
50.0321150.30970.37874
60.0639340.61660.269515
70.0885360.85380.197703
8-0.009584-0.09240.46328
9-0.087301-0.84190.201002
10-0.1144-1.10320.136386
110.122691.18320.119878
120.028380.27370.392466
130.1470171.41780.079799
14-0.150141-1.44790.075502
15-0.125095-1.20640.115366
16-0.048439-0.46710.320749
170.0231780.22350.411812
180.1120191.08030.141407
190.107051.03240.152292
20-0.016496-0.15910.436973
21-0.114945-1.10850.135255
22-0.193928-1.87020.032303
230.1723221.66180.049959
240.0199740.19260.423839
250.1502991.44940.07529
26-0.087075-0.83970.20161
27-0.146169-1.40960.080996
28-0.030473-0.29390.384755
29-0.024096-0.23240.40838
300.1383361.33410.09272
310.0203090.19590.422575
320.0124650.12020.452288
33-0.079262-0.76440.22329
34-0.020065-0.19350.423496
35-0.044568-0.42980.334167
360.1533511.47890.071278
370.057750.55690.28946
38-0.113797-1.09740.137646
39-0.055862-0.53870.295687
40-0.188772-1.82050.035953
410.1649671.59090.057514
420.0251390.24240.40449
430.1654011.59510.057045
44-0.011056-0.10660.45766
45-0.102525-0.98870.162684
46-0.124601-1.20160.116284
470.0074560.07190.471416
480.1128791.08860.139579

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.227684 & -2.1957 & 0.0153 \tabularnewline
2 & -0.008753 & -0.0844 & 0.466454 \tabularnewline
3 & -0.248511 & -2.3966 & 0.009275 \tabularnewline
4 & -0.045299 & -0.4368 & 0.331617 \tabularnewline
5 & 0.032115 & 0.3097 & 0.37874 \tabularnewline
6 & 0.063934 & 0.6166 & 0.269515 \tabularnewline
7 & 0.088536 & 0.8538 & 0.197703 \tabularnewline
8 & -0.009584 & -0.0924 & 0.46328 \tabularnewline
9 & -0.087301 & -0.8419 & 0.201002 \tabularnewline
10 & -0.1144 & -1.1032 & 0.136386 \tabularnewline
11 & 0.12269 & 1.1832 & 0.119878 \tabularnewline
12 & 0.02838 & 0.2737 & 0.392466 \tabularnewline
13 & 0.147017 & 1.4178 & 0.079799 \tabularnewline
14 & -0.150141 & -1.4479 & 0.075502 \tabularnewline
15 & -0.125095 & -1.2064 & 0.115366 \tabularnewline
16 & -0.048439 & -0.4671 & 0.320749 \tabularnewline
17 & 0.023178 & 0.2235 & 0.411812 \tabularnewline
18 & 0.112019 & 1.0803 & 0.141407 \tabularnewline
19 & 0.10705 & 1.0324 & 0.152292 \tabularnewline
20 & -0.016496 & -0.1591 & 0.436973 \tabularnewline
21 & -0.114945 & -1.1085 & 0.135255 \tabularnewline
22 & -0.193928 & -1.8702 & 0.032303 \tabularnewline
23 & 0.172322 & 1.6618 & 0.049959 \tabularnewline
24 & 0.019974 & 0.1926 & 0.423839 \tabularnewline
25 & 0.150299 & 1.4494 & 0.07529 \tabularnewline
26 & -0.087075 & -0.8397 & 0.20161 \tabularnewline
27 & -0.146169 & -1.4096 & 0.080996 \tabularnewline
28 & -0.030473 & -0.2939 & 0.384755 \tabularnewline
29 & -0.024096 & -0.2324 & 0.40838 \tabularnewline
30 & 0.138336 & 1.3341 & 0.09272 \tabularnewline
31 & 0.020309 & 0.1959 & 0.422575 \tabularnewline
32 & 0.012465 & 0.1202 & 0.452288 \tabularnewline
