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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 computationTue, 04 Dec 2012 12:49:19 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/04/t1354643372zyljf79v1qpdya6.htm/, Retrieved Thu, 28 Mar 2024 16:28:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196433, Retrieved Thu, 28 Mar 2024 16:28:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [workshop 9] [2012-12-04 17:49:19] [468d5fc6f63a6d6dca168804c24af07d] [Current]
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Dataseries X:
655362
873127
1107897
1555964
1671159
1493308
2957796
2638691
1305669
1280496
921900
867888
652586
913831
1108544
1555827
1699283
1509458
3268975
2425016
1312703
1365498
934453
775019
651142
843192
1146766
1652601
1465906
1652734
2922334
2702805
1458956
1410363
1019279
936574
708917
885295
1099663
1576220
1487870
1488635
2882530
2677026
1404398
1344370
936865
872705
628151
953712
1160384
1400618
1661511
1495347
2918786
2775677
1407026
1370199
964526
850851
683118
847224
1073256
1514326
1503734
1507712
2865698
2788128
1391596
1366378
946295
859626




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196433&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196433&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196433&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 time3 seconds
R Server'George Udny Yule' @ yule.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.692354-5.31811e-06
20.2314561.77780.040291
30.0053560.04110.483661
4-0.084512-0.64910.259381
50.0966080.74210.230498
6-0.016336-0.12550.450285
7-0.086927-0.66770.253465
80.0428890.32940.371495
90.0750110.57620.283347
10-0.226283-1.73810.043704
110.3853712.96010.002212
12-0.434989-3.34120.000726
130.2484541.90840.030604
14-0.041019-0.31510.376909
15-0.011111-0.08530.466139
16-0.013262-0.10190.459603
17-0.017221-0.13230.447609
180.0904650.69490.244931
19-0.051603-0.39640.34663
20-0.038426-0.29520.384456
210.1054380.80990.210631
22-0.141666-1.08820.140476
230.1658981.27430.103779
24-0.11698-0.89850.186274
250.0180460.13860.445114
260.0453860.34860.36431
27-0.07537-0.57890.282422
280.0578350.44420.329247
290.0384170.29510.384481
30-0.157094-1.20670.116189
310.0960830.7380.231712
320.1138620.87460.192672
33-0.265981-2.0430.022762
340.2767192.12550.01887
35-0.214406-1.64690.05245
360.1283680.9860.164076
37-0.034898-0.26810.394795
38-0.011564-0.08880.464762
390.01940.1490.441027
40-0.002937-0.02260.49104
41-0.038172-0.29320.385199
420.0729840.56060.288597
43-0.025332-0.19460.423194
44-0.077477-0.59510.277022
450.1238070.9510.172747
46-0.099256-0.76240.22443
470.0626470.48120.316076
48-0.041375-0.31780.375876

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.692354 & -5.3181 & 1e-06 \tabularnewline
2 & 0.231456 & 1.7778 & 0.040291 \tabularnewline
3 & 0.005356 & 0.0411 & 0.483661 \tabularnewline
4 & -0.084512 & -0.6491 & 0.259381 \tabularnewline
5 & 0.096608 & 0.7421 & 0.230498 \tabularnewline
6 & -0.016336 & -0.1255 & 0.450285 \tabularnewline
