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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 computationFri, 17 Oct 2014 14:23:23 +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/2014/Oct/17/t1413552232qsywkn4m3t07l3m.htm/, Retrieved Fri, 10 May 2024 15:01:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=243287, Retrieved Fri, 10 May 2024 15:01:53 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Gemiddelde consum...] [2014-10-17 13:14:10] [be6f075fcfffb6e204f178c2e69229d5]
- RMPD    [(Partial) Autocorrelation Function] [Werkloze beroepsb...] [2014-10-17 13:23:23] [30b408b6447afc100cbee3b5fe745b69] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
82
80
76
73
70
68
67
64
69
69
67
57
67
69
67
66
65
56
57
53
58
59
60
59
65
62
61
62
57
51
45
46
48
49
48
43
51
54
57
60
58
61
62
62
64
68
70
73
79
84
82
78
78
76
73
71
71
70
74
72
80
80
80
79
82
71
75
74
76
82
85
82
92
93
93
99
98
89
96
94
99
108
113
115
126
131
134
134
137
139
139
134
133
135
130
133

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=243287&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=243287&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=243287&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'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0062770.06120.475671
20.1292141.25940.105481
30.1518371.47990.071101
40.0586090.57130.284588
5-0.177612-1.73110.043336
60.1903521.85530.033325
7-0.269809-2.62980.004984
80.0345340.33660.368582
90.022240.21680.414426
10-0.051535-0.50230.308307
110.0414570.40410.343534
120.3804373.7080.000176
13-0.089146-0.86890.193548
140.1287551.25490.106288
150.0704320.68650.24704
16-0.090193-0.87910.190785
17-0.103587-1.00960.157616
18-0.029664-0.28910.386557
19-0.203644-1.98490.025021
20-0.016617-0.1620.435839
210.0038660.03770.485009
22-0.040457-0.39430.347112
230.0696780.67910.249352
240.2119152.06550.0208
250.0470350.45840.32384
260.0959990.93570.175906
270.0096460.0940.462647
28-0.022058-0.2150.415117
29-0.045184-0.44040.330323
30-0.104875-1.02220.154642
31-0.106987-1.04280.149849
32-0.062291-0.60710.272604
330.0432240.42130.337246
34-0.032327-0.31510.376695
350.0213960.20850.417626
360.1936631.88760.031066
370.107761.05030.148119
38-0.042694-0.41610.339125
390.0270580.26370.396278
400.0921060.89770.185797
41-0.117958-1.14970.126575
420.0267840.26110.397306
43-0.098741-0.96240.169144
44-0.012241-0.11930.452641
45-0.045902-0.44740.327804
460.0238080.23210.408497
47-0.053572-0.52220.301389
480.2485462.42250.008655

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.006277 & 0.0612 & 0.475671 \tabularnewline
2 & 0.129214 & 1.2594 & 0.105481 \tabularnewline
3 & 0.151837 & 1.4799 & 0.071101 \tabularnewline
4 & 0.058609 & 0.5713 & 0.284588 \tabularnewline
5 & -0.177612 & -1.7311 & 0.043336 \tabularnewline
6 & 0.190352 & 1.8553 & 0.033325 \tabularnewline
7 & -0.269809 & -2.6298 & 0.004984 \tabularnewline
8 & 0.034534 & 0.3366 & 0.368582 \tabularnewline
9 & 0.02224 & 0.2168 & 0.414426 \tabularnewline
