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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, 23 Oct 2015 18:47:33 +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/2015/Oct/23/t14456224757w4h96a1io6huq7.htm/, Retrieved Tue, 14 May 2024 07:42:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=282937, Retrieved Tue, 14 May 2024 07:42:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81

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] [] [2015-10-23 17:29:21] [b1987693a2b63654c6d4ca246f63ea73]
-   P   [(Partial) Autocorrelation Function] [] [2015-10-23 17:40:17] [b1987693a2b63654c6d4ca246f63ea73]
-    D    [(Partial) Autocorrelation Function] [] [2015-10-23 17:45:59] [b1987693a2b63654c6d4ca246f63ea73]
- R PD        [(Partial) Autocorrelation Function] [] [2015-10-23 17:47:33] [07f175c9375843c217f66b4a3796ae0c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
85.95
86.41
86.42
86.81
86.71
86.7
87.07
86.96
87.04
87.5
88.32
88.56
88.92
89.56
90.21
90.42
91.23
91.73
92.21
91.65
91.8
91.63
91.09
90.89
90.98
91.29
90.77
90.96
90.89
90.72
90.66
90.94
90.7
90.74
90.98
91.13
91.54
91.93
92.27
92.59
92.96
92.95
92.99
93.05
93.34
93.47
93.59
93.96
94.49
95.04
95.52
95.75
96.07
96.37
96.48
96.4
96.66
96.81
97.19
97.23
97.94
98.52
98.73
98.8
98.77
98.54
98.72
99.15
99.32
99.5
99.39
99.4
99.37
99.69
99.83
99.79
99.94
100.11
100.21
100.15
100.21
100.13
100.2
100.36
100.5
100.66
100.72
100.41
100.3
100.38
100.55
100.17
100.09
100.22
100.09
99.98

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282937&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282937&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282937&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'George Udny Yule' @ yule.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3324493.24030.000823
20.241872.35750.010226
30.2324722.26590.012865
40.2418692.35740.010226
5-0.062555-0.60970.271754
6-0.012215-0.11910.452742
70.1480091.44260.07621
8-0.020366-0.19850.421539
9-0.063341-0.61740.269234
10-0.029777-0.29020.386137
110.0522820.50960.305764
12-0.09105-0.88750.188539
13-0.00367-0.03580.485772
14-0.085002-0.82850.204733
15-0.030042-0.29280.385151
16-0.156104-1.52150.065726
17-0.060237-0.58710.27926
18-0.164527-1.60360.05606
19-0.088233-0.860.19598
20-0.079152-0.77150.221169
21-0.040901-0.39870.345521
220.0520740.50760.30647
230.0238310.23230.40841
240.07960.77580.219885
25-0.057119-0.55670.289512
26-0.076603-0.74660.228564
27-0.103487-1.00870.157849
28-0.127925-1.24690.107758
29-0.10181-0.99230.161782
30-0.07689-0.74940.227723
31-0.125616-1.22430.111924
32-0.057272-0.55820.289004
330.0383910.37420.35455
34-0.048422-0.4720.319021
350.0012280.0120.495238
360.1074521.04730.148807
370.0239590.23350.407928