33 & -0.079262 & -0.7644 & 0.22329 \tabularnewline
34 & -0.020065 & -0.1935 & 0.423496 \tabularnewline
35 & -0.044568 & -0.4298 & 0.334167 \tabularnewline
36 & 0.153351 & 1.4789 & 0.071278 \tabularnewline
37 & 0.05775 & 0.5569 & 0.28946 \tabularnewline
38 & -0.113797 & -1.0974 & 0.137646 \tabularnewline
39 & -0.055862 & -0.5387 & 0.295687 \tabularnewline
40 & -0.188772 & -1.8205 & 0.035953 \tabularnewline
41 & 0.164967 & 1.5909 & 0.057514 \tabularnewline
42 & 0.025139 & 0.2424 & 0.40449 \tabularnewline
43 & 0.165401 & 1.5951 & 0.057045 \tabularnewline
44 & -0.011056 & -0.1066 & 0.45766 \tabularnewline
45 & -0.102525 & -0.9887 & 0.162684 \tabularnewline
46 & -0.124601 & -1.2016 & 0.116284 \tabularnewline
47 & 0.007456 & 0.0719 & 0.471416 \tabularnewline
48 & 0.112879 & 1.0886 & 0.139579 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309420&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]-0.227684[/C][C]-2.1957[/C][C]0.0153[/C][/ROW]
[ROW][C]2[/C][C]-0.008753[/C][C]-0.0844[/C][C]0.466454[/C][/ROW]
[ROW][C]3[/C][C]-0.248511[/C][C]-2.3966[/C][C]0.009275[/C][/ROW]
[ROW][C]4[/C][C]-0.045299[/C][C]-0.4368[/C][C]0.331617[/C][/ROW]
[ROW][C]5[/C][C]0.032115[/C][C]0.3097[/C][C]0.37874[/C][/ROW]
[ROW][C]6[/C][C]0.063934[/C][C]0.6166[/C][C]0.269515[/C][/ROW]
[ROW][C]7[/C][C]0.088536[/C][C]0.8538[/C][C]0.197703[/C][/ROW]
[ROW][C]8[/C][C]-0.009584[/C][C]-0.0924[/C][C]0.46328[/C][/ROW]
[ROW][C]9[/C][C]-0.087301[/C][C]-0.8419[/C][C]0.201002[/C][/ROW]
[ROW][C]10[/C][C]-0.1144[/C][C]-1.1032[/C][C]0.136386[/C][/ROW]
[ROW][C]11[/C][C]0.12269[/C][C]1.1832[/C][C]0.119878[/C][/ROW]
[ROW][C]12[/C][C]0.02838[/C][C]0.2737[/C][C]0.392466[/C][/ROW]
[ROW][C]13[/C][C]0.147017[/C][C]1.4178[/C][C]0.079799[/C][/ROW]
[ROW][C]14[/C][C]-0.150141[/C][C]-1.4479[/C][C]0.075502[/C][/ROW]
[ROW][C]15[/C][C]-0.125095[/C][C]-1.2064[/C][C]0.115366[/C][/ROW]
[ROW][C]16[/C][C]-0.048439[/C][C]-0.4671[/C][C]0.320749[/C][/ROW]
[ROW][C]17[/C][C]0.023178[/C][C]0.2235[/C][C]0.411812[/C][/ROW]
[ROW][C]18[/C][C]0.112019[/C][C]1.0803[/C][C]0.141407[/C][/ROW]
[ROW][C]19[/C][C]0.10705[/C][C]1.0324[/C][C]0.152292[/C][/ROW]
[ROW][C]20[/C][C]-0.016496[/C][C]-0.1591[/C][C]0.436973[/C][/ROW]
[ROW][C]21[/C][C]-0.114945[/C][C]-1.1085[/C][C]0.135255[/C][/ROW]
[ROW][C]22[/C][C]-0.193928[/C][C]-1.8702[/C][C]0.032303[/C][/ROW]
[ROW][C]23[/C][C]0.172322[/C][C]1.6618[/C][C]0.049959[/C][/ROW]
[ROW][C]24[/C][C]0.019974[/C][C]0.1926[/C][C]0.423839[/C][/ROW]
[ROW][C]25[/C][C]0.150299[/C][C]1.4494[/C][C]0.07529[/C][/ROW]
[ROW][C]26[/C][C]-0.087075[/C][C]-0.8397[/C][C]0.20161[/C][/ROW]
[ROW][C]27[/C][C]-0.146169[/C][C]-1.4096[/C][C]0.080996[/C][/ROW]
[ROW][C]28[/C][C]-0.030473[/C][C]-0.2939[/C][C]0.384755[/C][/ROW]
[ROW][C]29[/C][C]-0.024096[/C][C]-0.2324[/C][C]0.40838[/C][/ROW]
