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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, 16 Nov 2012 15:03:45 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/16/t1353096276wbtwujuyh3tpoeh.htm/, Retrieved Sat, 27 Apr 2024 08:54:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=190004, Retrieved Sat, 27 Apr 2024 08:54:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60

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] [autocorrelatie me...] [2012-11-16 20:03:45] [a4dec8ecbe2562b1daf91a8f6c837985] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,51
96,65
95,91
95,86
95,7
95,57
95,57
95,57
94,87
95,07
95,13
95,48
95,38
95,38
95,48
95,77
94,78
92,51
92,17
91,75
90,43
90,55
90,37
90,4
90,41
90,41
90,41
89,77
89,77
89,77
89,37
89,81
89,07
89,84
89,73
90,02
88,39
90,13
90,13
90,37
89,73
89,73
89,73
89,73
89,6
89,63
86,42
86,8
86,51
86,41
86,39
86,62
85,85
87,36
87,28
87,35
87,35
87,35
87,38
88,17
88,37
87,44
87,44
87,47
87,47
87,48
87,11
87,11
86,26
86,28
86,28
86,28

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=190004&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=190004&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190004&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
1-0.165095-1.39110.084267
20.0985760.83060.204487
3-0.049155-0.41420.339991
40.1193111.00530.159075
5-0.142028-1.19680.117692
60.1675081.41140.08124
7-0.249634-2.10350.019485
8-0.03896-0.32830.371832
9-0.184485-1.55450.062256
100.1648151.38880.084624
11-0.118507-0.99860.1607
120.0701310.59090.27822
13-0.238345-2.00830.024207
140.0618220.52090.302022
15-0.032069-0.27020.393888
160.2507892.11320.01905
17-0.190749-1.60730.056215
180.0233020.19630.422449
190.086160.7260.235114
200.0223910.18870.425443
21-0.138195-1.16450.124069
220.1387761.16930.123087
23-0.061912-0.52170.301758
24-0.01318-0.11110.455941
25-0.020356-0.17150.43215
260.1335021.12490.132209
27-0.011985-0.1010.459924
280.0793720.66880.252895
290.1430441.20530.116043
300.0693860.58470.280316
31-0.103657-0.87340.192686
320.0524770.44220.329852
33-0.108327-0.91280.182223
340.016250.13690.44574
35-0.062712-0.52840.299428
36-0.116414-0.98090.16498
37-0.120789-1.01780.156117
380.0662590.55830.289195
39-0.0476-0.40110.344782
40-0.041025-0.34570.365302
410.0106920.09010.464235
42-0.044462-0.37460.354521
43-0.063415-0.53430.297387
440.1341261.13020.131104
450.0431630.36370.358583
46-0.008185-0.0690.472604
47-0.012616-0.10630.45782
480.0284030.23930.40577

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.165095 & -1.3911 & 0.084267 \tabularnewline
2 & 0.098576 & 0.8306 & 0.204487 \tabularnewline
3 & -0.049155 & -0.4142 & 0.339991 \tabularnewline
4 & 0.119311 & 1.0053 & 0.159075 \tabularnewline
5 & -0.142028 & -1.1968 & 0.117692 \tabularnewline
6 & 0.167508 & 1.4114 & 0.08124 \tabularnewline
7 & -0.249634 & -2.1035 & 0.019485 \tabularnewline
8 & -0.03896 & -0.3283 & 0.371832 \tabularnewline
9 & -0.184485 & -1.5545 & 0.062256 \tabularnewline
