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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 computationMon, 14 Mar 2016 16:22:44 +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/Mar/14/t1457972604s1f7lsqhmiesl2b.htm/, Retrieved Mon, 29 Apr 2024 02:18:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294011, Retrieved Mon, 29 Apr 2024 02:18:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

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] [] [2016-03-14 16:22:44] [809417a83781bff5791db815734e4daf] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
90.18
90.5
90.63
90.75
90.76
90.67
90.5
90.8
91.22
92.19
92.51
92.67
93.75
94.1
94.96
95.21
95.33
95.43
95.44
95.64
95.8
95.87
95.98
96.07
96.23
96.32
96.55
96.73
96.61
96.64
96.86
97.02
97.22
98.1
98.46
98.6
98.78
99.13
99.48
99.62
99.68
99.95
100.12
100.25
100.47
100.7
100.88
100.95
100.92
101.12
101.19
101.28
101.28
101.3
101.3
101.36
101.45
101.58
101.73
101.84
102.01
102.14
102.16
102.32
102.41
102.4
102.43
102.42
102.3
102.65
102.72
102.86

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294011&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]1 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=294011&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294011&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3283762.76690.003605
20.2649192.23220.014377
30.1979621.66810.049855
40.0620340.52270.301402
50.1327761.11880.133501
6-0.05394-0.45450.325427
7-0.049559-0.41760.338753
8-0.097309-0.81990.207498
9-0.175299-1.47710.072036
10-0.098146-0.8270.205507
110.0270280.22770.410251
120.0336560.28360.388776
13-0.001862-0.01570.493762
14-0.056963-0.480.316358
15-0.097255-0.81950.207626
16-0.109154-0.91970.18041
17-0.056777-0.47840.316914
180.0231650.19520.422901
190.0622590.52460.300746
200.0048960.04130.483604
210.1097680.92490.17907
220.0509830.42960.334397
230.0909830.76660.222921
240.2238811.88650.031662
250.1624471.36880.087688
260.0572940.48280.315372
27-0.061597-0.5190.302679
28-0.065282-0.55010.291998
29-0.011124-0.09370.462792
30-0.009101-0.07670.469543
31-0.049667-0.41850.33842
320.0002380.0020.499203
33-0.040563-0.34180.36676
34-0.072251-0.60880.272301
35-0.06125-0.51610.303693
360.0022980.01940.492303
370.0093130.07850.468837
38-0.081005-0.68260.248553
39-0.087798-0.73980.23093
40-0.080013-0.67420.251185
41-0.094657-0.79760.213883
42-0.054754-0.46140.322974
43-0.052696-0.4440.329188
44-0.047985-0.40430.343593
45-0.044755-0.37710.353609
46-0.017298-0.14580.442265
47-0.019593-0.16510.434669
48-0.004294-0.03620.485621

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.328376 & 2.7669 & 0.003605 \tabularnewline
2 & 0.264919 & 2.2322 & 0.014377 \tabularnewline
3 & 0.197962 & 1.6681 & 0.049855 \tabularnewline
4 & 0.062034 & 0.5227 & 0.301402 \tabularnewline
5 & 0.132776 & 1.1188 & 0.133501 \tabularnewline
6 & -0.05394 & -0.4545 & 0.325427 \tabularnewline
7 & -0.049559 & -0.4176 & 0.338753 \tabularnewline
8 & -0.097309 & -0.8199 & 0.207498 \tabularnewline
