Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 01 May 2010 13:07:56 +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/2010/May/01/t1272719349on8f49y01y9yafx.htm/, Retrieved Sun, 10 Nov 2024 19:48:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75138, Retrieved Sun, 10 Nov 2024 19:48:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact206
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [6 bis] [2009-12-08 14:15:57] [96d7baecdd5ebd8fe17b0c7c170ff3c2]
- R  D    [(Partial) Autocorrelation Function] [Opgave 6 bis:Mont...] [2010-05-01 13:07:56] [4c7bd8110f71133578d35fb221e548da] [Current]
Feedback Forum

Post a new message
Dataseries X:
464
675
703
887
1139
1077
1318
1260
1120
963
996
960
530
883
894
1045
1199
1287
1565
1577
1076
918
1008
1063
544
635
804
980
1018
1064
1404
1286
1104
999
996
1015
615
722
832
977
1270
1437
1520
1708
1151
934
1159
1209
699
830
996
1124
1458
1270
1753
2258
1208
1241
1265
1828
809
997
1164
1205
1538
1513
1378
2083
1357
1536
1526
1376
779
1005
1193
1522
1539
1546
2116
2326
1596
1356
1553
1613
814
1150
1225
1691
1759
1754
2100
2062
2012
1897
1964
2186
966
1549
1538
1612
2078
2137
2907
2249
1883
1739
1828
1868
1138
1430
1809
1763
2200
2067
2503
2141
2103
1972
2181
2344
970
1199
1718
1683
2025
2051
2439
2353
2230
1852
2147
2286
1007
1665
1642
1518
1831
2207
2822
2393
2306
1785
2047
2171
1212
1335
2011
1860
1954
2152
2835
2224
2182
1992
2389
2724
891
1247
2017
2257
2255
2255
3057
3330
1896
2096
2374
2535
1041
1728
2201
2455
2204
2660
3670
2665
2639
2226
2586
2684
1185
1749
2459
2618
2585
3310
3923




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75138&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75138&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75138&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7056599.64970
20.536627.33820
30.5064226.92520
40.4519516.18030
50.313784.29091.4e-05
60.1905462.60570.004954
70.3506584.79522e-06
80.4631516.33350
90.4827536.60150
100.5014996.85790
110.622478.51220
120.78146210.68630
130.5580737.63150
140.4217125.76680
150.4053155.54260
160.3512144.80282e-06
170.2112852.88930.002159
180.1096261.49910.067765
190.268433.67070.000158
200.3475964.75332e-06
210.3762715.14540
220.4010185.48380
230.5268297.20430
240.6424438.78530
250.4465936.10710
260.3212374.39289e-06
270.2912473.98274.9e-05
280.2351093.21510.000768
290.1167611.59670.056012
300.049950.68310.24771
310.1757792.40370.008602
320.2379453.25380.000676
330.2711333.70770.000138
340.2877943.93555.8e-05
350.385315.2690
360.511036.98820
370.3373034.61254e-06
380.229153.13360.001003
390.1909662.61140.004874
400.1468862.00860.023007
410.0383630.52460.30024
42-0.03071-0.420.337501
430.0873341.19430.116943
440.1408771.92650.027781
450.1838592.51420.006386
460.2122172.9020.002076
470.2862523.91446.3e-05
480.3846075.25940

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.705659 & 9.6497 & 0 \tabularnewline
2 & 0.53662 & 7.3382 & 0 \tabularnewline
3 & 0.506422 & 6.9252 & 0 \tabularnewline
