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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 computationSun, 10 Jan 2016 11:26:30 +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/2016/Jan/10/t1452425302h85y4gwd274oacx.htm/, Retrieved Sun, 05 May 2024 06:09:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=287748, Retrieved Sun, 05 May 2024 06:09:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [differentiëren re...] [2016-01-10 11:26:30] [442c3b7d1457f8bc4e82a9331e05e70d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
85.13
85.54
85.47
85.78
86.07
86.05
86.32
86.43
86.41
86.38
86.59
86.68
86.87
87.32
87.13
87.42
87.22
87.17
87.52
87.49
87.53
87.93
88.54
88.96
89.3
90.01
90.52
90.64
91.25
91.59
92.09
91.81
92.03
92.15
91.98
92.11
92.28
92.53
91.97
92.05
91.87
91.49
91.48
91.63
91.46
91.61
91.7
91.87
92.21
92.65
92.83
93.02
93.33
93.35
93.45
93.51
93.8
93.94
94.02
94.26
94.71
95.26
95.54
95.69
96.03
96.4
96.55
96.45
96.65
96.84
97.21
97.31
97.91
98.51
98.54
98.52
98.66
98.53
98.71
98.92
98.96
99.25
99.32
99.41
99.36
99.58
99.77
99.77
100.03
100.2
100.24
100.1
100.03
100.18
100.29
100.41
100.6
100.75
100.79
100.44
100.29
100.34
100.46
100.12
100.06
100.28
100.28
100.4

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=287748&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=287748&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287748&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
10.242242.50570.006863
20.1969892.03770.022025
30.3074073.17980.000964
40.1819131.88170.031295
50.0214910.22230.412252
6-0.051427-0.5320.297927
70.1391241.43910.076519
8-0.002846-0.02940.488286
9-0.002569-0.02660.489425
10-0.077085-0.79740.213501
11-0.072705-0.75210.226831
120.0158370.16380.435092
13-0.100501-1.03960.150436
14-0.134249-1.38870.083906
15-0.073665-0.7620.223868
16-0.202446-2.09410.019306
17-0.049927-0.51640.303303
18-0.210657-2.1790.015761
19-0.145748-1.50760.067298
20-0.091752-0.94910.172356
21-0.04126-0.42680.335192
220.0462210.47810.316773
23-0.025007-0.25870.398192
240.2002442.07130.020366
250.0314520.32530.37278
26-0.022958-0.23750.40637
27-0.023484-0.24290.404268
28-0.121369-1.25540.106026
29-0.01304-0.13490.446478
30-0.11868-1.22760.111139
31-0.132836-1.37410.086147
32-0.06546-0.67710.249894
330.0417790.43220.333247
34-0.070513-0.72940.233678
35-0.046666-0.48270.315143
360.2047142.11760.018264
370.0291420.30140.381831
38-0.055979-0.5790.281887
390.0137270.1420.443676
40-0.015313-0.15840.437222
41-0.074302-0.76860.221915
42-0.030458-0.31510.376664
430.0010180.01050.49581
440.0401080.41490.339531
45-0.004407-0.04560.481864