[ROW][C]30[/C][C]0.138336[/C][C]1.3341[/C][C]0.09272[/C][/ROW]
[ROW][C]31[/C][C]0.020309[/C][C]0.1959[/C][C]0.422575[/C][/ROW]
[ROW][C]32[/C][C]0.012465[/C][C]0.1202[/C][C]0.452288[/C][/ROW]
[ROW][C]33[/C][C]-0.079262[/C][C]-0.7644[/C][C]0.22329[/C][/ROW]
[ROW][C]34[/C][C]-0.020065[/C][C]-0.1935[/C][C]0.423496[/C][/ROW]
[ROW][C]35[/C][C]-0.044568[/C][C]-0.4298[/C][C]0.334167[/C][/ROW]
[ROW][C]36[/C][C]0.153351[/C][C]1.4789[/C][C]0.071278[/C][/ROW]
[ROW][C]37[/C][C]0.05775[/C][C]0.5569[/C][C]0.28946[/C][/ROW]
[ROW][C]38[/C][C]-0.113797[/C][C]-1.0974[/C][C]0.137646[/C][/ROW]
[ROW][C]39[/C][C]-0.055862[/C][C]-0.5387[/C][C]0.295687[/C][/ROW]
[ROW][C]40[/C][C]-0.188772[/C][C]-1.8205[/C][C]0.035953[/C][/ROW]
[ROW][C]41[/C][C]0.164967[/C][C]1.5909[/C][C]0.057514[/C][/ROW]
[ROW][C]42[/C][C]0.025139[/C][C]0.2424[/C][C]0.40449[/C][/ROW]
[ROW][C]43[/C][C]0.165401[/C][C]1.5951[/C][C]0.057045[/C][/ROW]
[ROW][C]44[/C][C]-0.011056[/C][C]-0.1066[/C][C]0.45766[/C][/ROW]
[ROW][C]45[/C][C]-0.102525[/C][C]-0.9887[/C][C]0.162684[/C][/ROW]
[ROW][C]46[/C][C]-0.124601[/C][C]-1.2016[/C][C]0.116284[/C][/ROW]
[ROW][C]47[/C][C]0.007456[/C][C]0.0719[/C][C]0.471416[/C][/ROW]
[ROW][C]48[/C][C]0.112879[/C][C]1.0886[/C][C]0.139579[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309420&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309420&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
1-0.227684-2.19570.0153
2-0.008753-0.08440.466454
3-0.248511-2.39660.009275
4-0.045299-0.43680.331617
50.0321150.30970.37874
60.0639340.61660.269515
70.0885360.85380.197703
8-0.009584-0.09240.46328
9-0.087301-0.84190.201002
10-0.1144-1.10320.136386
110.122691.18320.119878
120.028380.27370.392466
130.1470171.41780.079799
14-0.150141-1.44790.075502
15-0.125095-1.20640.115366
16-0.048439-0.46710.320749
170.0231780.22350.411812
180.1120191.08030.141407
190.107051.03240.152292
20-0.016496-0.15910.436973
21-0.114945-1.10850.135255
22-0.193928-1.87020.032303
230.1723221.66180.049959
240.0199740.19260.423839
250.1502991.44940.07529
26-0.087075-0.83970.20161
27-0.146169-1.40960.080996
28-0.030473-0.29390.384755
29-0.024096-0.23240.40838
300.1383361.33410.09272
310.0203090.19590.422575
320.0124650.12020.452288
33-0.079262-0.76440.22329
34-0.020065-0.19350.423496
35-0.044568-0.42980.334167
360.1533511.47890.071278
370.057750.55690.28946
38-0.113797-1.09740.137646
39-0.055862-0.53870.295687
40-0.188772-1.82050.035953
410.1649671.59090.057514
420.0251390.24240.40449
430.1654011.59510.057045
44-0.011056-0.10660.45766
45-0.102525-0.98870.162684
46-0.124601-1.20160.116284
470.0074560.07190.471416
480.1128791.08860.139579







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.227684-2.19570.0153
2-0.063907-0.61630.269604
3-0.280827-2.70820.004026
4-0.201251-1.94080.027655
5-0.084299-0.8130.209161
6-0.049613-0.47840.316728