4 & 0.451951 & 6.1803 & 0 \tabularnewline
5 & 0.31378 & 4.2909 & 1.4e-05 \tabularnewline
6 & 0.190546 & 2.6057 & 0.004954 \tabularnewline
7 & 0.350658 & 4.7952 & 2e-06 \tabularnewline
8 & 0.463151 & 6.3335 & 0 \tabularnewline
9 & 0.482753 & 6.6015 & 0 \tabularnewline
10 & 0.501499 & 6.8579 & 0 \tabularnewline
11 & 0.62247 & 8.5122 & 0 \tabularnewline
12 & 0.781462 & 10.6863 & 0 \tabularnewline
13 & 0.558073 & 7.6315 & 0 \tabularnewline
14 & 0.421712 & 5.7668 & 0 \tabularnewline
15 & 0.405315 & 5.5426 & 0 \tabularnewline
16 & 0.351214 & 4.8028 & 2e-06 \tabularnewline
17 & 0.211285 & 2.8893 & 0.002159 \tabularnewline
18 & 0.109626 & 1.4991 & 0.067765 \tabularnewline
19 & 0.26843 & 3.6707 & 0.000158 \tabularnewline
20 & 0.347596 & 4.7533 & 2e-06 \tabularnewline
21 & 0.376271 & 5.1454 & 0 \tabularnewline
22 & 0.401018 & 5.4838 & 0 \tabularnewline
23 & 0.526829 & 7.2043 & 0 \tabularnewline
24 & 0.642443 & 8.7853 & 0 \tabularnewline
25 & 0.446593 & 6.1071 & 0 \tabularnewline
26 & 0.321237 & 4.3928 & 9e-06 \tabularnewline
27 & 0.291247 & 3.9827 & 4.9e-05 \tabularnewline
28 & 0.235109 & 3.2151 & 0.000768 \tabularnewline
29 & 0.116761 & 1.5967 & 0.056012 \tabularnewline
30 & 0.04995 & 0.6831 & 0.24771 \tabularnewline
31 & 0.175779 & 2.4037 & 0.008602 \tabularnewline
32 & 0.237945 & 3.2538 & 0.000676 \tabularnewline
33 & 0.271133 & 3.7077 & 0.000138 \tabularnewline
34 & 0.287794 & 3.9355 & 5.8e-05 \tabularnewline
35 & 0.38531 & 5.269 & 0 \tabularnewline
36 & 0.51103 & 6.9882 & 0 \tabularnewline
37 & 0.337303 & 4.6125 & 4e-06 \tabularnewline
38 & 0.22915 & 3.1336 & 0.001003 \tabularnewline
39 & 0.190966 & 2.6114 & 0.004874 \tabularnewline
40 & 0.146886 & 2.0086 & 0.023007 \tabularnewline
41 & 0.038363 & 0.5246 & 0.30024 \tabularnewline
42 & -0.03071 & -0.42 & 0.337501 \tabularnewline
43 & 0.087334 & 1.1943 & 0.116943 \tabularnewline
44 & 0.140877 & 1.9265 & 0.027781 \tabularnewline
45 & 0.183859 & 2.5142 & 0.006386 \tabularnewline
46 & 0.212217 & 2.902 & 0.002076 \tabularnewline
47 & 0.286252 & 3.9144 & 6.3e-05 \tabularnewline
48 & 0.384607 & 5.2594 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75138&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]0.705659[/C][C]9.6497[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.53662[/C][C]7.3382[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.506422[/C][C]6.9252[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.451951[/C][C]6.1803[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.31378[/C][C]4.2909[/C][C]1.4e-05[/C][/ROW]
[ROW][C]6[/C][C]0.190546[/C][C]2.6057[/C][C]0.004954[/C][/ROW]
[ROW][C]7[/C][C]0.350658[/C][C]4.7952[/C][C]2e-06[/C][/ROW]
[ROW][C]8[/C][C]0.463151[/C][C]6.3335[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.482753[/C][C]6.6015[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.501499[/C][C]6.8579[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.62247[/C][C]8.5122[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.781462[/C][C]10.6863[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.558073[/C][C]7.6315[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.421712[/C][C]5.7668[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.405315[/C][C]5.5426[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.351214[/C][C]4.8028[/C][C]2e-06[/C][/ROW]