7 & -0.086927 & -0.6677 & 0.253465 \tabularnewline
8 & 0.042889 & 0.3294 & 0.371495 \tabularnewline
9 & 0.075011 & 0.5762 & 0.283347 \tabularnewline
10 & -0.226283 & -1.7381 & 0.043704 \tabularnewline
11 & 0.385371 & 2.9601 & 0.002212 \tabularnewline
12 & -0.434989 & -3.3412 & 0.000726 \tabularnewline
13 & 0.248454 & 1.9084 & 0.030604 \tabularnewline
14 & -0.041019 & -0.3151 & 0.376909 \tabularnewline
15 & -0.011111 & -0.0853 & 0.466139 \tabularnewline
16 & -0.013262 & -0.1019 & 0.459603 \tabularnewline
17 & -0.017221 & -0.1323 & 0.447609 \tabularnewline
18 & 0.090465 & 0.6949 & 0.244931 \tabularnewline
19 & -0.051603 & -0.3964 & 0.34663 \tabularnewline
20 & -0.038426 & -0.2952 & 0.384456 \tabularnewline
21 & 0.105438 & 0.8099 & 0.210631 \tabularnewline
22 & -0.141666 & -1.0882 & 0.140476 \tabularnewline
23 & 0.165898 & 1.2743 & 0.103779 \tabularnewline
24 & -0.11698 & -0.8985 & 0.186274 \tabularnewline
25 & 0.018046 & 0.1386 & 0.445114 \tabularnewline
26 & 0.045386 & 0.3486 & 0.36431 \tabularnewline
27 & -0.07537 & -0.5789 & 0.282422 \tabularnewline
28 & 0.057835 & 0.4442 & 0.329247 \tabularnewline
29 & 0.038417 & 0.2951 & 0.384481 \tabularnewline
30 & -0.157094 & -1.2067 & 0.116189 \tabularnewline
31 & 0.096083 & 0.738 & 0.231712 \tabularnewline
32 & 0.113862 & 0.8746 & 0.192672 \tabularnewline
33 & -0.265981 & -2.043 & 0.022762 \tabularnewline
34 & 0.276719 & 2.1255 & 0.01887 \tabularnewline
35 & -0.214406 & -1.6469 & 0.05245 \tabularnewline
36 & 0.128368 & 0.986 & 0.164076 \tabularnewline
37 & -0.034898 & -0.2681 & 0.394795 \tabularnewline
38 & -0.011564 & -0.0888 & 0.464762 \tabularnewline
39 & 0.0194 & 0.149 & 0.441027 \tabularnewline
40 & -0.002937 & -0.0226 & 0.49104 \tabularnewline
41 & -0.038172 & -0.2932 & 0.385199 \tabularnewline
42 & 0.072984 & 0.5606 & 0.288597 \tabularnewline
43 & -0.025332 & -0.1946 & 0.423194 \tabularnewline
44 & -0.077477 & -0.5951 & 0.277022 \tabularnewline
45 & 0.123807 & 0.951 & 0.172747 \tabularnewline
46 & -0.099256 & -0.7624 & 0.22443 \tabularnewline
47 & 0.062647 & 0.4812 & 0.316076 \tabularnewline
48 & -0.041375 & -0.3178 & 0.375876 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196433&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]-0.692354[/C][C]-5.3181[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.231456[/C][C]1.7778[/C][C]0.040291[/C][/ROW]
[ROW][C]3[/C][C]0.005356[/C][C]0.0411[/C][C]0.483661[/C][/ROW]
[ROW][C]4[/C][C]-0.084512[/C][C]-0.6491[/C][C]0.259381[/C][/ROW]
[ROW][C]5[/C][C]0.096608[/C][C]0.7421[/C][C]0.230498[/C][/ROW]
[ROW][C]6[/C][C]-0.016336[/C][C]-0.1255[/C][C]0.450285[/C][/ROW]
[ROW][C]7[/C][C]-0.086927[/C][C]-0.6677[/C][C]0.253465[/C][/ROW]
[ROW][C]8[/C][C]0.042889[/C][C]0.3294[/C][C]0.371495[/C][/ROW]
[ROW][C]9[/C][C]0.075011[/C][C]0.5762[/C][C]0.283347[/C][/ROW]
[ROW][C]10[/C][C]-0.226283[/C][C]-1.7381[/C][C]0.043704[/C][/ROW]
[ROW][C]11[/C][C]0.385371[/C][C]2.9601[/C][C]0.002212[/C][/ROW]
[ROW][C]12[/C][C]-0.434989[/C][C]-3.3412[/C][C]0.000726[/C][/ROW]
[ROW][C]13[/C][C]0.248454[/C][C]1.9084[/C][C]0.030604[/C][/ROW]