38-0.036254-0.35340.362301
39-0.05376-0.5240.300752
400.0132290.12890.44884
41-0.111202-1.08390.140583
42-0.00837-0.08160.467574
430.0236520.23050.409088
440.055320.53920.295506
45-0.030805-0.30030.382321
460.0751050.7320.232974
470.0215940.21050.416873
480.0341220.33260.37009

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.332449 & 3.2403 & 0.000823 \tabularnewline
2 & 0.24187 & 2.3575 & 0.010226 \tabularnewline
3 & 0.232472 & 2.2659 & 0.012865 \tabularnewline
4 & 0.241869 & 2.3574 & 0.010226 \tabularnewline
5 & -0.062555 & -0.6097 & 0.271754 \tabularnewline
6 & -0.012215 & -0.1191 & 0.452742 \tabularnewline
7 & 0.148009 & 1.4426 & 0.07621 \tabularnewline
8 & -0.020366 & -0.1985 & 0.421539 \tabularnewline
9 & -0.063341 & -0.6174 & 0.269234 \tabularnewline
10 & -0.029777 & -0.2902 & 0.386137 \tabularnewline
11 & 0.052282 & 0.5096 & 0.305764 \tabularnewline
12 & -0.09105 & -0.8875 & 0.188539 \tabularnewline
13 & -0.00367 & -0.0358 & 0.485772 \tabularnewline
14 & -0.085002 & -0.8285 & 0.204733 \tabularnewline
15 & -0.030042 & -0.2928 & 0.385151 \tabularnewline
16 & -0.156104 & -1.5215 & 0.065726 \tabularnewline
17 & -0.060237 & -0.5871 & 0.27926 \tabularnewline
18 & -0.164527 & -1.6036 & 0.05606 \tabularnewline
19 & -0.088233 & -0.86 & 0.19598 \tabularnewline
20 & -0.079152 & -0.7715 & 0.221169 \tabularnewline
21 & -0.040901 & -0.3987 & 0.345521 \tabularnewline
22 & 0.052074 & 0.5076 & 0.30647 \tabularnewline
23 & 0.023831 & 0.2323 & 0.40841 \tabularnewline
24 & 0.0796 & 0.7758 & 0.219885 \tabularnewline
25 & -0.057119 & -0.5567 & 0.289512 \tabularnewline
26 & -0.076603 & -0.7466 & 0.228564 \tabularnewline
27 & -0.103487 & -1.0087 & 0.157849 \tabularnewline
28 & -0.127925 & -1.2469 & 0.107758 \tabularnewline
29 & -0.10181 & -0.9923 & 0.161782 \tabularnewline
30 & -0.07689 & -0.7494 & 0.227723 \tabularnewline
31 & -0.125616 & -1.2243 & 0.111924 \tabularnewline
32 & -0.057272 & -0.5582 & 0.289004 \tabularnewline
33 & 0.038391 & 0.3742 & 0.35455 \tabularnewline
34 & -0.048422 & -0.472 & 0.319021 \tabularnewline
35 & 0.001228 & 0.012 & 0.495238 \tabularnewline
36 & 0.107452 & 1.0473 & 0.148807 \tabularnewline
37 & 0.023959 & 0.2335 & 0.407928 \tabularnewline
38 & -0.036254 & -0.3534 & 0.362301 \tabularnewline
39 & -0.05376 & -0.524 & 0.300752 \tabularnewline
40 & 0.013229 & 0.1289 & 0.44884 \tabularnewline
41 & -0.111202 & -1.0839 & 0.140583 \tabularnewline
42 & -0.00837 & -0.0816 & 0.467574 \tabularnewline
43 & 0.023652 & 0.2305 & 0.409088 \tabularnewline
44 & 0.05532 & 0.5392 & 0.295506 \tabularnewline
45 & -0.030805 & -0.3003 & 0.382321 \tabularnewline
46 & 0.075105 & 0.732 & 0.232974 \tabularnewline
47 & 0.021594 & 0.2105 & 0.416873 \tabularnewline