70.0349450.3370.368437
80.0219560.21170.416388
9-0.061339-0.59150.277799
10-0.128166-1.2360.109788
110.0708130.68290.248185
120.0281170.27110.393439
130.1277521.2320.110528
14-0.046873-0.4520.326153
15-0.147026-1.41790.079785
16-0.077738-0.74970.227671
17-0.071275-0.68740.246786
18-0.025349-0.24450.403708
190.0647820.62470.266839
200.023960.23110.408887
21-0.04272-0.4120.340653
22-0.190076-1.8330.034999
230.0999790.96420.168732
24-0.027281-0.26310.396534
250.072870.70270.241988
260.0031020.02990.488098
27-0.133308-1.28560.100891
28-0.028685-0.27660.391338
29-0.082093-0.79170.215283
30-0.019024-0.18350.427419
31-0.068627-0.66180.254863
32-0.054831-0.52880.299112
330.0091250.0880.465034
340.0140030.1350.446437
35-0.002455-0.02370.490583
360.0184740.17820.429495
370.0796130.76780.222289
38-0.103204-0.99530.161097
39-0.04881-0.47070.319476
40-0.161667-1.55910.061189
41-0.014493-0.13980.444573
42-0.061242-0.59060.278112
430.007720.07440.470407
440.0352690.34010.367266
45-0.002837-0.02740.489116
46-0.07071-0.68190.248497
470.0082190.07930.468496
480.0170170.16410.435002

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.227684 & -2.1957 & 0.0153 \tabularnewline
2 & -0.063907 & -0.6163 & 0.269604 \tabularnewline
3 & -0.280827 & -2.7082 & 0.004026 \tabularnewline
4 & -0.201251 & -1.9408 & 0.027655 \tabularnewline
5 & -0.084299 & -0.813 & 0.209161 \tabularnewline
6 & -0.049613 & -0.4784 & 0.316728 \tabularnewline
7 & 0.034945 & 0.337 & 0.368437 \tabularnewline
8 & 0.021956 & 0.2117 & 0.416388 \tabularnewline
9 & -0.061339 & -0.5915 & 0.277799 \tabularnewline
10 & -0.128166 & -1.236 & 0.109788 \tabularnewline
11 & 0.070813 & 0.6829 & 0.248185 \tabularnewline
12 & 0.028117 & 0.2711 & 0.393439 \tabularnewline
13 & 0.127752 & 1.232 & 0.110528 \tabularnewline
14 & -0.046873 & -0.452 & 0.326153 \tabularnewline
15 & -0.147026 & -1.4179 & 0.079785 \tabularnewline
16 & -0.077738 & -0.7497 & 0.227671 \tabularnewline
17 & -0.071275 & -0.6874 & 0.246786 \tabularnewline
18 & -0.025349 & -0.2445 & 0.403708 \tabularnewline
19 & 0.064782 & 0.6247 & 0.266839 \tabularnewline
20 & 0.02396 & 0.2311 & 0.408887 \tabularnewline
21 & -0.04272 & -0.412 & 0.340653 \tabularnewline
22 & -0.190076 & -1.833 & 0.034999 \tabularnewline
23 & 0.099979 & 0.9642 & 0.168732 \tabularnewline
24 & -0.027281 & -0.2631 & 0.396534 \tabularnewline
25 & 0.07287 & 0.7027 & 0.241988 \tabularnewline
26 & 0.003102 & 0.0299 & 0.488098 \tabularnewline
27 & -0.133308 & -1.2856 & 0.100891 \tabularnewline
28 & -0.028685 & -0.2766 & 0.391338 \tabularnewline
29 & -0.082093 & -0.7917 & 0.215283 \tabularnewline
30 & -0.019024 & -0.1835 & 0.427419 \tabularnewline
31 & -0.068627 & -0.6618 & 0.254863 \tabularnewline
32 & -0.054831 & -0.5288 & 0.299112 \tabularnewline