[ROW][C]17[/C][C]0.211285[/C][C]2.8893[/C][C]0.002159[/C][/ROW]
[ROW][C]18[/C][C]0.109626[/C][C]1.4991[/C][C]0.067765[/C][/ROW]
[ROW][C]19[/C][C]0.26843[/C][C]3.6707[/C][C]0.000158[/C][/ROW]
[ROW][C]20[/C][C]0.347596[/C][C]4.7533[/C][C]2e-06[/C][/ROW]
[ROW][C]21[/C][C]0.376271[/C][C]5.1454[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.401018[/C][C]5.4838[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.526829[/C][C]7.2043[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.642443[/C][C]8.7853[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.446593[/C][C]6.1071[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.321237[/C][C]4.3928[/C][C]9e-06[/C][/ROW]
[ROW][C]27[/C][C]0.291247[/C][C]3.9827[/C][C]4.9e-05[/C][/ROW]
[ROW][C]28[/C][C]0.235109[/C][C]3.2151[/C][C]0.000768[/C][/ROW]
[ROW][C]29[/C][C]0.116761[/C][C]1.5967[/C][C]0.056012[/C][/ROW]
[ROW][C]30[/C][C]0.04995[/C][C]0.6831[/C][C]0.24771[/C][/ROW]
[ROW][C]31[/C][C]0.175779[/C][C]2.4037[/C][C]0.008602[/C][/ROW]
[ROW][C]32[/C][C]0.237945[/C][C]3.2538[/C][C]0.000676[/C][/ROW]
[ROW][C]33[/C][C]0.271133[/C][C]3.7077[/C][C]0.000138[/C][/ROW]
[ROW][C]34[/C][C]0.287794[/C][C]3.9355[/C][C]5.8e-05[/C][/ROW]
[ROW][C]35[/C][C]0.38531[/C][C]5.269[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0.51103[/C][C]6.9882[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.337303[/C][C]4.6125[/C][C]4e-06[/C][/ROW]
[ROW][C]38[/C][C]0.22915[/C][C]3.1336[/C][C]0.001003[/C][/ROW]
[ROW][C]39[/C][C]0.190966[/C][C]2.6114[/C][C]0.004874[/C][/ROW]
[ROW][C]40[/C][C]0.146886[/C][C]2.0086[/C][C]0.023007[/C][/ROW]
[ROW][C]41[/C][C]0.038363[/C][C]0.5246[/C][C]0.30024[/C][/ROW]
[ROW][C]42[/C][C]-0.03071[/C][C]-0.42[/C][C]0.337501[/C][/ROW]
[ROW][C]43[/C][C]0.087334[/C][C]1.1943[/C][C]0.116943[/C][/ROW]
[ROW][C]44[/C][C]0.140877[/C][C]1.9265[/C][C]0.027781[/C][/ROW]
[ROW][C]45[/C][C]0.183859[/C][C]2.5142[/C][C]0.006386[/C][/ROW]
[ROW][C]46[/C][C]0.212217[/C][C]2.902[/C][C]0.002076[/C][/ROW]
[ROW][C]47[/C][C]0.286252[/C][C]3.9144[/C][C]6.3e-05[/C][/ROW]
[ROW][C]48[/C][C]0.384607[/C][C]5.2594[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75138&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75138&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7056599.64970
20.536627.33820
30.5064226.92520
40.4519516.18030
50.313784.29091.4e-05
60.1905462.60570.004954
70.3506584.79522e-06
80.4631516.33350
90.4827536.60150
100.5014996.85790
110.622478.51220
120.78146210.68630
130.5580737.63150
140.4217125.76680
150.4053155.54260
160.3512144.80282e-06
170.2112852.88930.002159
180.1096261.49910.067765
190.268433.67070.000158
200.3475964.75332e-06
210.3762715.14540
220.4010185.48380
230.5268297.20430