[ROW][C]14[/C][C]-0.041019[/C][C]-0.3151[/C][C]0.376909[/C][/ROW]
[ROW][C]15[/C][C]-0.011111[/C][C]-0.0853[/C][C]0.466139[/C][/ROW]
[ROW][C]16[/C][C]-0.013262[/C][C]-0.1019[/C][C]0.459603[/C][/ROW]
[ROW][C]17[/C][C]-0.017221[/C][C]-0.1323[/C][C]0.447609[/C][/ROW]
[ROW][C]18[/C][C]0.090465[/C][C]0.6949[/C][C]0.244931[/C][/ROW]
[ROW][C]19[/C][C]-0.051603[/C][C]-0.3964[/C][C]0.34663[/C][/ROW]
[ROW][C]20[/C][C]-0.038426[/C][C]-0.2952[/C][C]0.384456[/C][/ROW]
[ROW][C]21[/C][C]0.105438[/C][C]0.8099[/C][C]0.210631[/C][/ROW]
[ROW][C]22[/C][C]-0.141666[/C][C]-1.0882[/C][C]0.140476[/C][/ROW]
[ROW][C]23[/C][C]0.165898[/C][C]1.2743[/C][C]0.103779[/C][/ROW]
[ROW][C]24[/C][C]-0.11698[/C][C]-0.8985[/C][C]0.186274[/C][/ROW]
[ROW][C]25[/C][C]0.018046[/C][C]0.1386[/C][C]0.445114[/C][/ROW]
[ROW][C]26[/C][C]0.045386[/C][C]0.3486[/C][C]0.36431[/C][/ROW]
[ROW][C]27[/C][C]-0.07537[/C][C]-0.5789[/C][C]0.282422[/C][/ROW]
[ROW][C]28[/C][C]0.057835[/C][C]0.4442[/C][C]0.329247[/C][/ROW]
[ROW][C]29[/C][C]0.038417[/C][C]0.2951[/C][C]0.384481[/C][/ROW]
[ROW][C]30[/C][C]-0.157094[/C][C]-1.2067[/C][C]0.116189[/C][/ROW]
[ROW][C]31[/C][C]0.096083[/C][C]0.738[/C][C]0.231712[/C][/ROW]
[ROW][C]32[/C][C]0.113862[/C][C]0.8746[/C][C]0.192672[/C][/ROW]
[ROW][C]33[/C][C]-0.265981[/C][C]-2.043[/C][C]0.022762[/C][/ROW]
[ROW][C]34[/C][C]0.276719[/C][C]2.1255[/C][C]0.01887[/C][/ROW]
[ROW][C]35[/C][C]-0.214406[/C][C]-1.6469[/C][C]0.05245[/C][/ROW]
[ROW][C]36[/C][C]0.128368[/C][C]0.986[/C][C]0.164076[/C][/ROW]
[ROW][C]37[/C][C]-0.034898[/C][C]-0.2681[/C][C]0.394795[/C][/ROW]
[ROW][C]38[/C][C]-0.011564[/C][C]-0.0888[/C][C]0.464762[/C][/ROW]
[ROW][C]39[/C][C]0.0194[/C][C]0.149[/C][C]0.441027[/C][/ROW]
[ROW][C]40[/C][C]-0.002937[/C][C]-0.0226[/C][C]0.49104[/C][/ROW]
[ROW][C]41[/C][C]-0.038172[/C][C]-0.2932[/C][C]0.385199[/C][/ROW]
[ROW][C]42[/C][C]0.072984[/C][C]0.5606[/C][C]0.288597[/C][/ROW]
[ROW][C]43[/C][C]-0.025332[/C][C]-0.1946[/C][C]0.423194[/C][/ROW]
[ROW][C]44[/C][C]-0.077477[/C][C]-0.5951[/C][C]0.277022[/C][/ROW]
[ROW][C]45[/C][C]0.123807[/C][C]0.951[/C][C]0.172747[/C][/ROW]
[ROW][C]46[/C][C]-0.099256[/C][C]-0.7624[/C][C]0.22443[/C][/ROW]
[ROW][C]47[/C][C]0.062647[/C][C]0.4812[/C][C]0.316076[/C][/ROW]
[ROW][C]48[/C][C]-0.041375[/C][C]-0.3178[/C][C]0.375876[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196433&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196433&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
1-0.692354-5.31811e-06
20.2314561.77780.040291
30.0053560.04110.483661
4-0.084512-0.64910.259381
50.0966080.74210.230498
6-0.016336-0.12550.450285
7-0.086927-0.66770.253465
80.0428890.32940.371495
90.0750110.57620.283347
10-0.226283-1.73810.043704
110.3853712.96010.002212
12-0.434989-3.34120.000726
130.2484541.90840.030604
14-0.041019-0.31510.376909
15-0.011111-0.08530.466139
16-0.013262-0.10190.459603
17-0.017221-0.13230.447609
180.0904650.69490.244931
19-0.051603-0.39640.34663
20-0.038426-0.29520.384456
210.1054380.80990.210631
22-0.141666-1.08820.140476
230.1658981.27430.103779