460.0822710.8510.198331
470.0210810.21810.413897
480.0814530.84260.200678

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.24224 & 2.5057 & 0.006863 \tabularnewline
2 & 0.196989 & 2.0377 & 0.022025 \tabularnewline
3 & 0.307407 & 3.1798 & 0.000964 \tabularnewline
4 & 0.181913 & 1.8817 & 0.031295 \tabularnewline
5 & 0.021491 & 0.2223 & 0.412252 \tabularnewline
6 & -0.051427 & -0.532 & 0.297927 \tabularnewline
7 & 0.139124 & 1.4391 & 0.076519 \tabularnewline
8 & -0.002846 & -0.0294 & 0.488286 \tabularnewline
9 & -0.002569 & -0.0266 & 0.489425 \tabularnewline
10 & -0.077085 & -0.7974 & 0.213501 \tabularnewline
11 & -0.072705 & -0.7521 & 0.226831 \tabularnewline
12 & 0.015837 & 0.1638 & 0.435092 \tabularnewline
13 & -0.100501 & -1.0396 & 0.150436 \tabularnewline
14 & -0.134249 & -1.3887 & 0.083906 \tabularnewline
15 & -0.073665 & -0.762 & 0.223868 \tabularnewline
16 & -0.202446 & -2.0941 & 0.019306 \tabularnewline
17 & -0.049927 & -0.5164 & 0.303303 \tabularnewline
18 & -0.210657 & -2.179 & 0.015761 \tabularnewline
19 & -0.145748 & -1.5076 & 0.067298 \tabularnewline
20 & -0.091752 & -0.9491 & 0.172356 \tabularnewline
21 & -0.04126 & -0.4268 & 0.335192 \tabularnewline
22 & 0.046221 & 0.4781 & 0.316773 \tabularnewline
23 & -0.025007 & -0.2587 & 0.398192 \tabularnewline
24 & 0.200244 & 2.0713 & 0.020366 \tabularnewline
25 & 0.031452 & 0.3253 & 0.37278 \tabularnewline
26 & -0.022958 & -0.2375 & 0.40637 \tabularnewline
27 & -0.023484 & -0.2429 & 0.404268 \tabularnewline
28 & -0.121369 & -1.2554 & 0.106026 \tabularnewline
29 & -0.01304 & -0.1349 & 0.446478 \tabularnewline
30 & -0.11868 & -1.2276 & 0.111139 \tabularnewline
31 & -0.132836 & -1.3741 & 0.086147 \tabularnewline
32 & -0.06546 & -0.6771 & 0.249894 \tabularnewline
33 & 0.041779 & 0.4322 & 0.333247 \tabularnewline
34 & -0.070513 & -0.7294 & 0.233678 \tabularnewline
35 & -0.046666 & -0.4827 & 0.315143 \tabularnewline
36 & 0.204714 & 2.1176 & 0.018264 \tabularnewline
37 & 0.029142 & 0.3014 & 0.381831 \tabularnewline
38 & -0.055979 & -0.579 & 0.281887 \tabularnewline
39 & 0.013727 & 0.142 & 0.443676 \tabularnewline
40 & -0.015313 & -0.1584 & 0.437222 \tabularnewline
41 & -0.074302 & -0.7686 & 0.221915 \tabularnewline
42 & -0.030458 & -0.3151 & 0.376664 \tabularnewline
43 & 0.001018 & 0.0105 & 0.49581 \tabularnewline
44 & 0.040108 & 0.4149 & 0.339531 \tabularnewline
45 & -0.004407 & -0.0456 & 0.481864 \tabularnewline
46 & 0.082271 & 0.851 & 0.198331 \tabularnewline
47 & 0.021081 & 0.2181 & 0.413897 \tabularnewline
48 & 0.081453 & 0.8426 & 0.200678 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287748&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]0.24224[/C][C]2.5057[/C][C]0.006863[/C][/ROW]