9 & -0.175299 & -1.4771 & 0.072036 \tabularnewline
10 & -0.098146 & -0.827 & 0.205507 \tabularnewline
11 & 0.027028 & 0.2277 & 0.410251 \tabularnewline
12 & 0.033656 & 0.2836 & 0.388776 \tabularnewline
13 & -0.001862 & -0.0157 & 0.493762 \tabularnewline
14 & -0.056963 & -0.48 & 0.316358 \tabularnewline
15 & -0.097255 & -0.8195 & 0.207626 \tabularnewline
16 & -0.109154 & -0.9197 & 0.18041 \tabularnewline
17 & -0.056777 & -0.4784 & 0.316914 \tabularnewline
18 & 0.023165 & 0.1952 & 0.422901 \tabularnewline
19 & 0.062259 & 0.5246 & 0.300746 \tabularnewline
20 & 0.004896 & 0.0413 & 0.483604 \tabularnewline
21 & 0.109768 & 0.9249 & 0.17907 \tabularnewline
22 & 0.050983 & 0.4296 & 0.334397 \tabularnewline
23 & 0.090983 & 0.7666 & 0.222921 \tabularnewline
24 & 0.223881 & 1.8865 & 0.031662 \tabularnewline
25 & 0.162447 & 1.3688 & 0.087688 \tabularnewline
26 & 0.057294 & 0.4828 & 0.315372 \tabularnewline
27 & -0.061597 & -0.519 & 0.302679 \tabularnewline
28 & -0.065282 & -0.5501 & 0.291998 \tabularnewline
29 & -0.011124 & -0.0937 & 0.462792 \tabularnewline
30 & -0.009101 & -0.0767 & 0.469543 \tabularnewline
31 & -0.049667 & -0.4185 & 0.33842 \tabularnewline
32 & 0.000238 & 0.002 & 0.499203 \tabularnewline
33 & -0.040563 & -0.3418 & 0.36676 \tabularnewline
34 & -0.072251 & -0.6088 & 0.272301 \tabularnewline
35 & -0.06125 & -0.5161 & 0.303693 \tabularnewline
36 & 0.002298 & 0.0194 & 0.492303 \tabularnewline
37 & 0.009313 & 0.0785 & 0.468837 \tabularnewline
38 & -0.081005 & -0.6826 & 0.248553 \tabularnewline
39 & -0.087798 & -0.7398 & 0.23093 \tabularnewline
40 & -0.080013 & -0.6742 & 0.251185 \tabularnewline
41 & -0.094657 & -0.7976 & 0.213883 \tabularnewline
42 & -0.054754 & -0.4614 & 0.322974 \tabularnewline
43 & -0.052696 & -0.444 & 0.329188 \tabularnewline
44 & -0.047985 & -0.4043 & 0.343593 \tabularnewline
45 & -0.044755 & -0.3771 & 0.353609 \tabularnewline
46 & -0.017298 & -0.1458 & 0.442265 \tabularnewline
47 & -0.019593 & -0.1651 & 0.434669 \tabularnewline
48 & -0.004294 & -0.0362 & 0.485621 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294011&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]0.328376[/C][C]2.7669[/C][C]0.003605[/C][/ROW]
[ROW][C]2[/C][C]0.264919[/C][C]2.2322[/C][C]0.014377[/C][/ROW]
[ROW][C]3[/C][C]0.197962[/C][C]1.6681[/C][C]0.049855[/C][/ROW]
[ROW][C]4[/C][C]0.062034[/C][C]0.5227[/C][C]0.301402[/C][/ROW]
[ROW][C]5[/C][C]0.132776[/C][C]1.1188[/C][C]0.133501[/C][/ROW]
[ROW][C]6[/C][C]-0.05394[/C][C]-0.4545[/C][C]0.325427[/C][/ROW]
[ROW][C]7[/C][C]-0.049559[/C][C]-0.4176[/C][C]0.338753[/C][/ROW]
[ROW][C]8[/C][C]-0.097309[/C][C]-0.8199[/C][C]0.207498[/C][/ROW]
[ROW][C]9[/C][C]-0.175299[/C][C]-1.4771[/C][C]0.072036[/C][/ROW]
[ROW][C]10[/C][C]-0.098146[/C][C]-0.827[/C][C]0.205507[/C][/ROW]
[ROW][C]11[/C][C]0.027028[/C][C]0.2277[/C][C]0.410251[/C][/ROW]
[ROW][C]12[/C][C]0.033656[/C][C]0.2836[/C][C]0.388776[/C][/ROW]
[ROW][C]13[/C][C]-0.001862[/C][C]-0.0157[/C][C]0.493762[/C][/ROW]
[ROW][C]14[/C][C]-0.056963[/C][C]-0.48[/C][C]0.316358[/C][/ROW]