10 & -0.051535 & -0.5023 & 0.308307 \tabularnewline
11 & 0.041457 & 0.4041 & 0.343534 \tabularnewline
12 & 0.380437 & 3.708 & 0.000176 \tabularnewline
13 & -0.089146 & -0.8689 & 0.193548 \tabularnewline
14 & 0.128755 & 1.2549 & 0.106288 \tabularnewline
15 & 0.070432 & 0.6865 & 0.24704 \tabularnewline
16 & -0.090193 & -0.8791 & 0.190785 \tabularnewline
17 & -0.103587 & -1.0096 & 0.157616 \tabularnewline
18 & -0.029664 & -0.2891 & 0.386557 \tabularnewline
19 & -0.203644 & -1.9849 & 0.025021 \tabularnewline
20 & -0.016617 & -0.162 & 0.435839 \tabularnewline
21 & 0.003866 & 0.0377 & 0.485009 \tabularnewline
22 & -0.040457 & -0.3943 & 0.347112 \tabularnewline
23 & 0.069678 & 0.6791 & 0.249352 \tabularnewline
24 & 0.211915 & 2.0655 & 0.0208 \tabularnewline
25 & 0.047035 & 0.4584 & 0.32384 \tabularnewline
26 & 0.095999 & 0.9357 & 0.175906 \tabularnewline
27 & 0.009646 & 0.094 & 0.462647 \tabularnewline
28 & -0.022058 & -0.215 & 0.415117 \tabularnewline
29 & -0.045184 & -0.4404 & 0.330323 \tabularnewline
30 & -0.104875 & -1.0222 & 0.154642 \tabularnewline
31 & -0.106987 & -1.0428 & 0.149849 \tabularnewline
32 & -0.062291 & -0.6071 & 0.272604 \tabularnewline
33 & 0.043224 & 0.4213 & 0.337246 \tabularnewline
34 & -0.032327 & -0.3151 & 0.376695 \tabularnewline
35 & 0.021396 & 0.2085 & 0.417626 \tabularnewline
36 & 0.193663 & 1.8876 & 0.031066 \tabularnewline
37 & 0.10776 & 1.0503 & 0.148119 \tabularnewline
38 & -0.042694 & -0.4161 & 0.339125 \tabularnewline
39 & 0.027058 & 0.2637 & 0.396278 \tabularnewline
40 & 0.092106 & 0.8977 & 0.185797 \tabularnewline
41 & -0.117958 & -1.1497 & 0.126575 \tabularnewline
42 & 0.026784 & 0.2611 & 0.397306 \tabularnewline
43 & -0.098741 & -0.9624 & 0.169144 \tabularnewline
44 & -0.012241 & -0.1193 & 0.452641 \tabularnewline
45 & -0.045902 & -0.4474 & 0.327804 \tabularnewline
46 & 0.023808 & 0.2321 & 0.408497 \tabularnewline
47 & -0.053572 & -0.5222 & 0.301389 \tabularnewline
48 & 0.248546 & 2.4225 & 0.008655 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=243287&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]0.006277[/C][C]0.0612[/C][C]0.475671[/C][/ROW]
[ROW][C]2[/C][C]0.129214[/C][C]1.2594[/C][C]0.105481[/C][/ROW]
[ROW][C]3[/C][C]0.151837[/C][C]1.4799[/C][C]0.071101[/C][/ROW]
[ROW][C]4[/C][C]0.058609[/C][C]0.5713[/C][C]0.284588[/C][/ROW]
[ROW][C]5[/C][C]-0.177612[/C][C]-1.7311[/C][C]0.043336[/C][/ROW]
[ROW][C]6[/C][C]0.190352[/C][C]1.8553[/C][C]0.033325[/C][/ROW]
[ROW][C]7[/C][C]-0.269809[/C][C]-2.6298[/C][C]0.004984[/C][/ROW]
[ROW][C]8[/C][C]0.034534[/C][C]0.3366[/C][C]0.368582[/C][/ROW]
[ROW][C]9[/C][C]0.02224[/C][C]0.2168[/C][C]0.414426[/C][/ROW]
[ROW][C]10[/C][C]-0.051535[/C][C]-0.5023[/C][C]0.308307[/C][/ROW]
[ROW][C]11[/C][C]0.041457[/C][C]0.4041[/C][C]0.343534[/C][/ROW]
[ROW][C]12[/C][C]0.380437[/C][C]3.708[/C][C]0.000176[/C][/ROW]
[ROW][C]13[/C][C]-0.089146[/C][C]-0.8689[/C][C]0.193548[/C][/ROW]
[ROW][C]14[/C][C]0.128755[/C][C]1.2549[/C][C]0.106288[/C][/ROW]
[ROW][C]15[/C][C]0.070432[/C][C]0.6865[/C][C]0.24704[/C][/ROW]