[ROW][C]2[/C][C]0.196989[/C][C]2.0377[/C][C]0.022025[/C][/ROW]
[ROW][C]3[/C][C]0.307407[/C][C]3.1798[/C][C]0.000964[/C][/ROW]
[ROW][C]4[/C][C]0.181913[/C][C]1.8817[/C][C]0.031295[/C][/ROW]
[ROW][C]5[/C][C]0.021491[/C][C]0.2223[/C][C]0.412252[/C][/ROW]
[ROW][C]6[/C][C]-0.051427[/C][C]-0.532[/C][C]0.297927[/C][/ROW]
[ROW][C]7[/C][C]0.139124[/C][C]1.4391[/C][C]0.076519[/C][/ROW]
[ROW][C]8[/C][C]-0.002846[/C][C]-0.0294[/C][C]0.488286[/C][/ROW]
[ROW][C]9[/C][C]-0.002569[/C][C]-0.0266[/C][C]0.489425[/C][/ROW]
[ROW][C]10[/C][C]-0.077085[/C][C]-0.7974[/C][C]0.213501[/C][/ROW]
[ROW][C]11[/C][C]-0.072705[/C][C]-0.7521[/C][C]0.226831[/C][/ROW]
[ROW][C]12[/C][C]0.015837[/C][C]0.1638[/C][C]0.435092[/C][/ROW]
[ROW][C]13[/C][C]-0.100501[/C][C]-1.0396[/C][C]0.150436[/C][/ROW]
[ROW][C]14[/C][C]-0.134249[/C][C]-1.3887[/C][C]0.083906[/C][/ROW]
[ROW][C]15[/C][C]-0.073665[/C][C]-0.762[/C][C]0.223868[/C][/ROW]
[ROW][C]16[/C][C]-0.202446[/C][C]-2.0941[/C][C]0.019306[/C][/ROW]
[ROW][C]17[/C][C]-0.049927[/C][C]-0.5164[/C][C]0.303303[/C][/ROW]
[ROW][C]18[/C][C]-0.210657[/C][C]-2.179[/C][C]0.015761[/C][/ROW]
[ROW][C]19[/C][C]-0.145748[/C][C]-1.5076[/C][C]0.067298[/C][/ROW]
[ROW][C]20[/C][C]-0.091752[/C][C]-0.9491[/C][C]0.172356[/C][/ROW]
[ROW][C]21[/C][C]-0.04126[/C][C]-0.4268[/C][C]0.335192[/C][/ROW]
[ROW][C]22[/C][C]0.046221[/C][C]0.4781[/C][C]0.316773[/C][/ROW]
[ROW][C]23[/C][C]-0.025007[/C][C]-0.2587[/C][C]0.398192[/C][/ROW]
[ROW][C]24[/C][C]0.200244[/C][C]2.0713[/C][C]0.020366[/C][/ROW]
[ROW][C]25[/C][C]0.031452[/C][C]0.3253[/C][C]0.37278[/C][/ROW]
[ROW][C]26[/C][C]-0.022958[/C][C]-0.2375[/C][C]0.40637[/C][/ROW]
[ROW][C]27[/C][C]-0.023484[/C][C]-0.2429[/C][C]0.404268[/C][/ROW]
[ROW][C]28[/C][C]-0.121369[/C][C]-1.2554[/C][C]0.106026[/C][/ROW]
[ROW][C]29[/C][C]-0.01304[/C][C]-0.1349[/C][C]0.446478[/C][/ROW]
[ROW][C]30[/C][C]-0.11868[/C][C]-1.2276[/C][C]0.111139[/C][/ROW]
[ROW][C]31[/C][C]-0.132836[/C][C]-1.3741[/C][C]0.086147[/C][/ROW]
[ROW][C]32[/C][C]-0.06546[/C][C]-0.6771[/C][C]0.249894[/C][/ROW]
[ROW][C]33[/C][C]0.041779[/C][C]0.4322[/C][C]0.333247[/C][/ROW]
[ROW][C]34[/C][C]-0.070513[/C][C]-0.7294[/C][C]0.233678[/C][/ROW]
[ROW][C]35[/C][C]-0.046666[/C][C]-0.4827[/C][C]0.315143[/C][/ROW]
[ROW][C]36[/C][C]0.204714[/C][C]2.1176[/C][C]0.018264[/C][/ROW]
[ROW][C]37[/C][C]0.029142[/C][C]0.3014[/C][C]0.381831[/C][/ROW]
[ROW][C]38[/C][C]-0.055979[/C][C]-0.579[/C][C]0.281887[/C][/ROW]
[ROW][C]39[/C][C]0.013727[/C][C]0.142[/C][C]0.443676[/C][/ROW]
[ROW][C]40[/C][C]-0.015313[/C][C]-0.1584[/C][C]0.437222[/C][/ROW]