[ROW][C]15[/C][C]-0.097255[/C][C]-0.8195[/C][C]0.207626[/C][/ROW]
[ROW][C]16[/C][C]-0.109154[/C][C]-0.9197[/C][C]0.18041[/C][/ROW]
[ROW][C]17[/C][C]-0.056777[/C][C]-0.4784[/C][C]0.316914[/C][/ROW]
[ROW][C]18[/C][C]0.023165[/C][C]0.1952[/C][C]0.422901[/C][/ROW]
[ROW][C]19[/C][C]0.062259[/C][C]0.5246[/C][C]0.300746[/C][/ROW]
[ROW][C]20[/C][C]0.004896[/C][C]0.0413[/C][C]0.483604[/C][/ROW]
[ROW][C]21[/C][C]0.109768[/C][C]0.9249[/C][C]0.17907[/C][/ROW]
[ROW][C]22[/C][C]0.050983[/C][C]0.4296[/C][C]0.334397[/C][/ROW]
[ROW][C]23[/C][C]0.090983[/C][C]0.7666[/C][C]0.222921[/C][/ROW]
[ROW][C]24[/C][C]0.223881[/C][C]1.8865[/C][C]0.031662[/C][/ROW]
[ROW][C]25[/C][C]0.162447[/C][C]1.3688[/C][C]0.087688[/C][/ROW]
[ROW][C]26[/C][C]0.057294[/C][C]0.4828[/C][C]0.315372[/C][/ROW]
[ROW][C]27[/C][C]-0.061597[/C][C]-0.519[/C][C]0.302679[/C][/ROW]
[ROW][C]28[/C][C]-0.065282[/C][C]-0.5501[/C][C]0.291998[/C][/ROW]
[ROW][C]29[/C][C]-0.011124[/C][C]-0.0937[/C][C]0.462792[/C][/ROW]
[ROW][C]30[/C][C]-0.009101[/C][C]-0.0767[/C][C]0.469543[/C][/ROW]
[ROW][C]31[/C][C]-0.049667[/C][C]-0.4185[/C][C]0.33842[/C][/ROW]
[ROW][C]32[/C][C]0.000238[/C][C]0.002[/C][C]0.499203[/C][/ROW]
[ROW][C]33[/C][C]-0.040563[/C][C]-0.3418[/C][C]0.36676[/C][/ROW]
[ROW][C]34[/C][C]-0.072251[/C][C]-0.6088[/C][C]0.272301[/C][/ROW]
[ROW][C]35[/C][C]-0.06125[/C][C]-0.5161[/C][C]0.303693[/C][/ROW]
[ROW][C]36[/C][C]0.002298[/C][C]0.0194[/C][C]0.492303[/C][/ROW]
[ROW][C]37[/C][C]0.009313[/C][C]0.0785[/C][C]0.468837[/C][/ROW]
[ROW][C]38[/C][C]-0.081005[/C][C]-0.6826[/C][C]0.248553[/C][/ROW]
[ROW][C]39[/C][C]-0.087798[/C][C]-0.7398[/C][C]0.23093[/C][/ROW]
[ROW][C]40[/C][C]-0.080013[/C][C]-0.6742[/C][C]0.251185[/C][/ROW]
[ROW][C]41[/C][C]-0.094657[/C][C]-0.7976[/C][C]0.213883[/C][/ROW]
[ROW][C]42[/C][C]-0.054754[/C][C]-0.4614[/C][C]0.322974[/C][/ROW]
[ROW][C]43[/C][C]-0.052696[/C][C]-0.444[/C][C]0.329188[/C][/ROW]
[ROW][C]44[/C][C]-0.047985[/C][C]-0.4043[/C][C]0.343593[/C][/ROW]
[ROW][C]45[/C][C]-0.044755[/C][C]-0.3771[/C][C]0.353609[/C][/ROW]
[ROW][C]46[/C][C]-0.017298[/C][C]-0.1458[/C][C]0.442265[/C][/ROW]
[ROW][C]47[/C][C]-0.019593[/C][C]-0.1651[/C][C]0.434669[/C][/ROW]
[ROW][C]48[/C][C]-0.004294[/C][C]-0.0362[/C][C]0.485621[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294011&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294011&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
10.3283762.76690.003605
20.2649192.23220.014377
30.1979621.66810.049855
40.0620340.52270.301402
50.1327761.11880.133501
6-0.05394-0.45450.325427
7-0.049559-0.41760.338753
8-0.097309-0.81990.207498
9-0.175299-1.47710.072036
10-0.098146-0.8270.205507
110.0270280.22770.410251
120.0336560.28360.388776
13-0.001862-0.01570.493762
14-0.056963-0.480.316358
15-0.097255-0.81950.207626
16-0.109154-0.91970.18041
17-0.056777-0.47840.316914
180.0231650.19520.422901
190.0622590.52460.300746
200.0048960.04130.483604
210.1097680.92490.17907
220.0509830.42960.334397
230.0909830.76660.222921
240.2238811.88650.031662
250.1624471.36880.087688