[ROW][C]16[/C][C]-0.090193[/C][C]-0.8791[/C][C]0.190785[/C][/ROW]
[ROW][C]17[/C][C]-0.103587[/C][C]-1.0096[/C][C]0.157616[/C][/ROW]
[ROW][C]18[/C][C]-0.029664[/C][C]-0.2891[/C][C]0.386557[/C][/ROW]
[ROW][C]19[/C][C]-0.203644[/C][C]-1.9849[/C][C]0.025021[/C][/ROW]
[ROW][C]20[/C][C]-0.016617[/C][C]-0.162[/C][C]0.435839[/C][/ROW]
[ROW][C]21[/C][C]0.003866[/C][C]0.0377[/C][C]0.485009[/C][/ROW]
[ROW][C]22[/C][C]-0.040457[/C][C]-0.3943[/C][C]0.347112[/C][/ROW]
[ROW][C]23[/C][C]0.069678[/C][C]0.6791[/C][C]0.249352[/C][/ROW]
[ROW][C]24[/C][C]0.211915[/C][C]2.0655[/C][C]0.0208[/C][/ROW]
[ROW][C]25[/C][C]0.047035[/C][C]0.4584[/C][C]0.32384[/C][/ROW]
[ROW][C]26[/C][C]0.095999[/C][C]0.9357[/C][C]0.175906[/C][/ROW]
[ROW][C]27[/C][C]0.009646[/C][C]0.094[/C][C]0.462647[/C][/ROW]
[ROW][C]28[/C][C]-0.022058[/C][C]-0.215[/C][C]0.415117[/C][/ROW]
[ROW][C]29[/C][C]-0.045184[/C][C]-0.4404[/C][C]0.330323[/C][/ROW]
[ROW][C]30[/C][C]-0.104875[/C][C]-1.0222[/C][C]0.154642[/C][/ROW]
[ROW][C]31[/C][C]-0.106987[/C][C]-1.0428[/C][C]0.149849[/C][/ROW]
[ROW][C]32[/C][C]-0.062291[/C][C]-0.6071[/C][C]0.272604[/C][/ROW]
[ROW][C]33[/C][C]0.043224[/C][C]0.4213[/C][C]0.337246[/C][/ROW]
[ROW][C]34[/C][C]-0.032327[/C][C]-0.3151[/C][C]0.376695[/C][/ROW]
[ROW][C]35[/C][C]0.021396[/C][C]0.2085[/C][C]0.417626[/C][/ROW]
[ROW][C]36[/C][C]0.193663[/C][C]1.8876[/C][C]0.031066[/C][/ROW]
[ROW][C]37[/C][C]0.10776[/C][C]1.0503[/C][C]0.148119[/C][/ROW]
[ROW][C]38[/C][C]-0.042694[/C][C]-0.4161[/C][C]0.339125[/C][/ROW]
[ROW][C]39[/C][C]0.027058[/C][C]0.2637[/C][C]0.396278[/C][/ROW]
[ROW][C]40[/C][C]0.092106[/C][C]0.8977[/C][C]0.185797[/C][/ROW]
[ROW][C]41[/C][C]-0.117958[/C][C]-1.1497[/C][C]0.126575[/C][/ROW]
[ROW][C]42[/C][C]0.026784[/C][C]0.2611[/C][C]0.397306[/C][/ROW]
[ROW][C]43[/C][C]-0.098741[/C][C]-0.9624[/C][C]0.169144[/C][/ROW]
[ROW][C]44[/C][C]-0.012241[/C][C]-0.1193[/C][C]0.452641[/C][/ROW]
[ROW][C]45[/C][C]-0.045902[/C][C]-0.4474[/C][C]0.327804[/C][/ROW]
[ROW][C]46[/C][C]0.023808[/C][C]0.2321[/C][C]0.408497[/C][/ROW]
[ROW][C]47[/C][C]-0.053572[/C][C]-0.5222[/C][C]0.301389[/C][/ROW]
[ROW][C]48[/C][C]0.248546[/C][C]2.4225[/C][C]0.008655[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=243287&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=243287&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
10.0062770.06120.475671
20.1292141.25940.105481
30.1518371.47990.071101
40.0586090.57130.284588
5-0.177612-1.73110.043336
60.1903521.85530.033325
7-0.269809-2.62980.004984
80.0345340.33660.368582
90.022240.21680.414426
10-0.051535-0.50230.308307
110.0414570.40410.343534
120.3804373.7080.000176
13-0.089146-0.86890.193548
140.1287551.25490.106288
150.0704320.68650.24704
16-0.090193-0.87910.190785
17-0.103587-1.00960.157616
18-0.029664-0.28910.386557
19-0.203644-1.98490.025021
20-0.016617-0.1620.435839
210.0038660.03770.485009
22-0.040457-0.39430.347112
230.0696780.67910.249352
240.2119152.06550.0208
250.0470350.45840.32384
260.0959990.93570.175906
270.0096460.0940.462647