[ROW][C]41[/C][C]-0.074302[/C][C]-0.7686[/C][C]0.221915[/C][/ROW]
[ROW][C]42[/C][C]-0.030458[/C][C]-0.3151[/C][C]0.376664[/C][/ROW]
[ROW][C]43[/C][C]0.001018[/C][C]0.0105[/C][C]0.49581[/C][/ROW]
[ROW][C]44[/C][C]0.040108[/C][C]0.4149[/C][C]0.339531[/C][/ROW]
[ROW][C]45[/C][C]-0.004407[/C][C]-0.0456[/C][C]0.481864[/C][/ROW]
[ROW][C]46[/C][C]0.082271[/C][C]0.851[/C][C]0.198331[/C][/ROW]
[ROW][C]47[/C][C]0.021081[/C][C]0.2181[/C][C]0.413897[/C][/ROW]
[ROW][C]48[/C][C]0.081453[/C][C]0.8426[/C][C]0.200678[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287748&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287748&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
10.242242.50570.006863
20.1969892.03770.022025
30.3074073.17980.000964
40.1819131.88170.031295
50.0214910.22230.412252
6-0.051427-0.5320.297927
70.1391241.43910.076519
8-0.002846-0.02940.488286
9-0.002569-0.02660.489425
10-0.077085-0.79740.213501
11-0.072705-0.75210.226831
120.0158370.16380.435092
13-0.100501-1.03960.150436
14-0.134249-1.38870.083906
15-0.073665-0.7620.223868
16-0.202446-2.09410.019306
17-0.049927-0.51640.303303
18-0.210657-2.1790.015761
19-0.145748-1.50760.067298
20-0.091752-0.94910.172356
21-0.04126-0.42680.335192
220.0462210.47810.316773
23-0.025007-0.25870.398192
240.2002442.07130.020366
250.0314520.32530.37278
26-0.022958-0.23750.40637
27-0.023484-0.24290.404268
28-0.121369-1.25540.106026
29-0.01304-0.13490.446478
30-0.11868-1.22760.111139
31-0.132836-1.37410.086147
32-0.06546-0.67710.249894
330.0417790.43220.333247
34-0.070513-0.72940.233678
35-0.046666-0.48270.315143
360.2047142.11760.018264
370.0291420.30140.381831
38-0.055979-0.5790.281887
390.0137270.1420.443676
40-0.015313-0.15840.437222
41-0.074302-0.76860.221915
42-0.030458-0.31510.376664
430.0010180.01050.49581
440.0401080.41490.339531
45-0.004407-0.04560.481864
460.0822710.8510.198331
470.0210810.21810.413897
480.0814530.84260.200678






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.242242.50570.006863
20.146931.51990.065748
30.2509312.59560.005383
40.0581780.60180.274291
5-0.111434-1.15270.125804
6-0.166139-1.71860.044294
70.1431341.48060.070828
8-0.000836-0.00860.496558
90.0488650.50550.307138
10-0.156986-1.62390.053672
11-0.098287-1.01670.155798
120.0780420.80730.210651
130.004870.05040.47996
14-0.098852-1.02250.154417
15-0.052723-0.54540.293318
16-0.22743-2.35260.010237
170.1613351.66890.049035
18-0.118716-1.2280.111069
19-0.027449-0.28390.388504
20-0.062887-0.65050.258378
210.0789970.81720.207828
220.1631131.68730.047234
230.060760.62850.265507
240.0827730.85620.196896
25-0.103557-1.07120.143244
26-0.151715-1.56940.059759