24-0.11698-0.89850.186274
250.0180460.13860.445114
260.0453860.34860.36431
27-0.07537-0.57890.282422
280.0578350.44420.329247
290.0384170.29510.384481
30-0.157094-1.20670.116189
310.0960830.7380.231712
320.1138620.87460.192672
33-0.265981-2.0430.022762
340.2767192.12550.01887
35-0.214406-1.64690.05245
360.1283680.9860.164076
37-0.034898-0.26810.394795
38-0.011564-0.08880.464762
390.01940.1490.441027
40-0.002937-0.02260.49104
41-0.038172-0.29320.385199
420.0729840.56060.288597
43-0.025332-0.19460.423194
44-0.077477-0.59510.277022
450.1238070.9510.172747
46-0.099256-0.76240.22443
470.0626470.48120.316076
48-0.041375-0.31780.375876







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.692354-5.31811e-06
2-0.476138-3.65730.000272
3-0.217952-1.67410.0497
4-0.176331-1.35440.090383
5-0.062089-0.47690.317592
60.1150670.88380.190184
70.0047510.03650.485506
8-0.191178-1.46850.073645
9-0.043298-0.33260.370317
10-0.334295-2.56780.006394
110.1173320.90120.185562
12-0.062268-0.47830.317106
13-0.205152-1.57580.060209
14-0.244043-1.87450.032905
15-0.097677-0.75030.228036
16-0.157624-1.21070.115413
17-0.296038-2.27390.013312
18-0.045629-0.35050.363612
190.1154930.88710.189309
20-0.201512-1.54780.063504
210.0629270.48340.315316
22-0.295309-2.26830.013492
230.0321210.24670.402987
24-0.015485-0.11890.452861
25-0.046172-0.35470.362056
26-0.034294-0.26340.396573
27-0.055631-0.42730.335354
28-0.081055-0.62260.267976
290.0029870.02290.490886
30-0.074999-0.57610.283377
31-0.049977-0.38390.351223
320.0080.06140.475605
330.0665670.51130.305522
34-0.095479-0.73340.233114
350.0324590.24930.401988
360.06480.49770.310259
37-0.071432-0.54870.292647
380.0127610.0980.461124
390.0812060.62380.267597
400.0092090.07070.471924
41-0.02007-0.15420.439003
42-0.01795-0.13790.445402
43-0.000514-0.00390.498432
44-0.025966-0.19940.4213
450.0499560.38370.351282
46-0.07236-0.55580.290221
47-0.072317-0.55550.290334
480.0874760.67190.25213

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.692354 & -5.3181 & 1e-06 \tabularnewline
2 & -0.476138 & -3.6573 & 0.000272 \tabularnewline
3 & -0.217952 & -1.6741 & 0.0497 \tabularnewline
4 & -0.176331 & -1.3544 & 0.090383 \tabularnewline
5 & -0.062089 & -0.4769 & 0.317592 \tabularnewline
6 & 0.115067 & 0.8838 & 0.190184 \tabularnewline
7 & 0.004751 & 0.0365 & 0.485506 \tabularnewline
8 & -0.191178 & -1.4685 & 0.073645 \tabularnewline
9 & -0.043298 & -0.3326 & 0.370317 \tabularnewline
10 & -0.334295 & -2.5678 & 0.006394 \tabularnewline
11 & 0.117332 & 0.9012 & 0.185562 \tabularnewline
12 & -0.062268 & -0.4783 & 0.317106 \tabularnewline
13 & -0.205152 & -1.5758 & 0.060209 \tabularnewline
14 & -0.244043 & -1.8745 & 0.032905 \tabularnewline
15 & -0.097677 & -0.7503 & 0.228036 \tabularnewline
16 & -0.157624 & -1.2107 & 0.115413 \tabularnewline
17 & -0.296038 & -2.2739 & 0.013312 \tabularnewline
18 & -0.045629 & -0.3505 & 0.363612 \tabularnewline
19 & 0.115493 & 0.8871 & 0.189309 \tabularnewline
20 & -0.201512 & -1.5478 & 0.063504 \tabularnewline