260.0572940.48280.315372
27-0.061597-0.5190.302679
28-0.065282-0.55010.291998
29-0.011124-0.09370.462792
30-0.009101-0.07670.469543
31-0.049667-0.41850.33842
320.0002380.0020.499203
33-0.040563-0.34180.36676
34-0.072251-0.60880.272301
35-0.06125-0.51610.303693
360.0022980.01940.492303
370.0093130.07850.468837
38-0.081005-0.68260.248553
39-0.087798-0.73980.23093
40-0.080013-0.67420.251185
41-0.094657-0.79760.213883
42-0.054754-0.46140.322974
43-0.052696-0.4440.329188
44-0.047985-0.40430.343593
45-0.044755-0.37710.353609
46-0.017298-0.14580.442265
47-0.019593-0.16510.434669
48-0.004294-0.03620.485621






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3283762.76690.003605
20.1760741.48360.071167
30.0791980.66730.25336
4-0.064884-0.54670.293141
50.0933430.78650.21709
6-0.143959-1.2130.114571
7-0.040335-0.33990.367479
8-0.075365-0.6350.263723
9-0.100103-0.84350.200897
10-0.001971-0.01660.493397
110.1737741.46420.07377
120.0469540.39560.346778
13-0.045643-0.38460.350842
14-0.091992-0.77510.220416
15-0.111256-0.93750.175851
16-0.109715-0.92450.179186
170.031450.2650.395888
180.1173250.98860.163109
190.1257621.05970.146438
200.0100040.08430.46653
210.1283521.08150.141564
22-0.088981-0.74980.227936
23-0.052712-0.44420.329138
240.1270551.07060.143991
250.0801620.67550.25079
26-0.09298-0.78350.217981
27-0.066933-0.5640.287271
28-0.005449-0.04590.481755
290.0071490.06020.476067
300.0306490.25830.398478
31-0.014509-0.12230.451521
320.0380920.3210.374589
330.009140.0770.469414
34-0.030209-0.25450.399906
35-0.10068-0.84830.199549
36-0.014728-0.12410.450794
370.0223320.18820.42564
38-0.030595-0.25780.398655
390.0028360.02390.490501
400.0229640.19350.423562
41-0.049451-0.41670.339084
42-0.078578-0.66210.255022
43-0.082244-0.6930.245286
44-0.052191-0.43980.33072
45-0.01767-0.14890.44103
460.0988320.83280.203883
470.0116220.09790.461131
48-0.041598-0.35050.363496

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.328376 & 2.7669 & 0.003605 \tabularnewline
2 & 0.176074 & 1.4836 & 0.071167 \tabularnewline
3 & 0.079198 & 0.6673 & 0.25336 \tabularnewline
4 & -0.064884 & -0.5467 & 0.293141 \tabularnewline
5 & 0.093343 & 0.7865 & 0.21709 \tabularnewline
6 & -0.143959 & -1.213 & 0.114571 \tabularnewline
7 & -0.040335 & -0.3399 & 0.367479 \tabularnewline
8 & -0.075365 & -0.635 & 0.263723 \tabularnewline
9 & -0.100103 & -0.8435 & 0.200897 \tabularnewline
10 & -0.001971 & -0.0166 & 0.493397 \tabularnewline
11 & 0.173774 & 1.4642 & 0.07377 \tabularnewline
12 & 0.046954 & 0.3956 & 0.346778 \tabularnewline
13 & -0.045643 & -0.3846 & 0.350842 \tabularnewline
14 & -0.091992 & -0.7751 & 0.220416 \tabularnewline
15 & -0.111256 & -0.9375 & 0.175851 \tabularnewline
16 & -0.109715 & -0.9245 & 0.179186 \tabularnewline
17 & 0.03145 & 0.265 & 0.395888 \tabularnewline
18 & 0.117325 & 0.9886 & 0.163109 \tabularnewline
19 & 0.125762 & 1.0597 & 0.146438 \tabularnewline
20 & 0.010004 & 0.0843 & 0.46653 \tabularnewline
21 & 0.128352 & 1.0815 & 0.141564 \tabularnewline