27-0.063949-0.66150.254858
28-0.144218-1.49180.069347
290.049940.51660.303256
30-0.074363-0.76920.221729
31-0.134101-1.38720.084139
32-0.046336-0.47930.316351
330.1980852.0490.021454
34-0.053366-0.5520.291041
350.0864390.89410.186628
360.1181991.22270.112071
37-0.029721-0.30740.379555
38-0.038776-0.40110.344571
39-0.095067-0.98340.16382
40-0.02859-0.29570.384004
41-0.082794-0.85640.196838
420.0748090.77380.220368
430.0248390.25690.39886
44-0.00852-0.08810.464969
45-0.092567-0.95750.17023
460.0005880.00610.497581
47-0.041746-0.43180.33337
480.0483010.49960.309181

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.24224 & 2.5057 & 0.006863 \tabularnewline
2 & 0.14693 & 1.5199 & 0.065748 \tabularnewline
3 & 0.250931 & 2.5956 & 0.005383 \tabularnewline
4 & 0.058178 & 0.6018 & 0.274291 \tabularnewline
5 & -0.111434 & -1.1527 & 0.125804 \tabularnewline
6 & -0.166139 & -1.7186 & 0.044294 \tabularnewline
7 & 0.143134 & 1.4806 & 0.070828 \tabularnewline
8 & -0.000836 & -0.0086 & 0.496558 \tabularnewline
9 & 0.048865 & 0.5055 & 0.307138 \tabularnewline
10 & -0.156986 & -1.6239 & 0.053672 \tabularnewline
11 & -0.098287 & -1.0167 & 0.155798 \tabularnewline
12 & 0.078042 & 0.8073 & 0.210651 \tabularnewline
13 & 0.00487 & 0.0504 & 0.47996 \tabularnewline
14 & -0.098852 & -1.0225 & 0.154417 \tabularnewline
15 & -0.052723 & -0.5454 & 0.293318 \tabularnewline
16 & -0.22743 & -2.3526 & 0.010237 \tabularnewline
17 & 0.161335 & 1.6689 & 0.049035 \tabularnewline
18 & -0.118716 & -1.228 & 0.111069 \tabularnewline
19 & -0.027449 & -0.2839 & 0.388504 \tabularnewline
20 & -0.062887 & -0.6505 & 0.258378 \tabularnewline
21 & 0.078997 & 0.8172 & 0.207828 \tabularnewline
22 & 0.163113 & 1.6873 & 0.047234 \tabularnewline
23 & 0.06076 & 0.6285 & 0.265507 \tabularnewline
24 & 0.082773 & 0.8562 & 0.196896 \tabularnewline
25 & -0.103557 & -1.0712 & 0.143244 \tabularnewline
26 & -0.151715 & -1.5694 & 0.059759 \tabularnewline
27 & -0.063949 & -0.6615 & 0.254858 \tabularnewline
28 & -0.144218 & -1.4918 & 0.069347 \tabularnewline
29 & 0.04994 & 0.5166 & 0.303256 \tabularnewline
30 & -0.074363 & -0.7692 & 0.221729 \tabularnewline
31 & -0.134101 & -1.3872 & 0.084139 \tabularnewline
32 & -0.046336 & -0.4793 & 0.316351 \tabularnewline
33 & 0.198085 & 2.049 & 0.021454 \tabularnewline
34 & -0.053366 & -0.552 & 0.291041 \tabularnewline
35 & 0.086439 & 0.8941 & 0.186628 \tabularnewline
36 & 0.118199 & 1.2227 & 0.112071 \tabularnewline
37 & -0.029721 & -0.3074 & 0.379555 \tabularnewline
38 & -0.038776 & -0.4011 & 0.344571 \tabularnewline
39 & -0.095067 & -0.9834 & 0.16382 \tabularnewline
40 & -0.02859 & -0.2957 & 0.384004 \tabularnewline