48 & 0.034122 & 0.3326 & 0.37009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282937&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]0.332449[/C][C]3.2403[/C][C]0.000823[/C][/ROW]
[ROW][C]2[/C][C]0.24187[/C][C]2.3575[/C][C]0.010226[/C][/ROW]
[ROW][C]3[/C][C]0.232472[/C][C]2.2659[/C][C]0.012865[/C][/ROW]
[ROW][C]4[/C][C]0.241869[/C][C]2.3574[/C][C]0.010226[/C][/ROW]
[ROW][C]5[/C][C]-0.062555[/C][C]-0.6097[/C][C]0.271754[/C][/ROW]
[ROW][C]6[/C][C]-0.012215[/C][C]-0.1191[/C][C]0.452742[/C][/ROW]
[ROW][C]7[/C][C]0.148009[/C][C]1.4426[/C][C]0.07621[/C][/ROW]
[ROW][C]8[/C][C]-0.020366[/C][C]-0.1985[/C][C]0.421539[/C][/ROW]
[ROW][C]9[/C][C]-0.063341[/C][C]-0.6174[/C][C]0.269234[/C][/ROW]
[ROW][C]10[/C][C]-0.029777[/C][C]-0.2902[/C][C]0.386137[/C][/ROW]
[ROW][C]11[/C][C]0.052282[/C][C]0.5096[/C][C]0.305764[/C][/ROW]
[ROW][C]12[/C][C]-0.09105[/C][C]-0.8875[/C][C]0.188539[/C][/ROW]
[ROW][C]13[/C][C]-0.00367[/C][C]-0.0358[/C][C]0.485772[/C][/ROW]
[ROW][C]14[/C][C]-0.085002[/C][C]-0.8285[/C][C]0.204733[/C][/ROW]
[ROW][C]15[/C][C]-0.030042[/C][C]-0.2928[/C][C]0.385151[/C][/ROW]
[ROW][C]16[/C][C]-0.156104[/C][C]-1.5215[/C][C]0.065726[/C][/ROW]
[ROW][C]17[/C][C]-0.060237[/C][C]-0.5871[/C][C]0.27926[/C][/ROW]
[ROW][C]18[/C][C]-0.164527[/C][C]-1.6036[/C][C]0.05606[/C][/ROW]
[ROW][C]19[/C][C]-0.088233[/C][C]-0.86[/C][C]0.19598[/C][/ROW]
[ROW][C]20[/C][C]-0.079152[/C][C]-0.7715[/C][C]0.221169[/C][/ROW]
[ROW][C]21[/C][C]-0.040901[/C][C]-0.3987[/C][C]0.345521[/C][/ROW]
[ROW][C]22[/C][C]0.052074[/C][C]0.5076[/C][C]0.30647[/C][/ROW]
[ROW][C]23[/C][C]0.023831[/C][C]0.2323[/C][C]0.40841[/C][/ROW]
[ROW][C]24[/C][C]0.0796[/C][C]0.7758[/C][C]0.219885[/C][/ROW]
[ROW][C]25[/C][C]-0.057119[/C][C]-0.5567[/C][C]0.289512[/C][/ROW]
[ROW][C]26[/C][C]-0.076603[/C][C]-0.7466[/C][C]0.228564[/C][/ROW]
[ROW][C]27[/C][C]-0.103487[/C][C]-1.0087[/C][C]0.157849[/C][/ROW]
[ROW][C]28[/C][C]-0.127925[/C][C]-1.2469[/C][C]0.107758[/C][/ROW]
[ROW][C]29[/C][C]-0.10181[/C][C]-0.9923[/C][C]0.161782[/C][/ROW]
[ROW][C]30[/C][C]-0.07689[/C][C]-0.7494[/C][C]0.227723[/C][/ROW]
[ROW][C]31[/C][C]-0.125616[/C][C]-1.2243[/C][C]0.111924[/C][/ROW]
[ROW][C]32[/C][C]-0.057272[/C][C]-0.5582[/C][C]0.289004[/C][/ROW]
[ROW][C]33[/C][C]0.038391[/C][C]0.3742[/C][C]0.35455[/C][/ROW]
[ROW][C]34[/C][C]-0.048422[/C][C]-0.472[/C][C]0.319021[/C][/ROW]
[ROW][C]35[/C][C]0.001228[/C][C]0.012[/C][C]0.495238[/C][/ROW]
[ROW][C]36[/C][C]0.107452[/C][C]1.0473[/C][C]0.148807[/C][/ROW]
[ROW][C]37[/C][C]0.023959[/C][C]0.2335[/C][C]0.407928[/C][/ROW]
[ROW][C]38[/C][C]-0.036254[/C][C]-0.3534[/C][C]0.362301[/C][/ROW]
[ROW][C]39[/C][C]-0.05376[/C][C]-0.524[/C][C]0.300752[/C][/ROW]
[ROW][C]40[/C][C]0.013229[/C][C]0.1289[/C][C]0.44884[/C][/ROW]
[ROW][C]41[/C][C]-0.111202[/C][C]-1.0839[/C][C]0.140583[/C][/ROW]
[ROW][C]42[/C][C]-0.00837[/C][C]-0.0816[/C][C]0.467574[/C][/ROW]