240.6424438.78530
250.4465936.10710
260.3212374.39289e-06
270.2912473.98274.9e-05
280.2351093.21510.000768
290.1167611.59670.056012
300.049950.68310.24771
310.1757792.40370.008602
320.2379453.25380.000676
330.2711333.70770.000138
340.2877943.93555.8e-05
350.385315.2690
360.511036.98820
370.3373034.61254e-06
380.229153.13360.001003
390.1909662.61140.004874
400.1468862.00860.023007
410.0383630.52460.30024
42-0.03071-0.420.337501
430.0873341.19430.116943
440.1408771.92650.027781
450.1838592.51420.006386
460.2122172.9020.002076
470.2862523.91446.3e-05
480.3846075.25940







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7056599.64970
20.0770161.05320.14681
30.2055182.81040.002737
40.0326450.44640.327906
5-0.135586-1.85410.032649
6-0.110941-1.51710.065466
70.4416466.03940
80.2474953.38440.000434
90.1862842.54740.005829
100.0607650.8310.203531
110.2031692.77830.003011
120.4350685.94950
13-0.286508-3.91796.3e-05
14-0.090693-1.24020.108227
15-0.06691-0.9150.180691
16-0.056206-0.76860.221549
17-0.10045-1.37360.085601
18-0.121854-1.66630.048661
19-0.026966-0.36880.356362
20-0.077685-1.06230.144728
210.097951.33950.091025
22-0.015645-0.21390.415413
230.1209091.65340.049963
240.1360631.86060.032183
25-0.02025-0.27690.391075
26-0.050592-0.69180.24495
27-0.060807-0.83150.20337
28-0.019669-0.2690.394125
290.04420.60440.273146
300.0068380.09350.462801
31-0.167463-2.290.011568
32-0.086188-1.17860.120028
33-0.004047-0.05530.477964
34-0.051106-0.69890.242753
35-0.029146-0.39860.345335
360.2237413.05960.001271
37-0.05089-0.69590.243675
380.0236020.32280.37362
39-0.023409-0.32010.374619
400.0367320.50230.308022
410.0595430.81420.208271
42-0.011219-0.15340.439119
43-0.037958-0.51910.302166
44-0.104164-1.42440.077996
450.0127690.17460.430786
460.0095190.13020.448287
47-0.048617-0.66480.253492
48-0.040084-0.54810.292126

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.705659 & 9.6497 & 0 \tabularnewline
2 & 0.077016 & 1.0532 & 0.14681 \tabularnewline
3 & 0.205518 & 2.8104 & 0.002737 \tabularnewline
4 & 0.032645 & 0.4464 & 0.327906 \tabularnewline
5 & -0.135586 & -1.8541 & 0.032649 \tabularnewline
6 & -0.110941 & -1.5171 & 0.065466 \tabularnewline
7 & 0.441646 & 6.0394 & 0 \tabularnewline
8 & 0.247495 & 3.3844 & 0.000434 \tabularnewline
9 & 0.186284 & 2.5474 & 0.005829 \tabularnewline
10 & 0.060765 & 0.831 & 0.203531 \tabularnewline
11 & 0.203169 & 2.7783 & 0.003011 \tabularnewline
12 & 0.435068 & 5.9495 & 0 \tabularnewline
13 & -0.286508 & -3.9179 & 6.3e-05 \tabularnewline
14 & -0.090693 & -1.2402 & 0.108227 \tabularnewline
15 & -0.06691 & -0.915 & 0.180691 \tabularnewline
16 & -0.056206 & -0.7686 & 0.221549 \tabularnewline
17 & -0.10045 & -1.3736 & 0.085601 \tabularnewline
18 & -0.121854 & -1.6663 & 0.048661 \tabularnewline
19 & -0.026966 & -0.3688 & 0.356362 \tabularnewline
20 & -0.077685 & -1.0623 & 0.144728 \tabularnewline
21 & 0.09795 & 1.3395 & 0.091025 \tabularnewline
22 & -0.015645 & -0.2139 & 0.415413 \tabularnewline