41 & -0.082794 & -0.8564 & 0.196838 \tabularnewline
42 & 0.074809 & 0.7738 & 0.220368 \tabularnewline
43 & 0.024839 & 0.2569 & 0.39886 \tabularnewline
44 & -0.00852 & -0.0881 & 0.464969 \tabularnewline
45 & -0.092567 & -0.9575 & 0.17023 \tabularnewline
46 & 0.000588 & 0.0061 & 0.497581 \tabularnewline
47 & -0.041746 & -0.4318 & 0.33337 \tabularnewline
48 & 0.048301 & 0.4996 & 0.309181 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287748&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]0.24224[/C][C]2.5057[/C][C]0.006863[/C][/ROW]
[ROW][C]2[/C][C]0.14693[/C][C]1.5199[/C][C]0.065748[/C][/ROW]
[ROW][C]3[/C][C]0.250931[/C][C]2.5956[/C][C]0.005383[/C][/ROW]
[ROW][C]4[/C][C]0.058178[/C][C]0.6018[/C][C]0.274291[/C][/ROW]
[ROW][C]5[/C][C]-0.111434[/C][C]-1.1527[/C][C]0.125804[/C][/ROW]
[ROW][C]6[/C][C]-0.166139[/C][C]-1.7186[/C][C]0.044294[/C][/ROW]
[ROW][C]7[/C][C]0.143134[/C][C]1.4806[/C][C]0.070828[/C][/ROW]
[ROW][C]8[/C][C]-0.000836[/C][C]-0.0086[/C][C]0.496558[/C][/ROW]
[ROW][C]9[/C][C]0.048865[/C][C]0.5055[/C][C]0.307138[/C][/ROW]
[ROW][C]10[/C][C]-0.156986[/C][C]-1.6239[/C][C]0.053672[/C][/ROW]
[ROW][C]11[/C][C]-0.098287[/C][C]-1.0167[/C][C]0.155798[/C][/ROW]
[ROW][C]12[/C][C]0.078042[/C][C]0.8073[/C][C]0.210651[/C][/ROW]
[ROW][C]13[/C][C]0.00487[/C][C]0.0504[/C][C]0.47996[/C][/ROW]
[ROW][C]14[/C][C]-0.098852[/C][C]-1.0225[/C][C]0.154417[/C][/ROW]
[ROW][C]15[/C][C]-0.052723[/C][C]-0.5454[/C][C]0.293318[/C][/ROW]
[ROW][C]16[/C][C]-0.22743[/C][C]-2.3526[/C][C]0.010237[/C][/ROW]
[ROW][C]17[/C][C]0.161335[/C][C]1.6689[/C][C]0.049035[/C][/ROW]
[ROW][C]18[/C][C]-0.118716[/C][C]-1.228[/C][C]0.111069[/C][/ROW]
[ROW][C]19[/C][C]-0.027449[/C][C]-0.2839[/C][C]0.388504[/C][/ROW]
[ROW][C]20[/C][C]-0.062887[/C][C]-0.6505[/C][C]0.258378[/C][/ROW]
[ROW][C]21[/C][C]0.078997[/C][C]0.8172[/C][C]0.207828[/C][/ROW]
[ROW][C]22[/C][C]0.163113[/C][C]1.6873[/C][C]0.047234[/C][/ROW]
[ROW][C]23[/C][C]0.06076[/C][C]0.6285[/C][C]0.265507[/C][/ROW]
[ROW][C]24[/C][C]0.082773[/C][C]0.8562[/C][C]0.196896[/C][/ROW]
[ROW][C]25[/C][C]-0.103557[/C][C]-1.0712[/C][C]0.143244[/C][/ROW]
[ROW][C]26[/C][C]-0.151715[/C][C]-1.5694[/C][C]0.059759[/C][/ROW]
[ROW][C]27[/C][C]-0.063949[/C][C]-0.6615[/C][C]0.254858[/C][/ROW]
[ROW][C]28[/C][C]-0.144218[/C][C]-1.4918[/C][C]0.069347[/C][/ROW]
[ROW][C]29[/C][C]0.04994[/C][C]0.5166[/C][C]0.303256[/C][/ROW]
[ROW][C]30[/C][C]-0.074363[/C][C]-0.7692[/C][C]0.221729[/C][/ROW]
[ROW][C]31[/C][C]-0.134101[/C][C]-1.3872[/C][C]0.084139[/C][/ROW]
[ROW][C]32[/C][C]-0.046336[/C][C]-0.4793[/C][C]0.316351[/C][/ROW]
[ROW][C]33[/C][C]0.198085[/C][C]2.049[/C][C]0.021454[/C][/ROW]