28-0.022058-0.2150.415117
29-0.045184-0.44040.330323
30-0.104875-1.02220.154642
31-0.106987-1.04280.149849
32-0.062291-0.60710.272604
330.0432240.42130.337246
34-0.032327-0.31510.376695
350.0213960.20850.417626
360.1936631.88760.031066
370.107761.05030.148119
38-0.042694-0.41610.339125
390.0270580.26370.396278
400.0921060.89770.185797
41-0.117958-1.14970.126575
420.0267840.26110.397306
43-0.098741-0.96240.169144
44-0.012241-0.11930.452641
45-0.045902-0.44740.327804
460.0238080.23210.408497
47-0.053572-0.52220.301389
480.2485462.42250.008655






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0062770.06120.475671
20.129181.25910.105542
30.1528771.49010.06976
40.0450220.43880.330893
5-0.22445-2.18770.015573
60.1625191.5840.058254
7-0.261048-2.54440.00628
80.0815230.79460.214416
90.0459280.44770.327712
10-0.045596-0.44440.328876
110.1476381.4390.076719
120.2826582.7550.003517
13-0.036833-0.3590.360193
14-0.02517-0.24530.403368
15-0.047853-0.46640.320992
16-0.114705-1.1180.133191
17-0.073124-0.71270.238883
18-0.125454-1.22280.112219
190.0381990.37230.355244
20-0.014064-0.13710.445628
210.0932730.90910.182795
220.073630.71770.237365
23-0.011049-0.10770.457235
240.112481.09630.137856
250.0456840.44530.328567
26-0.048802-0.47570.317705
27-0.112653-1.0980.137489
280.0013780.01340.494658
290.0041850.04080.483775
30-0.070047-0.68270.248218
310.0481660.46950.319907
32-0.022141-0.21580.414802
330.1349791.31560.095735
34-0.014401-0.14040.444336
35-0.068451-0.66720.253137
360.1104721.07670.14216
37-0.00116-0.01130.495502
38-0.118443-1.15440.125607
39-0.083808-0.81690.208026
400.1648561.60680.055706
41-0.036376-0.35460.361855
420.1500261.46230.073484
43-0.054115-0.52740.299556
440.1051751.02510.153956
45-0.153597-1.49710.068844
46-0.012314-0.120.45236
47-0.035454-0.34560.365216
480.0201660.19660.422297

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.006277 & 0.0612 & 0.475671 \tabularnewline
2 & 0.12918 & 1.2591 & 0.105542 \tabularnewline
3 & 0.152877 & 1.4901 & 0.06976 \tabularnewline
4 & 0.045022 & 0.4388 & 0.330893 \tabularnewline
5 & -0.22445 & -2.1877 & 0.015573 \tabularnewline
6 & 0.162519 & 1.584 & 0.058254 \tabularnewline
7 & -0.261048 & -2.5444 & 0.00628 \tabularnewline
8 & 0.081523 & 0.7946 & 0.214416 \tabularnewline
9 & 0.045928 & 0.4477 & 0.327712 \tabularnewline
10 & -0.045596 & -0.4444 & 0.328876 \tabularnewline
11 & 0.147638 & 1.439 & 0.076719 \tabularnewline
12 & 0.282658 & 2.755 & 0.003517 \tabularnewline
13 & -0.036833 & -0.359 & 0.360193 \tabularnewline
14 & -0.02517 & -0.2453 & 0.403368 \tabularnewline
15 & -0.047853 & -0.4664 & 0.320992 \tabularnewline
16 & -0.114705 & -1.118 & 0.133191 \tabularnewline
17 & -0.073124 & -0.7127 & 0.238883 \tabularnewline
18 & -0.125454 & -1.2228 & 0.112219 \tabularnewline
19 & 0.038199 & 0.3723 & 0.355244 \tabularnewline
20 & -0.014064 & -0.1371 & 0.445628 \tabularnewline
21 & 0.093273 & 0.9091 & 0.182795 \tabularnewline
22 & 0.07363 & 0.7177 & 0.237365 \tabularnewline