10 & 0.164815 & 1.3888 & 0.084624 \tabularnewline
11 & -0.118507 & -0.9986 & 0.1607 \tabularnewline
12 & 0.070131 & 0.5909 & 0.27822 \tabularnewline
13 & -0.238345 & -2.0083 & 0.024207 \tabularnewline
14 & 0.061822 & 0.5209 & 0.302022 \tabularnewline
15 & -0.032069 & -0.2702 & 0.393888 \tabularnewline
16 & 0.250789 & 2.1132 & 0.01905 \tabularnewline
17 & -0.190749 & -1.6073 & 0.056215 \tabularnewline
18 & 0.023302 & 0.1963 & 0.422449 \tabularnewline
19 & 0.08616 & 0.726 & 0.235114 \tabularnewline
20 & 0.022391 & 0.1887 & 0.425443 \tabularnewline
21 & -0.138195 & -1.1645 & 0.124069 \tabularnewline
22 & 0.138776 & 1.1693 & 0.123087 \tabularnewline
23 & -0.061912 & -0.5217 & 0.301758 \tabularnewline
24 & -0.01318 & -0.1111 & 0.455941 \tabularnewline
25 & -0.020356 & -0.1715 & 0.43215 \tabularnewline
26 & 0.133502 & 1.1249 & 0.132209 \tabularnewline
27 & -0.011985 & -0.101 & 0.459924 \tabularnewline
28 & 0.079372 & 0.6688 & 0.252895 \tabularnewline
29 & 0.143044 & 1.2053 & 0.116043 \tabularnewline
30 & 0.069386 & 0.5847 & 0.280316 \tabularnewline
31 & -0.103657 & -0.8734 & 0.192686 \tabularnewline
32 & 0.052477 & 0.4422 & 0.329852 \tabularnewline
33 & -0.108327 & -0.9128 & 0.182223 \tabularnewline
34 & 0.01625 & 0.1369 & 0.44574 \tabularnewline
35 & -0.062712 & -0.5284 & 0.299428 \tabularnewline
36 & -0.116414 & -0.9809 & 0.16498 \tabularnewline
37 & -0.120789 & -1.0178 & 0.156117 \tabularnewline
38 & 0.066259 & 0.5583 & 0.289195 \tabularnewline
39 & -0.0476 & -0.4011 & 0.344782 \tabularnewline
40 & -0.041025 & -0.3457 & 0.365302 \tabularnewline
41 & 0.010692 & 0.0901 & 0.464235 \tabularnewline
42 & -0.044462 & -0.3746 & 0.354521 \tabularnewline
43 & -0.063415 & -0.5343 & 0.297387 \tabularnewline
44 & 0.134126 & 1.1302 & 0.131104 \tabularnewline
45 & 0.043163 & 0.3637 & 0.358583 \tabularnewline
46 & -0.008185 & -0.069 & 0.472604 \tabularnewline
47 & -0.012616 & -0.1063 & 0.45782 \tabularnewline
48 & 0.028403 & 0.2393 & 0.40577 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190004&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]-0.165095[/C][C]-1.3911[/C][C]0.084267[/C][/ROW]
[ROW][C]2[/C][C]0.098576[/C][C]0.8306[/C][C]0.204487[/C][/ROW]
[ROW][C]3[/C][C]-0.049155[/C][C]-0.4142[/C][C]0.339991[/C][/ROW]
[ROW][C]4[/C][C]0.119311[/C][C]1.0053[/C][C]0.159075[/C][/ROW]
[ROW][C]5[/C][C]-0.142028[/C][C]-1.1968[/C][C]0.117692[/C][/ROW]
[ROW][C]6[/C][C]0.167508[/C][C]1.4114[/C][C]0.08124[/C][/ROW]
[ROW][C]7[/C][C]-0.249634[/C][C]-2.1035[/C][C]0.019485[/C][/ROW]
[ROW][C]8[/C][C]-0.03896[/C][C]-0.3283[/C][C]0.371832[/C][/ROW]
[ROW][C]9[/C][C]-0.184485[/C][C]-1.5545[/C][C]0.062256[/C][/ROW]
[ROW][C]10[/C][C]0.164815[/C][C]1.3888[/C][C]0.084624[/C][/ROW]
[ROW][C]11[/C][C]-0.118507[/C][C]-0.9986[/C][C]0.1607[/C][/ROW]
[ROW][C]12[/C][C]0.070131[/C][C]0.5909[/C][C]0.27822[/C][/ROW]
[ROW][C]13[/C][C]-0.238345[/C][C]-2.0083[/C][C]0.024207[/C][/ROW]
[ROW][C]14[/C][C]0.061822[/C][C]0.5209[/C][C]0.302022[/C][/ROW]
[ROW][C]15[/C][C]-0.032069[/C][C]-0.2702[/C][C]0.393888[/C][/ROW]