21 & 0.062927 & 0.4834 & 0.315316 \tabularnewline
22 & -0.295309 & -2.2683 & 0.013492 \tabularnewline
23 & 0.032121 & 0.2467 & 0.402987 \tabularnewline
24 & -0.015485 & -0.1189 & 0.452861 \tabularnewline
25 & -0.046172 & -0.3547 & 0.362056 \tabularnewline
26 & -0.034294 & -0.2634 & 0.396573 \tabularnewline
27 & -0.055631 & -0.4273 & 0.335354 \tabularnewline
28 & -0.081055 & -0.6226 & 0.267976 \tabularnewline
29 & 0.002987 & 0.0229 & 0.490886 \tabularnewline
30 & -0.074999 & -0.5761 & 0.283377 \tabularnewline
31 & -0.049977 & -0.3839 & 0.351223 \tabularnewline
32 & 0.008 & 0.0614 & 0.475605 \tabularnewline
33 & 0.066567 & 0.5113 & 0.305522 \tabularnewline
34 & -0.095479 & -0.7334 & 0.233114 \tabularnewline
35 & 0.032459 & 0.2493 & 0.401988 \tabularnewline
36 & 0.0648 & 0.4977 & 0.310259 \tabularnewline
37 & -0.071432 & -0.5487 & 0.292647 \tabularnewline
38 & 0.012761 & 0.098 & 0.461124 \tabularnewline
39 & 0.081206 & 0.6238 & 0.267597 \tabularnewline
40 & 0.009209 & 0.0707 & 0.471924 \tabularnewline
41 & -0.02007 & -0.1542 & 0.439003 \tabularnewline
42 & -0.01795 & -0.1379 & 0.445402 \tabularnewline
43 & -0.000514 & -0.0039 & 0.498432 \tabularnewline
44 & -0.025966 & -0.1994 & 0.4213 \tabularnewline
45 & 0.049956 & 0.3837 & 0.351282 \tabularnewline
46 & -0.07236 & -0.5558 & 0.290221 \tabularnewline
47 & -0.072317 & -0.5555 & 0.290334 \tabularnewline
48 & 0.087476 & 0.6719 & 0.25213 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196433&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]-0.692354[/C][C]-5.3181[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.476138[/C][C]-3.6573[/C][C]0.000272[/C][/ROW]
[ROW][C]3[/C][C]-0.217952[/C][C]-1.6741[/C][C]0.0497[/C][/ROW]
[ROW][C]4[/C][C]-0.176331[/C][C]-1.3544[/C][C]0.090383[/C][/ROW]
[ROW][C]5[/C][C]-0.062089[/C][C]-0.4769[/C][C]0.317592[/C][/ROW]
[ROW][C]6[/C][C]0.115067[/C][C]0.8838[/C][C]0.190184[/C][/ROW]
[ROW][C]7[/C][C]0.004751[/C][C]0.0365[/C][C]0.485506[/C][/ROW]
[ROW][C]8[/C][C]-0.191178[/C][C]-1.4685[/C][C]0.073645[/C][/ROW]
[ROW][C]9[/C][C]-0.043298[/C][C]-0.3326[/C][C]0.370317[/C][/ROW]
[ROW][C]10[/C][C]-0.334295[/C][C]-2.5678[/C][C]0.006394[/C][/ROW]
[ROW][C]11[/C][C]0.117332[/C][C]0.9012[/C][C]0.185562[/C][/ROW]
[ROW][C]12[/C][C]-0.062268[/C][C]-0.4783[/C][C]0.317106[/C][/ROW]
[ROW][C]13[/C][C]-0.205152[/C][C]-1.5758[/C][C]0.060209[/C][/ROW]
[ROW][C]14[/C][C]-0.244043[/C][C]-1.8745[/C][C]0.032905[/C][/ROW]
[ROW][C]15[/C][C]-0.097677[/C][C]-0.7503[/C][C]0.228036[/C][/ROW]
[ROW][C]16[/C][C]-0.157624[/C][C]-1.2107[/C][C]0.115413[/C][/ROW]
[ROW][C]17[/C][C]-0.296038[/C][C]-2.2739[/C][C]0.013312[/C][/ROW]
[ROW][C]18[/C][C]-0.045629[/C][C]-0.3505[/C][C]0.363612[/C][/ROW]
[ROW][C]19[/C][C]0.115493[/C][C]0.8871[/C][C]0.189309[/C][/ROW]
[ROW][C]20[/C][C]-0.201512[/C][C]-1.5478[/C][C]0.063504[/C][/ROW]
[ROW][C]21[/C][C]0.062927[/C][C]0.4834[/C][C]0.315316[/C][/ROW]
[ROW][C]22[/C][C]-0.295309[/C][C]-2.2683[/C][C]0.013492[/C][/ROW]
[ROW][C]23[/C][C]0.032121[/C][C]0.2467[/C][C]0.402987[/C][/ROW]
[ROW][C]24[/C][C]-0.015485[/C][C]-0.1189[/C][C]0.452861[/C][/ROW]