23 & 0.120909 & 1.6534 & 0.049963 \tabularnewline
24 & 0.136063 & 1.8606 & 0.032183 \tabularnewline
25 & -0.02025 & -0.2769 & 0.391075 \tabularnewline
26 & -0.050592 & -0.6918 & 0.24495 \tabularnewline
27 & -0.060807 & -0.8315 & 0.20337 \tabularnewline
28 & -0.019669 & -0.269 & 0.394125 \tabularnewline
29 & 0.0442 & 0.6044 & 0.273146 \tabularnewline
30 & 0.006838 & 0.0935 & 0.462801 \tabularnewline
31 & -0.167463 & -2.29 & 0.011568 \tabularnewline
32 & -0.086188 & -1.1786 & 0.120028 \tabularnewline
33 & -0.004047 & -0.0553 & 0.477964 \tabularnewline
34 & -0.051106 & -0.6989 & 0.242753 \tabularnewline
35 & -0.029146 & -0.3986 & 0.345335 \tabularnewline
36 & 0.223741 & 3.0596 & 0.001271 \tabularnewline
37 & -0.05089 & -0.6959 & 0.243675 \tabularnewline
38 & 0.023602 & 0.3228 & 0.37362 \tabularnewline
39 & -0.023409 & -0.3201 & 0.374619 \tabularnewline
40 & 0.036732 & 0.5023 & 0.308022 \tabularnewline
41 & 0.059543 & 0.8142 & 0.208271 \tabularnewline
42 & -0.011219 & -0.1534 & 0.439119 \tabularnewline
43 & -0.037958 & -0.5191 & 0.302166 \tabularnewline
44 & -0.104164 & -1.4244 & 0.077996 \tabularnewline
45 & 0.012769 & 0.1746 & 0.430786 \tabularnewline
46 & 0.009519 & 0.1302 & 0.448287 \tabularnewline
47 & -0.048617 & -0.6648 & 0.253492 \tabularnewline
48 & -0.040084 & -0.5481 & 0.292126 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75138&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]0.705659[/C][C]9.6497[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.077016[/C][C]1.0532[/C][C]0.14681[/C][/ROW]
[ROW][C]3[/C][C]0.205518[/C][C]2.8104[/C][C]0.002737[/C][/ROW]
[ROW][C]4[/C][C]0.032645[/C][C]0.4464[/C][C]0.327906[/C][/ROW]
[ROW][C]5[/C][C]-0.135586[/C][C]-1.8541[/C][C]0.032649[/C][/ROW]
[ROW][C]6[/C][C]-0.110941[/C][C]-1.5171[/C][C]0.065466[/C][/ROW]
[ROW][C]7[/C][C]0.441646[/C][C]6.0394[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.247495[/C][C]3.3844[/C][C]0.000434[/C][/ROW]
[ROW][C]9[/C][C]0.186284[/C][C]2.5474[/C][C]0.005829[/C][/ROW]
[ROW][C]10[/C][C]0.060765[/C][C]0.831[/C][C]0.203531[/C][/ROW]
[ROW][C]11[/C][C]0.203169[/C][C]2.7783[/C][C]0.003011[/C][/ROW]
[ROW][C]12[/C][C]0.435068[/C][C]5.9495[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.286508[/C][C]-3.9179[/C][C]6.3e-05[/C][/ROW]
[ROW][C]14[/C][C]-0.090693[/C][C]-1.2402[/C][C]0.108227[/C][/ROW]
[ROW][C]15[/C][C]-0.06691[/C][C]-0.915[/C][C]0.180691[/C][/ROW]
[ROW][C]16[/C][C]-0.056206[/C][C]-0.7686[/C][C]0.221549[/C][/ROW]
[ROW][C]17[/C][C]-0.10045[/C][C]-1.3736[/C][C]0.085601[/C][/ROW]
[ROW][C]18[/C][C]-0.121854[/C][C]-1.6663[/C][C]0.048661[/C][/ROW]
[ROW][C]19[/C][C]-0.026966[/C][C]-0.3688[/C][C]0.356362[/C][/ROW]
[ROW][C]20[/C][C]-0.077685[/C][C]-1.0623[/C][C]0.144728[/C][/ROW]
[ROW][C]21[/C][C]0.09795[/C][C]1.3395[/C][C]0.091025[/C][/ROW]
[ROW][C]22[/C][C]-0.015645[/C][C]-0.2139[/C][C]0.415413[/C][/ROW]
[ROW][C]23[/C][C]0.120909[/C][C]1.6534[/C][C]0.049963[/C][/ROW]
[ROW][C]24[/C][C]0.136063[/C][C]1.8606[/C][C]0.032183[/C][/ROW]
[ROW][C]25[/C][C]-0.02025[/C][C]-0.2769[/C][C]0.391075[/C][/ROW]