[ROW][C]16[/C][C]0.250789[/C][C]2.1132[/C][C]0.01905[/C][/ROW]
[ROW][C]17[/C][C]-0.190749[/C][C]-1.6073[/C][C]0.056215[/C][/ROW]
[ROW][C]18[/C][C]0.023302[/C][C]0.1963[/C][C]0.422449[/C][/ROW]
[ROW][C]19[/C][C]0.08616[/C][C]0.726[/C][C]0.235114[/C][/ROW]
[ROW][C]20[/C][C]0.022391[/C][C]0.1887[/C][C]0.425443[/C][/ROW]
[ROW][C]21[/C][C]-0.138195[/C][C]-1.1645[/C][C]0.124069[/C][/ROW]
[ROW][C]22[/C][C]0.138776[/C][C]1.1693[/C][C]0.123087[/C][/ROW]
[ROW][C]23[/C][C]-0.061912[/C][C]-0.5217[/C][C]0.301758[/C][/ROW]
[ROW][C]24[/C][C]-0.01318[/C][C]-0.1111[/C][C]0.455941[/C][/ROW]
[ROW][C]25[/C][C]-0.020356[/C][C]-0.1715[/C][C]0.43215[/C][/ROW]
[ROW][C]26[/C][C]0.133502[/C][C]1.1249[/C][C]0.132209[/C][/ROW]
[ROW][C]27[/C][C]-0.011985[/C][C]-0.101[/C][C]0.459924[/C][/ROW]
[ROW][C]28[/C][C]0.079372[/C][C]0.6688[/C][C]0.252895[/C][/ROW]
[ROW][C]29[/C][C]0.143044[/C][C]1.2053[/C][C]0.116043[/C][/ROW]
[ROW][C]30[/C][C]0.069386[/C][C]0.5847[/C][C]0.280316[/C][/ROW]
[ROW][C]31[/C][C]-0.103657[/C][C]-0.8734[/C][C]0.192686[/C][/ROW]
[ROW][C]32[/C][C]0.052477[/C][C]0.4422[/C][C]0.329852[/C][/ROW]
[ROW][C]33[/C][C]-0.108327[/C][C]-0.9128[/C][C]0.182223[/C][/ROW]
[ROW][C]34[/C][C]0.01625[/C][C]0.1369[/C][C]0.44574[/C][/ROW]
[ROW][C]35[/C][C]-0.062712[/C][C]-0.5284[/C][C]0.299428[/C][/ROW]
[ROW][C]36[/C][C]-0.116414[/C][C]-0.9809[/C][C]0.16498[/C][/ROW]
[ROW][C]37[/C][C]-0.120789[/C][C]-1.0178[/C][C]0.156117[/C][/ROW]
[ROW][C]38[/C][C]0.066259[/C][C]0.5583[/C][C]0.289195[/C][/ROW]
[ROW][C]39[/C][C]-0.0476[/C][C]-0.4011[/C][C]0.344782[/C][/ROW]
[ROW][C]40[/C][C]-0.041025[/C][C]-0.3457[/C][C]0.365302[/C][/ROW]
[ROW][C]41[/C][C]0.010692[/C][C]0.0901[/C][C]0.464235[/C][/ROW]
[ROW][C]42[/C][C]-0.044462[/C][C]-0.3746[/C][C]0.354521[/C][/ROW]
[ROW][C]43[/C][C]-0.063415[/C][C]-0.5343[/C][C]0.297387[/C][/ROW]
[ROW][C]44[/C][C]0.134126[/C][C]1.1302[/C][C]0.131104[/C][/ROW]
[ROW][C]45[/C][C]0.043163[/C][C]0.3637[/C][C]0.358583[/C][/ROW]
[ROW][C]46[/C][C]-0.008185[/C][C]-0.069[/C][C]0.472604[/C][/ROW]
[ROW][C]47[/C][C]-0.012616[/C][C]-0.1063[/C][C]0.45782[/C][/ROW]
[ROW][C]48[/C][C]0.028403[/C][C]0.2393[/C][C]0.40577[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190004&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190004&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
1-0.165095-1.39110.084267
20.0985760.83060.204487
3-0.049155-0.41420.339991
40.1193111.00530.159075
5-0.142028-1.19680.117692
60.1675081.41140.08124
7-0.249634-2.10350.019485
8-0.03896-0.32830.371832
9-0.184485-1.55450.062256
100.1648151.38880.084624
11-0.118507-0.99860.1607
120.0701310.59090.27822
13-0.238345-2.00830.024207
140.0618220.52090.302022
15-0.032069-0.27020.393888
160.2507892.11320.01905
17-0.190749-1.60730.056215
180.0233020.19630.422449
190.086160.7260.235114
200.0223910.18870.425443
21-0.138195-1.16450.124069
220.1387761.16930.123087
23-0.061912-0.52170.301758
24-0.01318-0.11110.455941
25-0.020356-0.17150.43215
260.1335021.12490.132209