[ROW][C]43[/C][C]0.023652[/C][C]0.2305[/C][C]0.409088[/C][/ROW]
[ROW][C]44[/C][C]0.05532[/C][C]0.5392[/C][C]0.295506[/C][/ROW]
[ROW][C]45[/C][C]-0.030805[/C][C]-0.3003[/C][C]0.382321[/C][/ROW]
[ROW][C]46[/C][C]0.075105[/C][C]0.732[/C][C]0.232974[/C][/ROW]
[ROW][C]47[/C][C]0.021594[/C][C]0.2105[/C][C]0.416873[/C][/ROW]
[ROW][C]48[/C][C]0.034122[/C][C]0.3326[/C][C]0.37009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282937&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282937&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
10.3324493.24030.000823
20.241872.35750.010226
30.2324722.26590.012865
40.2418692.35740.010226
5-0.062555-0.60970.271754
6-0.012215-0.11910.452742
70.1480091.44260.07621
8-0.020366-0.19850.421539
9-0.063341-0.61740.269234
10-0.029777-0.29020.386137
110.0522820.50960.305764
12-0.09105-0.88750.188539
13-0.00367-0.03580.485772
14-0.085002-0.82850.204733
15-0.030042-0.29280.385151
16-0.156104-1.52150.065726
17-0.060237-0.58710.27926
18-0.164527-1.60360.05606
19-0.088233-0.860.19598
20-0.079152-0.77150.221169
21-0.040901-0.39870.345521
220.0520740.50760.30647
230.0238310.23230.40841
240.07960.77580.219885
25-0.057119-0.55670.289512
26-0.076603-0.74660.228564
27-0.103487-1.00870.157849
28-0.127925-1.24690.107758
29-0.10181-0.99230.161782
30-0.07689-0.74940.227723
31-0.125616-1.22430.111924
32-0.057272-0.55820.289004
330.0383910.37420.35455
34-0.048422-0.4720.319021
350.0012280.0120.495238
360.1074521.04730.148807
370.0239590.23350.407928
38-0.036254-0.35340.362301
39-0.05376-0.5240.300752
400.0132290.12890.44884
41-0.111202-1.08390.140583
42-0.00837-0.08160.467574
430.0236520.23050.409088
440.055320.53920.295506
45-0.030805-0.30030.382321
460.0751050.7320.232974
470.0215940.21050.416873
480.0341220.33260.37009






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3324493.24030.000823
20.1476681.43930.076677
30.1319931.28650.100697
40.1286391.25380.106493
5-0.251062-2.4470.008121
6-0.019023-0.18540.42665
70.1904031.85580.033289
8-0.103158-1.00550.158614
9-0.016464-0.16050.436425
10-0.05305-0.51710.303155
110.0326020.31780.37568
12-0.016683-0.16260.435586
130.0486160.47390.318347
14-0.160538-1.56470.060485
150.0271190.26430.39605
16-0.097244-0.94780.172813
170.0232950.22710.410436
18-0.120068-1.17030.122409
190.0225020.21930.413434
200.0034410.03350.486657
210.0392540.38260.351434
220.1199331.1690.122671
23-0.017199-0.16760.433614
240.0110490.10770.457234
25-0.104953-1.0230.154463
26-0.163821-1.59670.056823
270.0071030.06920.472475
28-0.111953-1.09120.138977
290.0694280.67670.25012
30-0.027599-0.2690.394254
31-0.109303-1.06540.144707
320.0550110.53620.296544
330.1297321.26450.104577
34-0.131623-1.28290.101324
350.0699410.68170.248543
360.065460.6380.262495