23 & -0.011049 & -0.1077 & 0.457235 \tabularnewline
24 & 0.11248 & 1.0963 & 0.137856 \tabularnewline
25 & 0.045684 & 0.4453 & 0.328567 \tabularnewline
26 & -0.048802 & -0.4757 & 0.317705 \tabularnewline
27 & -0.112653 & -1.098 & 0.137489 \tabularnewline
28 & 0.001378 & 0.0134 & 0.494658 \tabularnewline
29 & 0.004185 & 0.0408 & 0.483775 \tabularnewline
30 & -0.070047 & -0.6827 & 0.248218 \tabularnewline
31 & 0.048166 & 0.4695 & 0.319907 \tabularnewline
32 & -0.022141 & -0.2158 & 0.414802 \tabularnewline
33 & 0.134979 & 1.3156 & 0.095735 \tabularnewline
34 & -0.014401 & -0.1404 & 0.444336 \tabularnewline
35 & -0.068451 & -0.6672 & 0.253137 \tabularnewline
36 & 0.110472 & 1.0767 & 0.14216 \tabularnewline
37 & -0.00116 & -0.0113 & 0.495502 \tabularnewline
38 & -0.118443 & -1.1544 & 0.125607 \tabularnewline
39 & -0.083808 & -0.8169 & 0.208026 \tabularnewline
40 & 0.164856 & 1.6068 & 0.055706 \tabularnewline
41 & -0.036376 & -0.3546 & 0.361855 \tabularnewline
42 & 0.150026 & 1.4623 & 0.073484 \tabularnewline
43 & -0.054115 & -0.5274 & 0.299556 \tabularnewline
44 & 0.105175 & 1.0251 & 0.153956 \tabularnewline
45 & -0.153597 & -1.4971 & 0.068844 \tabularnewline
46 & -0.012314 & -0.12 & 0.45236 \tabularnewline
47 & -0.035454 & -0.3456 & 0.365216 \tabularnewline
48 & 0.020166 & 0.1966 & 0.422297 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=243287&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]0.006277[/C][C]0.0612[/C][C]0.475671[/C][/ROW]
[ROW][C]2[/C][C]0.12918[/C][C]1.2591[/C][C]0.105542[/C][/ROW]
[ROW][C]3[/C][C]0.152877[/C][C]1.4901[/C][C]0.06976[/C][/ROW]
[ROW][C]4[/C][C]0.045022[/C][C]0.4388[/C][C]0.330893[/C][/ROW]
[ROW][C]5[/C][C]-0.22445[/C][C]-2.1877[/C][C]0.015573[/C][/ROW]
[ROW][C]6[/C][C]0.162519[/C][C]1.584[/C][C]0.058254[/C][/ROW]
[ROW][C]7[/C][C]-0.261048[/C][C]-2.5444[/C][C]0.00628[/C][/ROW]
[ROW][C]8[/C][C]0.081523[/C][C]0.7946[/C][C]0.214416[/C][/ROW]
[ROW][C]9[/C][C]0.045928[/C][C]0.4477[/C][C]0.327712[/C][/ROW]
[ROW][C]10[/C][C]-0.045596[/C][C]-0.4444[/C][C]0.328876[/C][/ROW]
[ROW][C]11[/C][C]0.147638[/C][C]1.439[/C][C]0.076719[/C][/ROW]
[ROW][C]12[/C][C]0.282658[/C][C]2.755[/C][C]0.003517[/C][/ROW]
[ROW][C]13[/C][C]-0.036833[/C][C]-0.359[/C][C]0.360193[/C][/ROW]
[ROW][C]14[/C][C]-0.02517[/C][C]-0.2453[/C][C]0.403368[/C][/ROW]
[ROW][C]15[/C][C]-0.047853[/C][C]-0.4664[/C][C]0.320992[/C][/ROW]
[ROW][C]16[/C][C]-0.114705[/C][C]-1.118[/C][C]0.133191[/C][/ROW]
[ROW][C]17[/C][C]-0.073124[/C][C]-0.7127[/C][C]0.238883[/C][/ROW]
[ROW][C]18[/C][C]-0.125454[/C][C]-1.2228[/C][C]0.112219[/C][/ROW]
[ROW][C]19[/C][C]0.038199[/C][C]0.3723[/C][C]0.355244[/C][/ROW]
[ROW][C]20[/C][C]-0.014064[/C][C]-0.1371[/C][C]0.445628[/C][/ROW]
[ROW][C]21[/C][C]0.093273[/C][C]0.9091[/C][C]0.182795[/C][/ROW]
[ROW][C]22[/C][C]0.07363[/C][C]0.7177[/C][C]0.237365[/C][/ROW]
[ROW][C]23[/C][C]-0.011049[/C][C]-0.1077[/C][C]0.457235[/C][/ROW]
[ROW][C]24[/C][C]0.11248[/C][C]1.0963[/C][C]0.137856[/C][/ROW]
[ROW][C]25[/C][C]0.045684[/C][C]0.4453[/C][C]0.328567[/C][/ROW]