[ROW][C]25[/C][C]-0.046172[/C][C]-0.3547[/C][C]0.362056[/C][/ROW]
[ROW][C]26[/C][C]-0.034294[/C][C]-0.2634[/C][C]0.396573[/C][/ROW]
[ROW][C]27[/C][C]-0.055631[/C][C]-0.4273[/C][C]0.335354[/C][/ROW]
[ROW][C]28[/C][C]-0.081055[/C][C]-0.6226[/C][C]0.267976[/C][/ROW]
[ROW][C]29[/C][C]0.002987[/C][C]0.0229[/C][C]0.490886[/C][/ROW]
[ROW][C]30[/C][C]-0.074999[/C][C]-0.5761[/C][C]0.283377[/C][/ROW]
[ROW][C]31[/C][C]-0.049977[/C][C]-0.3839[/C][C]0.351223[/C][/ROW]
[ROW][C]32[/C][C]0.008[/C][C]0.0614[/C][C]0.475605[/C][/ROW]
[ROW][C]33[/C][C]0.066567[/C][C]0.5113[/C][C]0.305522[/C][/ROW]
[ROW][C]34[/C][C]-0.095479[/C][C]-0.7334[/C][C]0.233114[/C][/ROW]
[ROW][C]35[/C][C]0.032459[/C][C]0.2493[/C][C]0.401988[/C][/ROW]
[ROW][C]36[/C][C]0.0648[/C][C]0.4977[/C][C]0.310259[/C][/ROW]
[ROW][C]37[/C][C]-0.071432[/C][C]-0.5487[/C][C]0.292647[/C][/ROW]
[ROW][C]38[/C][C]0.012761[/C][C]0.098[/C][C]0.461124[/C][/ROW]
[ROW][C]39[/C][C]0.081206[/C][C]0.6238[/C][C]0.267597[/C][/ROW]
[ROW][C]40[/C][C]0.009209[/C][C]0.0707[/C][C]0.471924[/C][/ROW]
[ROW][C]41[/C][C]-0.02007[/C][C]-0.1542[/C][C]0.439003[/C][/ROW]
[ROW][C]42[/C][C]-0.01795[/C][C]-0.1379[/C][C]0.445402[/C][/ROW]
[ROW][C]43[/C][C]-0.000514[/C][C]-0.0039[/C][C]0.498432[/C][/ROW]
[ROW][C]44[/C][C]-0.025966[/C][C]-0.1994[/C][C]0.4213[/C][/ROW]
[ROW][C]45[/C][C]0.049956[/C][C]0.3837[/C][C]0.351282[/C][/ROW]
[ROW][C]46[/C][C]-0.07236[/C][C]-0.5558[/C][C]0.290221[/C][/ROW]
[ROW][C]47[/C][C]-0.072317[/C][C]-0.5555[/C][C]0.290334[/C][/ROW]
[ROW][C]48[/C][C]0.087476[/C][C]0.6719[/C][C]0.25213[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196433&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196433&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
1-0.692354-5.31811e-06
2-0.476138-3.65730.000272
3-0.217952-1.67410.0497
4-0.176331-1.35440.090383
5-0.062089-0.47690.317592
60.1150670.88380.190184
70.0047510.03650.485506
8-0.191178-1.46850.073645
9-0.043298-0.33260.370317
10-0.334295-2.56780.006394
110.1173320.90120.185562
12-0.062268-0.47830.317106
13-0.205152-1.57580.060209
14-0.244043-1.87450.032905
15-0.097677-0.75030.228036
16-0.157624-1.21070.115413
17-0.296038-2.27390.013312
18-0.045629-0.35050.363612
190.1154930.88710.189309
20-0.201512-1.54780.063504
210.0629270.48340.315316
22-0.295309-2.26830.013492
230.0321210.24670.402987
24-0.015485-0.11890.452861
25-0.046172-0.35470.362056
26-0.034294-0.26340.396573
27-0.055631-0.42730.335354
28-0.081055-0.62260.267976
290.0029870.02290.490886
30-0.074999-0.57610.283377
31-0.049977-0.38390.351223
320.0080.06140.475605
330.0665670.51130.305522
34-0.095479-0.73340.233114
350.0324590.24930.401988
360.06480.49770.310259
37-0.071432-0.54870.292647
380.0127610.0980.461124
390.0812060.62380.267597
400.0092090.07070.471924
41-0.02007-0.15420.439003
42-0.01795-0.13790.445402
43-0.000514-0.00390.498432
44-0.025966-0.19940.4213
450.0499560.38370.351282
46-0.07236-0.55580.290221
47-0.072317-0.55550.290334
480.0874760.67190.25213



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