[ROW][C]34[/C][C]-0.053366[/C][C]-0.552[/C][C]0.291041[/C][/ROW]
[ROW][C]35[/C][C]0.086439[/C][C]0.8941[/C][C]0.186628[/C][/ROW]
[ROW][C]36[/C][C]0.118199[/C][C]1.2227[/C][C]0.112071[/C][/ROW]
[ROW][C]37[/C][C]-0.029721[/C][C]-0.3074[/C][C]0.379555[/C][/ROW]
[ROW][C]38[/C][C]-0.038776[/C][C]-0.4011[/C][C]0.344571[/C][/ROW]
[ROW][C]39[/C][C]-0.095067[/C][C]-0.9834[/C][C]0.16382[/C][/ROW]
[ROW][C]40[/C][C]-0.02859[/C][C]-0.2957[/C][C]0.384004[/C][/ROW]
[ROW][C]41[/C][C]-0.082794[/C][C]-0.8564[/C][C]0.196838[/C][/ROW]
[ROW][C]42[/C][C]0.074809[/C][C]0.7738[/C][C]0.220368[/C][/ROW]
[ROW][C]43[/C][C]0.024839[/C][C]0.2569[/C][C]0.39886[/C][/ROW]
[ROW][C]44[/C][C]-0.00852[/C][C]-0.0881[/C][C]0.464969[/C][/ROW]
[ROW][C]45[/C][C]-0.092567[/C][C]-0.9575[/C][C]0.17023[/C][/ROW]
[ROW][C]46[/C][C]0.000588[/C][C]0.0061[/C][C]0.497581[/C][/ROW]
[ROW][C]47[/C][C]-0.041746[/C][C]-0.4318[/C][C]0.33337[/C][/ROW]
[ROW][C]48[/C][C]0.048301[/C][C]0.4996[/C][C]0.309181[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287748&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287748&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
10.242242.50570.006863
20.146931.51990.065748
30.2509312.59560.005383
40.0581780.60180.274291
5-0.111434-1.15270.125804
6-0.166139-1.71860.044294
70.1431341.48060.070828
8-0.000836-0.00860.496558
90.0488650.50550.307138
10-0.156986-1.62390.053672
11-0.098287-1.01670.155798
120.0780420.80730.210651
130.004870.05040.47996
14-0.098852-1.02250.154417
15-0.052723-0.54540.293318
16-0.22743-2.35260.010237
170.1613351.66890.049035
18-0.118716-1.2280.111069
19-0.027449-0.28390.388504
20-0.062887-0.65050.258378
210.0789970.81720.207828
220.1631131.68730.047234
230.060760.62850.265507
240.0827730.85620.196896
25-0.103557-1.07120.143244
26-0.151715-1.56940.059759
27-0.063949-0.66150.254858
28-0.144218-1.49180.069347
290.049940.51660.303256
30-0.074363-0.76920.221729
31-0.134101-1.38720.084139
32-0.046336-0.47930.316351
330.1980852.0490.021454
34-0.053366-0.5520.291041
350.0864390.89410.186628
360.1181991.22270.112071
37-0.029721-0.30740.379555
38-0.038776-0.40110.344571
39-0.095067-0.98340.16382
40-0.02859-0.29570.384004
41-0.082794-0.85640.196838
420.0748090.77380.220368
430.0248390.25690.39886
44-0.00852-0.08810.464969
45-0.092567-0.95750.17023
460.0005880.00610.497581
47-0.041746-0.43180.33337
480.0483010.49960.309181


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ; par2 = no ;
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)
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,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')