33 & 0.009125 & 0.088 & 0.465034 \tabularnewline
34 & 0.014003 & 0.135 & 0.446437 \tabularnewline
35 & -0.002455 & -0.0237 & 0.490583 \tabularnewline
36 & 0.018474 & 0.1782 & 0.429495 \tabularnewline
37 & 0.079613 & 0.7678 & 0.222289 \tabularnewline
38 & -0.103204 & -0.9953 & 0.161097 \tabularnewline
39 & -0.04881 & -0.4707 & 0.319476 \tabularnewline
40 & -0.161667 & -1.5591 & 0.061189 \tabularnewline
41 & -0.014493 & -0.1398 & 0.444573 \tabularnewline
42 & -0.061242 & -0.5906 & 0.278112 \tabularnewline
43 & 0.00772 & 0.0744 & 0.470407 \tabularnewline
44 & 0.035269 & 0.3401 & 0.367266 \tabularnewline
45 & -0.002837 & -0.0274 & 0.489116 \tabularnewline
46 & -0.07071 & -0.6819 & 0.248497 \tabularnewline
47 & 0.008219 & 0.0793 & 0.468496 \tabularnewline
48 & 0.017017 & 0.1641 & 0.435002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309420&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]-0.227684[/C][C]-2.1957[/C][C]0.0153[/C][/ROW]
[ROW][C]2[/C][C]-0.063907[/C][C]-0.6163[/C][C]0.269604[/C][/ROW]
[ROW][C]3[/C][C]-0.280827[/C][C]-2.7082[/C][C]0.004026[/C][/ROW]
[ROW][C]4[/C][C]-0.201251[/C][C]-1.9408[/C][C]0.027655[/C][/ROW]
[ROW][C]5[/C][C]-0.084299[/C][C]-0.813[/C][C]0.209161[/C][/ROW]
[ROW][C]6[/C][C]-0.049613[/C][C]-0.4784[/C][C]0.316728[/C][/ROW]
[ROW][C]7[/C][C]0.034945[/C][C]0.337[/C][C]0.368437[/C][/ROW]
[ROW][C]8[/C][C]0.021956[/C][C]0.2117[/C][C]0.416388[/C][/ROW]
[ROW][C]9[/C][C]-0.061339[/C][C]-0.5915[/C][C]0.277799[/C][/ROW]
[ROW][C]10[/C][C]-0.128166[/C][C]-1.236[/C][C]0.109788[/C][/ROW]
[ROW][C]11[/C][C]0.070813[/C][C]0.6829[/C][C]0.248185[/C][/ROW]
[ROW][C]12[/C][C]0.028117[/C][C]0.2711[/C][C]0.393439[/C][/ROW]
[ROW][C]13[/C][C]0.127752[/C][C]1.232[/C][C]0.110528[/C][/ROW]
[ROW][C]14[/C][C]-0.046873[/C][C]-0.452[/C][C]0.326153[/C][/ROW]
[ROW][C]15[/C][C]-0.147026[/C][C]-1.4179[/C][C]0.079785[/C][/ROW]
[ROW][C]16[/C][C]-0.077738[/C][C]-0.7497[/C][C]0.227671[/C][/ROW]
[ROW][C]17[/C][C]-0.071275[/C][C]-0.6874[/C][C]0.246786[/C][/ROW]
[ROW][C]18[/C][C]-0.025349[/C][C]-0.2445[/C][C]0.403708[/C][/ROW]
[ROW][C]19[/C][C]0.064782[/C][C]0.6247[/C][C]0.266839[/C][/ROW]
[ROW][C]20[/C][C]0.02396[/C][C]0.2311[/C][C]0.408887[/C][/ROW]
[ROW][C]21[/C][C]-0.04272[/C][C]-0.412[/C][C]0.340653[/C][/ROW]
[ROW][C]22[/C][C]-0.190076[/C][C]-1.833[/C][C]0.034999[/C][/ROW]
[ROW][C]23[/C][C]0.099979[/C][C]0.9642[/C][C]0.168732[/C][/ROW]
[ROW][C]24[/C][C]-0.027281[/C][C]-0.2631[/C][C]0.396534[/C][/ROW]
[ROW][C]25[/C][C]0.07287[/C][C]0.7027[/C][C]0.241988[/C][/ROW]
[ROW][C]26[/C][C]0.003102[/C][C]0.0299[/C][C]0.488098[/C][/ROW]
[ROW][C]27[/C][C]-0.133308[/C][C]-1.2856[/C][C]0.100891[/C][/ROW]
[ROW][C]28[/C][C]-0.028685[/C][C]-0.2766[/C][C]0.391338[/C][/ROW]
[ROW][C]29[/C][C]-0.082093[/C][C]-0.7917[/C][C]0.215283[/C][/ROW]
[ROW][C]30[/C][C]-0.019024[/C][C]-0.1835[/C][C]0.427419[/C][/ROW]