22 & -0.088981 & -0.7498 & 0.227936 \tabularnewline
23 & -0.052712 & -0.4442 & 0.329138 \tabularnewline
24 & 0.127055 & 1.0706 & 0.143991 \tabularnewline
25 & 0.080162 & 0.6755 & 0.25079 \tabularnewline
26 & -0.09298 & -0.7835 & 0.217981 \tabularnewline
27 & -0.066933 & -0.564 & 0.287271 \tabularnewline
28 & -0.005449 & -0.0459 & 0.481755 \tabularnewline
29 & 0.007149 & 0.0602 & 0.476067 \tabularnewline
30 & 0.030649 & 0.2583 & 0.398478 \tabularnewline
31 & -0.014509 & -0.1223 & 0.451521 \tabularnewline
32 & 0.038092 & 0.321 & 0.374589 \tabularnewline
33 & 0.00914 & 0.077 & 0.469414 \tabularnewline
34 & -0.030209 & -0.2545 & 0.399906 \tabularnewline
35 & -0.10068 & -0.8483 & 0.199549 \tabularnewline
36 & -0.014728 & -0.1241 & 0.450794 \tabularnewline
37 & 0.022332 & 0.1882 & 0.42564 \tabularnewline
38 & -0.030595 & -0.2578 & 0.398655 \tabularnewline
39 & 0.002836 & 0.0239 & 0.490501 \tabularnewline
40 & 0.022964 & 0.1935 & 0.423562 \tabularnewline
41 & -0.049451 & -0.4167 & 0.339084 \tabularnewline
42 & -0.078578 & -0.6621 & 0.255022 \tabularnewline
43 & -0.082244 & -0.693 & 0.245286 \tabularnewline
44 & -0.052191 & -0.4398 & 0.33072 \tabularnewline
45 & -0.01767 & -0.1489 & 0.44103 \tabularnewline
46 & 0.098832 & 0.8328 & 0.203883 \tabularnewline
47 & 0.011622 & 0.0979 & 0.461131 \tabularnewline
48 & -0.041598 & -0.3505 & 0.363496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294011&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]0.328376[/C][C]2.7669[/C][C]0.003605[/C][/ROW]
[ROW][C]2[/C][C]0.176074[/C][C]1.4836[/C][C]0.071167[/C][/ROW]
[ROW][C]3[/C][C]0.079198[/C][C]0.6673[/C][C]0.25336[/C][/ROW]
[ROW][C]4[/C][C]-0.064884[/C][C]-0.5467[/C][C]0.293141[/C][/ROW]
[ROW][C]5[/C][C]0.093343[/C][C]0.7865[/C][C]0.21709[/C][/ROW]
[ROW][C]6[/C][C]-0.143959[/C][C]-1.213[/C][C]0.114571[/C][/ROW]
[ROW][C]7[/C][C]-0.040335[/C][C]-0.3399[/C][C]0.367479[/C][/ROW]
[ROW][C]8[/C][C]-0.075365[/C][C]-0.635[/C][C]0.263723[/C][/ROW]
[ROW][C]9[/C][C]-0.100103[/C][C]-0.8435[/C][C]0.200897[/C][/ROW]
[ROW][C]10[/C][C]-0.001971[/C][C]-0.0166[/C][C]0.493397[/C][/ROW]
[ROW][C]11[/C][C]0.173774[/C][C]1.4642[/C][C]0.07377[/C][/ROW]
[ROW][C]12[/C][C]0.046954[/C][C]0.3956[/C][C]0.346778[/C][/ROW]
[ROW][C]13[/C][C]-0.045643[/C][C]-0.3846[/C][C]0.350842[/C][/ROW]
[ROW][C]14[/C][C]-0.091992[/C][C]-0.7751[/C][C]0.220416[/C][/ROW]
[ROW][C]15[/C][C]-0.111256[/C][C]-0.9375[/C][C]0.175851[/C][/ROW]
[ROW][C]16[/C][C]-0.109715[/C][C]-0.9245[/C][C]0.179186[/C][/ROW]
[ROW][C]17[/C][C]0.03145[/C][C]0.265[/C][C]0.395888[/C][/ROW]
[ROW][C]18[/C][C]0.117325[/C][C]0.9886[/C][C]0.163109[/C][/ROW]
[ROW][C]19[/C][C]0.125762[/C][C]1.0597[/C][C]0.146438[/C][/ROW]
[ROW][C]20[/C][C]0.010004[/C][C]0.0843[/C][C]0.46653[/C][/ROW]
[ROW][C]21[/C][C]0.128352[/C][C]1.0815[/C][C]0.141564[/C][/ROW]
[ROW][C]22[/C][C]-0.088981[/C][C]-0.7498[/C][C]0.227936[/C][/ROW]
[ROW][C]23[/C][C]-0.052712[/C][C]-0.4442[/C][C]0.329138[/C][/ROW]
[ROW][C]24[/C][C]0.127055[/C][C]1.0706[/C][C]0.143991[/C][/ROW]
[ROW][C]25[/C][C]0.080162[/C][C]0.6755[/C][C]0.25079[/C][/ROW]