[ROW][C]26[/C][C]-0.048802[/C][C]-0.4757[/C][C]0.317705[/C][/ROW]
[ROW][C]27[/C][C]-0.112653[/C][C]-1.098[/C][C]0.137489[/C][/ROW]
[ROW][C]28[/C][C]0.001378[/C][C]0.0134[/C][C]0.494658[/C][/ROW]
[ROW][C]29[/C][C]0.004185[/C][C]0.0408[/C][C]0.483775[/C][/ROW]
[ROW][C]30[/C][C]-0.070047[/C][C]-0.6827[/C][C]0.248218[/C][/ROW]
[ROW][C]31[/C][C]0.048166[/C][C]0.4695[/C][C]0.319907[/C][/ROW]
[ROW][C]32[/C][C]-0.022141[/C][C]-0.2158[/C][C]0.414802[/C][/ROW]
[ROW][C]33[/C][C]0.134979[/C][C]1.3156[/C][C]0.095735[/C][/ROW]
[ROW][C]34[/C][C]-0.014401[/C][C]-0.1404[/C][C]0.444336[/C][/ROW]
[ROW][C]35[/C][C]-0.068451[/C][C]-0.6672[/C][C]0.253137[/C][/ROW]
[ROW][C]36[/C][C]0.110472[/C][C]1.0767[/C][C]0.14216[/C][/ROW]
[ROW][C]37[/C][C]-0.00116[/C][C]-0.0113[/C][C]0.495502[/C][/ROW]
[ROW][C]38[/C][C]-0.118443[/C][C]-1.1544[/C][C]0.125607[/C][/ROW]
[ROW][C]39[/C][C]-0.083808[/C][C]-0.8169[/C][C]0.208026[/C][/ROW]
[ROW][C]40[/C][C]0.164856[/C][C]1.6068[/C][C]0.055706[/C][/ROW]
[ROW][C]41[/C][C]-0.036376[/C][C]-0.3546[/C][C]0.361855[/C][/ROW]
[ROW][C]42[/C][C]0.150026[/C][C]1.4623[/C][C]0.073484[/C][/ROW]
[ROW][C]43[/C][C]-0.054115[/C][C]-0.5274[/C][C]0.299556[/C][/ROW]
[ROW][C]44[/C][C]0.105175[/C][C]1.0251[/C][C]0.153956[/C][/ROW]
[ROW][C]45[/C][C]-0.153597[/C][C]-1.4971[/C][C]0.068844[/C][/ROW]
[ROW][C]46[/C][C]-0.012314[/C][C]-0.12[/C][C]0.45236[/C][/ROW]
[ROW][C]47[/C][C]-0.035454[/C][C]-0.3456[/C][C]0.365216[/C][/ROW]
[ROW][C]48[/C][C]0.020166[/C][C]0.1966[/C][C]0.422297[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=243287&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=243287&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
10.0062770.06120.475671
20.129181.25910.105542
30.1528771.49010.06976
40.0450220.43880.330893
5-0.22445-2.18770.015573
60.1625191.5840.058254
7-0.261048-2.54440.00628
80.0815230.79460.214416
90.0459280.44770.327712
10-0.045596-0.44440.328876
110.1476381.4390.076719
120.2826582.7550.003517
13-0.036833-0.3590.360193
14-0.02517-0.24530.403368
15-0.047853-0.46640.320992
16-0.114705-1.1180.133191
17-0.073124-0.71270.238883
18-0.125454-1.22280.112219
190.0381990.37230.355244
20-0.014064-0.13710.445628
210.0932730.90910.182795
220.073630.71770.237365
23-0.011049-0.10770.457235
240.112481.09630.137856
250.0456840.44530.328567
26-0.048802-0.47570.317705
27-0.112653-1.0980.137489
280.0013780.01340.494658
290.0041850.04080.483775
30-0.070047-0.68270.248218
310.0481660.46950.319907
32-0.022141-0.21580.414802
330.1349791.31560.095735
34-0.014401-0.14040.444336
35-0.068451-0.66720.253137
360.1104721.07670.14216
37-0.00116-0.01130.495502
38-0.118443-1.15440.125607
39-0.083808-0.81690.208026
400.1648561.60680.055706
41-0.036376-0.35460.361855
420.1500261.46230.073484
43-0.054115-0.52740.299556
440.1051751.02510.153956
45-0.153597-1.49710.068844
46-0.012314-0.120.45236
47-0.035454-0.34560.365216
480.0201660.19660.422297


Figures (Output of Computation)

Input Parameters & R Code

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