27-0.011985-0.1010.459924
280.0793720.66880.252895
290.1430441.20530.116043
300.0693860.58470.280316
31-0.103657-0.87340.192686
320.0524770.44220.329852
33-0.108327-0.91280.182223
340.016250.13690.44574
35-0.062712-0.52840.299428
36-0.116414-0.98090.16498
37-0.120789-1.01780.156117
380.0662590.55830.289195
39-0.0476-0.40110.344782
40-0.041025-0.34570.365302
410.0106920.09010.464235
42-0.044462-0.37460.354521
43-0.063415-0.53430.297387
440.1341261.13020.131104
450.0431630.36370.358583
46-0.008185-0.0690.472604
47-0.012616-0.10630.45782
480.0284030.23930.40577






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.165095-1.39110.084267
20.0733180.61780.269345
3-0.022707-0.19130.424405
40.1046920.88210.190336
5-0.107926-0.90940.183107
60.1206271.01640.15644
7-0.202443-1.70580.046207
8-0.138365-1.16590.123781
9-0.17461-1.47130.072815
100.100460.84650.200061
11-0.001104-0.00930.496301
120.003270.02760.489047
13-0.193679-1.6320.053557
14-0.082697-0.69680.244096
150.0032050.0270.489265
160.1727561.45570.074946
17-0.092219-0.7770.219855
18-0.116752-0.98380.164284
190.1761741.48450.071055
20-0.070501-0.59410.277183
21-0.188204-1.58580.058611
22-0.035747-0.30120.382066
230.1528181.28770.101022
240.0190170.16020.436573
25-0.081956-0.69060.246043
260.0186380.1570.437827
270.1478791.2460.108421
280.0931780.78510.217495
290.2112111.77970.039703
300.0622470.52450.300782
31-0.134795-1.13580.129929
320.0129160.10880.456821
33-0.045709-0.38520.350637
34-0.029024-0.24460.403752
35-0.077748-0.65510.257254
360.0341470.28770.387197
370.0175250.14770.441511
38-0.067462-0.56840.285765
39-0.041844-0.35260.362721
400.0004630.00390.49845
410.0461060.38850.349406
42-0.078447-0.6610.255374
43-0.090534-0.76290.224039
440.0088870.07490.470259
45-0.03504-0.29530.384331
46-0.033574-0.28290.389038
470.0483750.40760.342392
48-0.117623-0.99110.162498

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.165095 & -1.3911 & 0.084267 \tabularnewline
2 & 0.073318 & 0.6178 & 0.269345 \tabularnewline
3 & -0.022707 & -0.1913 & 0.424405 \tabularnewline
4 & 0.104692 & 0.8821 & 0.190336 \tabularnewline
5 & -0.107926 & -0.9094 & 0.183107 \tabularnewline
6 & 0.120627 & 1.0164 & 0.15644 \tabularnewline
7 & -0.202443 & -1.7058 & 0.046207 \tabularnewline
8 & -0.138365 & -1.1659 & 0.123781 \tabularnewline
9 & -0.17461 & -1.4713 & 0.072815 \tabularnewline
10 & 0.10046 & 0.8465 & 0.200061 \tabularnewline
11 & -0.001104 & -0.0093 & 0.496301 \tabularnewline
12 & 0.00327 & 0.0276 & 0.489047 \tabularnewline
13 & -0.193679 & -1.632 & 0.053557 \tabularnewline
14 & -0.082697 & -0.6968 & 0.244096 \tabularnewline
15 & 0.003205 & 0.027 & 0.489265 \tabularnewline
16 & 0.172756 & 1.4557 & 0.074946 \tabularnewline
17 & -0.092219 & -0.777 & 0.219855 \tabularnewline
18 & -0.116752 & -0.9838 & 0.164284 \tabularnewline
19 & 0.176174 & 1.4845 & 0.071055 \tabularnewline
20 & -0.070501 & -0.5941 & 0.277183 \tabularnewline
21 & -0.188204 & -1.5858 & 0.058611 \tabularnewline
22 & -0.035747 & -0.3012 & 0.382066 \tabularnewline