[ROW][C]31[/C][C]-0.068627[/C][C]-0.6618[/C][C]0.254863[/C][/ROW]
[ROW][C]32[/C][C]-0.054831[/C][C]-0.5288[/C][C]0.299112[/C][/ROW]
[ROW][C]33[/C][C]0.009125[/C][C]0.088[/C][C]0.465034[/C][/ROW]
[ROW][C]34[/C][C]0.014003[/C][C]0.135[/C][C]0.446437[/C][/ROW]
[ROW][C]35[/C][C]-0.002455[/C][C]-0.0237[/C][C]0.490583[/C][/ROW]
[ROW][C]36[/C][C]0.018474[/C][C]0.1782[/C][C]0.429495[/C][/ROW]
[ROW][C]37[/C][C]0.079613[/C][C]0.7678[/C][C]0.222289[/C][/ROW]
[ROW][C]38[/C][C]-0.103204[/C][C]-0.9953[/C][C]0.161097[/C][/ROW]
[ROW][C]39[/C][C]-0.04881[/C][C]-0.4707[/C][C]0.319476[/C][/ROW]
[ROW][C]40[/C][C]-0.161667[/C][C]-1.5591[/C][C]0.061189[/C][/ROW]
[ROW][C]41[/C][C]-0.014493[/C][C]-0.1398[/C][C]0.444573[/C][/ROW]
[ROW][C]42[/C][C]-0.061242[/C][C]-0.5906[/C][C]0.278112[/C][/ROW]
[ROW][C]43[/C][C]0.00772[/C][C]0.0744[/C][C]0.470407[/C][/ROW]
[ROW][C]44[/C][C]0.035269[/C][C]0.3401[/C][C]0.367266[/C][/ROW]
[ROW][C]45[/C][C]-0.002837[/C][C]-0.0274[/C][C]0.489116[/C][/ROW]
[ROW][C]46[/C][C]-0.07071[/C][C]-0.6819[/C][C]0.248497[/C][/ROW]
[ROW][C]47[/C][C]0.008219[/C][C]0.0793[/C][C]0.468496[/C][/ROW]
[ROW][C]48[/C][C]0.017017[/C][C]0.1641[/C][C]0.435002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309420&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309420&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
1-0.227684-2.19570.0153
2-0.063907-0.61630.269604
3-0.280827-2.70820.004026
4-0.201251-1.94080.027655
5-0.084299-0.8130.209161
6-0.049613-0.47840.316728
70.0349450.3370.368437
80.0219560.21170.416388
9-0.061339-0.59150.277799
10-0.128166-1.2360.109788
110.0708130.68290.248185
120.0281170.27110.393439
130.1277521.2320.110528
14-0.046873-0.4520.326153
15-0.147026-1.41790.079785
16-0.077738-0.74970.227671
17-0.071275-0.68740.246786
18-0.025349-0.24450.403708
190.0647820.62470.266839
200.023960.23110.408887
21-0.04272-0.4120.340653
22-0.190076-1.8330.034999
230.0999790.96420.168732
24-0.027281-0.26310.396534
250.072870.70270.241988
260.0031020.02990.488098
27-0.133308-1.28560.100891
28-0.028685-0.27660.391338
29-0.082093-0.79170.215283
30-0.019024-0.18350.427419
31-0.068627-0.66180.254863
32-0.054831-0.52880.299112
330.0091250.0880.465034
340.0140030.1350.446437
35-0.002455-0.02370.490583
360.0184740.17820.429495
370.0796130.76780.222289
38-0.103204-0.99530.161097
39-0.04881-0.47070.319476
40-0.161667-1.55910.061189
41-0.014493-0.13980.444573
42-0.061242-0.59060.278112
430.007720.07440.470407
440.0352690.34010.367266
45-0.002837-0.02740.489116
46-0.07071-0.68190.248497
470.0082190.07930.468496
480.0170170.16410.435002



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
par8 <- ''
par7 <- ''
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '1'
par2 <- '1'
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')