[ROW][C]26[/C][C]-0.050592[/C][C]-0.6918[/C][C]0.24495[/C][/ROW]
[ROW][C]27[/C][C]-0.060807[/C][C]-0.8315[/C][C]0.20337[/C][/ROW]
[ROW][C]28[/C][C]-0.019669[/C][C]-0.269[/C][C]0.394125[/C][/ROW]
[ROW][C]29[/C][C]0.0442[/C][C]0.6044[/C][C]0.273146[/C][/ROW]
[ROW][C]30[/C][C]0.006838[/C][C]0.0935[/C][C]0.462801[/C][/ROW]
[ROW][C]31[/C][C]-0.167463[/C][C]-2.29[/C][C]0.011568[/C][/ROW]
[ROW][C]32[/C][C]-0.086188[/C][C]-1.1786[/C][C]0.120028[/C][/ROW]
[ROW][C]33[/C][C]-0.004047[/C][C]-0.0553[/C][C]0.477964[/C][/ROW]
[ROW][C]34[/C][C]-0.051106[/C][C]-0.6989[/C][C]0.242753[/C][/ROW]
[ROW][C]35[/C][C]-0.029146[/C][C]-0.3986[/C][C]0.345335[/C][/ROW]
[ROW][C]36[/C][C]0.223741[/C][C]3.0596[/C][C]0.001271[/C][/ROW]
[ROW][C]37[/C][C]-0.05089[/C][C]-0.6959[/C][C]0.243675[/C][/ROW]
[ROW][C]38[/C][C]0.023602[/C][C]0.3228[/C][C]0.37362[/C][/ROW]
[ROW][C]39[/C][C]-0.023409[/C][C]-0.3201[/C][C]0.374619[/C][/ROW]
[ROW][C]40[/C][C]0.036732[/C][C]0.5023[/C][C]0.308022[/C][/ROW]
[ROW][C]41[/C][C]0.059543[/C][C]0.8142[/C][C]0.208271[/C][/ROW]
[ROW][C]42[/C][C]-0.011219[/C][C]-0.1534[/C][C]0.439119[/C][/ROW]
[ROW][C]43[/C][C]-0.037958[/C][C]-0.5191[/C][C]0.302166[/C][/ROW]
[ROW][C]44[/C][C]-0.104164[/C][C]-1.4244[/C][C]0.077996[/C][/ROW]
[ROW][C]45[/C][C]0.012769[/C][C]0.1746[/C][C]0.430786[/C][/ROW]
[ROW][C]46[/C][C]0.009519[/C][C]0.1302[/C][C]0.448287[/C][/ROW]
[ROW][C]47[/C][C]-0.048617[/C][C]-0.6648[/C][C]0.253492[/C][/ROW]
[ROW][C]48[/C][C]-0.040084[/C][C]-0.5481[/C][C]0.292126[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75138&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75138&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7056599.64970
20.0770161.05320.14681
30.2055182.81040.002737
40.0326450.44640.327906
5-0.135586-1.85410.032649
6-0.110941-1.51710.065466
70.4416466.03940
80.2474953.38440.000434
90.1862842.54740.005829
100.0607650.8310.203531
110.2031692.77830.003011
120.4350685.94950
13-0.286508-3.91796.3e-05
14-0.090693-1.24020.108227
15-0.06691-0.9150.180691
16-0.056206-0.76860.221549
17-0.10045-1.37360.085601
18-0.121854-1.66630.048661
19-0.026966-0.36880.356362
20-0.077685-1.06230.144728
210.097951.33950.091025
22-0.015645-0.21390.415413
230.1209091.65340.049963
240.1360631.86060.032183
25-0.02025-0.27690.391075
26-0.050592-0.69180.24495
27-0.060807-0.83150.20337
28-0.019669-0.2690.394125
290.04420.60440.273146
300.0068380.09350.462801
31-0.167463-2.290.011568
32-0.086188-1.17860.120028
33-0.004047-0.05530.477964
34-0.051106-0.69890.242753
35-0.029146-0.39860.345335
360.2237413.05960.001271
37-0.05089-0.69590.243675
380.0236020.32280.37362
39-0.023409-0.32010.374619
400.0367320.50230.308022
410.0595430.81420.208271
42-0.011219-0.15340.439119
43-0.037958-0.51910.302166
44-0.104164-1.42440.077996
450.0127690.17460.430786
460.0095190.13020.448287
47-0.048617-0.66480.253492
48-0.040084-0.54810.292126



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 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')