23 & 0.152818 & 1.2877 & 0.101022 \tabularnewline
24 & 0.019017 & 0.1602 & 0.436573 \tabularnewline
25 & -0.081956 & -0.6906 & 0.246043 \tabularnewline
26 & 0.018638 & 0.157 & 0.437827 \tabularnewline
27 & 0.147879 & 1.246 & 0.108421 \tabularnewline
28 & 0.093178 & 0.7851 & 0.217495 \tabularnewline
29 & 0.211211 & 1.7797 & 0.039703 \tabularnewline
30 & 0.062247 & 0.5245 & 0.300782 \tabularnewline
31 & -0.134795 & -1.1358 & 0.129929 \tabularnewline
32 & 0.012916 & 0.1088 & 0.456821 \tabularnewline
33 & -0.045709 & -0.3852 & 0.350637 \tabularnewline
34 & -0.029024 & -0.2446 & 0.403752 \tabularnewline
35 & -0.077748 & -0.6551 & 0.257254 \tabularnewline
36 & 0.034147 & 0.2877 & 0.387197 \tabularnewline
37 & 0.017525 & 0.1477 & 0.441511 \tabularnewline
38 & -0.067462 & -0.5684 & 0.285765 \tabularnewline
39 & -0.041844 & -0.3526 & 0.362721 \tabularnewline
40 & 0.000463 & 0.0039 & 0.49845 \tabularnewline
41 & 0.046106 & 0.3885 & 0.349406 \tabularnewline
42 & -0.078447 & -0.661 & 0.255374 \tabularnewline
43 & -0.090534 & -0.7629 & 0.224039 \tabularnewline
44 & 0.008887 & 0.0749 & 0.470259 \tabularnewline
45 & -0.03504 & -0.2953 & 0.384331 \tabularnewline
46 & -0.033574 & -0.2829 & 0.389038 \tabularnewline
47 & 0.048375 & 0.4076 & 0.342392 \tabularnewline
48 & -0.117623 & -0.9911 & 0.162498 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190004&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]-0.165095[/C][C]-1.3911[/C][C]0.084267[/C][/ROW]
[ROW][C]2[/C][C]0.073318[/C][C]0.6178[/C][C]0.269345[/C][/ROW]
[ROW][C]3[/C][C]-0.022707[/C][C]-0.1913[/C][C]0.424405[/C][/ROW]
[ROW][C]4[/C][C]0.104692[/C][C]0.8821[/C][C]0.190336[/C][/ROW]
[ROW][C]5[/C][C]-0.107926[/C][C]-0.9094[/C][C]0.183107[/C][/ROW]
[ROW][C]6[/C][C]0.120627[/C][C]1.0164[/C][C]0.15644[/C][/ROW]
[ROW][C]7[/C][C]-0.202443[/C][C]-1.7058[/C][C]0.046207[/C][/ROW]
[ROW][C]8[/C][C]-0.138365[/C][C]-1.1659[/C][C]0.123781[/C][/ROW]
[ROW][C]9[/C][C]-0.17461[/C][C]-1.4713[/C][C]0.072815[/C][/ROW]
[ROW][C]10[/C][C]0.10046[/C][C]0.8465[/C][C]0.200061[/C][/ROW]
[ROW][C]11[/C][C]-0.001104[/C][C]-0.0093[/C][C]0.496301[/C][/ROW]
[ROW][C]12[/C][C]0.00327[/C][C]0.0276[/C][C]0.489047[/C][/ROW]
[ROW][C]13[/C][C]-0.193679[/C][C]-1.632[/C][C]0.053557[/C][/ROW]
[ROW][C]14[/C][C]-0.082697[/C][C]-0.6968[/C][C]0.244096[/C][/ROW]
[ROW][C]15[/C][C]0.003205[/C][C]0.027[/C][C]0.489265[/C][/ROW]
[ROW][C]16[/C][C]0.172756[/C][C]1.4557[/C][C]0.074946[/C][/ROW]
[ROW][C]17[/C][C]-0.092219[/C][C]-0.777[/C][C]0.219855[/C][/ROW]
[ROW][C]18[/C][C]-0.116752[/C][C]-0.9838[/C][C]0.164284[/C][/ROW]
[ROW][C]19[/C][C]0.176174[/C][C]1.4845[/C][C]0.071055[/C][/ROW]
[ROW][C]20[/C][C]-0.070501[/C][C]-0.5941[/C][C]0.277183[/C][/ROW]
[ROW][C]21[/C][C]-0.188204[/C][C]-1.5858[/C][C]0.058611[/C][/ROW]
[ROW][C]22[/C][C]-0.035747[/C][C]-0.3012[/C][C]0.382066[/C][/ROW]
[ROW][C]23[/C][C]0.152818[/C][C]1.2877[/C][C]0.101022[/C][/ROW]
[ROW][C]24[/C][C]0.019017[/C][C]0.1602[/C][C]0.436573[/C][/ROW]