[ROW][C]26[/C][C]-0.09298[/C][C]-0.7835[/C][C]0.217981[/C][/ROW]
[ROW][C]27[/C][C]-0.066933[/C][C]-0.564[/C][C]0.287271[/C][/ROW]
[ROW][C]28[/C][C]-0.005449[/C][C]-0.0459[/C][C]0.481755[/C][/ROW]
[ROW][C]29[/C][C]0.007149[/C][C]0.0602[/C][C]0.476067[/C][/ROW]
[ROW][C]30[/C][C]0.030649[/C][C]0.2583[/C][C]0.398478[/C][/ROW]
[ROW][C]31[/C][C]-0.014509[/C][C]-0.1223[/C][C]0.451521[/C][/ROW]
[ROW][C]32[/C][C]0.038092[/C][C]0.321[/C][C]0.374589[/C][/ROW]
[ROW][C]33[/C][C]0.00914[/C][C]0.077[/C][C]0.469414[/C][/ROW]
[ROW][C]34[/C][C]-0.030209[/C][C]-0.2545[/C][C]0.399906[/C][/ROW]
[ROW][C]35[/C][C]-0.10068[/C][C]-0.8483[/C][C]0.199549[/C][/ROW]
[ROW][C]36[/C][C]-0.014728[/C][C]-0.1241[/C][C]0.450794[/C][/ROW]
[ROW][C]37[/C][C]0.022332[/C][C]0.1882[/C][C]0.42564[/C][/ROW]
[ROW][C]38[/C][C]-0.030595[/C][C]-0.2578[/C][C]0.398655[/C][/ROW]
[ROW][C]39[/C][C]0.002836[/C][C]0.0239[/C][C]0.490501[/C][/ROW]
[ROW][C]40[/C][C]0.022964[/C][C]0.1935[/C][C]0.423562[/C][/ROW]
[ROW][C]41[/C][C]-0.049451[/C][C]-0.4167[/C][C]0.339084[/C][/ROW]
[ROW][C]42[/C][C]-0.078578[/C][C]-0.6621[/C][C]0.255022[/C][/ROW]
[ROW][C]43[/C][C]-0.082244[/C][C]-0.693[/C][C]0.245286[/C][/ROW]
[ROW][C]44[/C][C]-0.052191[/C][C]-0.4398[/C][C]0.33072[/C][/ROW]
[ROW][C]45[/C][C]-0.01767[/C][C]-0.1489[/C][C]0.44103[/C][/ROW]
[ROW][C]46[/C][C]0.098832[/C][C]0.8328[/C][C]0.203883[/C][/ROW]
[ROW][C]47[/C][C]0.011622[/C][C]0.0979[/C][C]0.461131[/C][/ROW]
[ROW][C]48[/C][C]-0.041598[/C][C]-0.3505[/C][C]0.363496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294011&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294011&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
10.3283762.76690.003605
20.1760741.48360.071167
30.0791980.66730.25336
4-0.064884-0.54670.293141
50.0933430.78650.21709
6-0.143959-1.2130.114571
7-0.040335-0.33990.367479
8-0.075365-0.6350.263723
9-0.100103-0.84350.200897
10-0.001971-0.01660.493397
110.1737741.46420.07377
120.0469540.39560.346778
13-0.045643-0.38460.350842
14-0.091992-0.77510.220416
15-0.111256-0.93750.175851
16-0.109715-0.92450.179186
170.031450.2650.395888
180.1173250.98860.163109
190.1257621.05970.146438
200.0100040.08430.46653
210.1283521.08150.141564
22-0.088981-0.74980.227936
23-0.052712-0.44420.329138
240.1270551.07060.143991
250.0801620.67550.25079
26-0.09298-0.78350.217981
27-0.066933-0.5640.287271
28-0.005449-0.04590.481755
290.0071490.06020.476067
300.0306490.25830.398478
31-0.014509-0.12230.451521
320.0380920.3210.374589
330.009140.0770.469414
34-0.030209-0.25450.399906
35-0.10068-0.84830.199549
36-0.014728-0.12410.450794
370.0223320.18820.42564
38-0.030595-0.25780.398655
390.0028360.02390.490501
400.0229640.19350.423562
41-0.049451-0.41670.339084
42-0.078578-0.66210.255022
43-0.082244-0.6930.245286
44-0.052191-0.43980.33072
45-0.01767-0.14890.44103
460.0988320.83280.203883
470.0116220.09790.461131
48-0.041598-0.35050.363496


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)
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')