[ROW][C]25[/C][C]-0.081956[/C][C]-0.6906[/C][C]0.246043[/C][/ROW]
[ROW][C]26[/C][C]0.018638[/C][C]0.157[/C][C]0.437827[/C][/ROW]
[ROW][C]27[/C][C]0.147879[/C][C]1.246[/C][C]0.108421[/C][/ROW]
[ROW][C]28[/C][C]0.093178[/C][C]0.7851[/C][C]0.217495[/C][/ROW]
[ROW][C]29[/C][C]0.211211[/C][C]1.7797[/C][C]0.039703[/C][/ROW]
[ROW][C]30[/C][C]0.062247[/C][C]0.5245[/C][C]0.300782[/C][/ROW]
[ROW][C]31[/C][C]-0.134795[/C][C]-1.1358[/C][C]0.129929[/C][/ROW]
[ROW][C]32[/C][C]0.012916[/C][C]0.1088[/C][C]0.456821[/C][/ROW]
[ROW][C]33[/C][C]-0.045709[/C][C]-0.3852[/C][C]0.350637[/C][/ROW]
[ROW][C]34[/C][C]-0.029024[/C][C]-0.2446[/C][C]0.403752[/C][/ROW]
[ROW][C]35[/C][C]-0.077748[/C][C]-0.6551[/C][C]0.257254[/C][/ROW]
[ROW][C]36[/C][C]0.034147[/C][C]0.2877[/C][C]0.387197[/C][/ROW]
[ROW][C]37[/C][C]0.017525[/C][C]0.1477[/C][C]0.441511[/C][/ROW]
[ROW][C]38[/C][C]-0.067462[/C][C]-0.5684[/C][C]0.285765[/C][/ROW]
[ROW][C]39[/C][C]-0.041844[/C][C]-0.3526[/C][C]0.362721[/C][/ROW]
[ROW][C]40[/C][C]0.000463[/C][C]0.0039[/C][C]0.49845[/C][/ROW]
[ROW][C]41[/C][C]0.046106[/C][C]0.3885[/C][C]0.349406[/C][/ROW]
[ROW][C]42[/C][C]-0.078447[/C][C]-0.661[/C][C]0.255374[/C][/ROW]
[ROW][C]43[/C][C]-0.090534[/C][C]-0.7629[/C][C]0.224039[/C][/ROW]
[ROW][C]44[/C][C]0.008887[/C][C]0.0749[/C][C]0.470259[/C][/ROW]
[ROW][C]45[/C][C]-0.03504[/C][C]-0.2953[/C][C]0.384331[/C][/ROW]
[ROW][C]46[/C][C]-0.033574[/C][C]-0.2829[/C][C]0.389038[/C][/ROW]
[ROW][C]47[/C][C]0.048375[/C][C]0.4076[/C][C]0.342392[/C][/ROW]
[ROW][C]48[/C][C]-0.117623[/C][C]-0.9911[/C][C]0.162498[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190004&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190004&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
1-0.165095-1.39110.084267
20.0733180.61780.269345
3-0.022707-0.19130.424405
40.1046920.88210.190336
5-0.107926-0.90940.183107
60.1206271.01640.15644
7-0.202443-1.70580.046207
8-0.138365-1.16590.123781
9-0.17461-1.47130.072815
100.100460.84650.200061
11-0.001104-0.00930.496301
120.003270.02760.489047
13-0.193679-1.6320.053557
14-0.082697-0.69680.244096
150.0032050.0270.489265
160.1727561.45570.074946
17-0.092219-0.7770.219855
18-0.116752-0.98380.164284
190.1761741.48450.071055
20-0.070501-0.59410.277183
21-0.188204-1.58580.058611
22-0.035747-0.30120.382066
230.1528181.28770.101022
240.0190170.16020.436573
25-0.081956-0.69060.246043
260.0186380.1570.437827
270.1478791.2460.108421
280.0931780.78510.217495
290.2112111.77970.039703
300.0622470.52450.300782
31-0.134795-1.13580.129929
320.0129160.10880.456821
33-0.045709-0.38520.350637
34-0.029024-0.24460.403752
35-0.077748-0.65510.257254
360.0341470.28770.387197
370.0175250.14770.441511
38-0.067462-0.56840.285765
39-0.041844-0.35260.362721
400.0004630.00390.49845
410.0461060.38850.349406
42-0.078447-0.6610.255374
43-0.090534-0.76290.224039
440.0088870.07490.470259
45-0.03504-0.29530.384331
46-0.033574-0.28290.389038
470.0483750.40760.342392
48-0.117623-0.99110.162498


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')