37-0.124605-1.21450.113783
380.0778070.75840.225053
39-0.161323-1.57240.059594
400.0072230.07040.47201
41-0.016786-0.16360.435192
420.0789680.76970.221699
43-0.011952-0.11650.453752
44-0.003579-0.03490.486122
45-0.077873-0.7590.224863
460.015310.14920.440848
47-0.039491-0.38490.350583
480.0861220.83940.201674

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.332449 & 3.2403 & 0.000823 \tabularnewline
2 & 0.147668 & 1.4393 & 0.076677 \tabularnewline
3 & 0.131993 & 1.2865 & 0.100697 \tabularnewline
4 & 0.128639 & 1.2538 & 0.106493 \tabularnewline
5 & -0.251062 & -2.447 & 0.008121 \tabularnewline
6 & -0.019023 & -0.1854 & 0.42665 \tabularnewline
7 & 0.190403 & 1.8558 & 0.033289 \tabularnewline
8 & -0.103158 & -1.0055 & 0.158614 \tabularnewline
9 & -0.016464 & -0.1605 & 0.436425 \tabularnewline
10 & -0.05305 & -0.5171 & 0.303155 \tabularnewline
11 & 0.032602 & 0.3178 & 0.37568 \tabularnewline
12 & -0.016683 & -0.1626 & 0.435586 \tabularnewline
13 & 0.048616 & 0.4739 & 0.318347 \tabularnewline
14 & -0.160538 & -1.5647 & 0.060485 \tabularnewline
15 & 0.027119 & 0.2643 & 0.39605 \tabularnewline
16 & -0.097244 & -0.9478 & 0.172813 \tabularnewline
17 & 0.023295 & 0.2271 & 0.410436 \tabularnewline
18 & -0.120068 & -1.1703 & 0.122409 \tabularnewline
19 & 0.022502 & 0.2193 & 0.413434 \tabularnewline
20 & 0.003441 & 0.0335 & 0.486657 \tabularnewline
21 & 0.039254 & 0.3826 & 0.351434 \tabularnewline
22 & 0.119933 & 1.169 & 0.122671 \tabularnewline
23 & -0.017199 & -0.1676 & 0.433614 \tabularnewline
24 & 0.011049 & 0.1077 & 0.457234 \tabularnewline
25 & -0.104953 & -1.023 & 0.154463 \tabularnewline
26 & -0.163821 & -1.5967 & 0.056823 \tabularnewline
27 & 0.007103 & 0.0692 & 0.472475 \tabularnewline
28 & -0.111953 & -1.0912 & 0.138977 \tabularnewline
29 & 0.069428 & 0.6767 & 0.25012 \tabularnewline
30 & -0.027599 & -0.269 & 0.394254 \tabularnewline
31 & -0.109303 & -1.0654 & 0.144707 \tabularnewline
32 & 0.055011 & 0.5362 & 0.296544 \tabularnewline
33 & 0.129732 & 1.2645 & 0.104577 \tabularnewline
34 & -0.131623 & -1.2829 & 0.101324 \tabularnewline
35 & 0.069941 & 0.6817 & 0.248543 \tabularnewline
36 & 0.06546 & 0.638 & 0.262495 \tabularnewline
37 & -0.124605 & -1.2145 & 0.113783 \tabularnewline
38 & 0.077807 & 0.7584 & 0.225053 \tabularnewline
39 & -0.161323 & -1.5724 & 0.059594 \tabularnewline
40 & 0.007223 & 0.0704 & 0.47201 \tabularnewline
41 & -0.016786 & -0.1636 & 0.435192 \tabularnewline
42 & 0.078968 & 0.7697 & 0.221699 \tabularnewline
43 & -0.011952 & -0.1165 & 0.453752 \tabularnewline
44 & -0.003579 & -0.0349 & 0.486122 \tabularnewline
45 & -0.077873 & -0.759 & 0.224863 \tabularnewline
46 & 0.01531 & 0.1492 & 0.440848 \tabularnewline
47 & -0.039491 & -0.3849 & 0.350583 \tabularnewline
48 & 0.086122 & 0.8394 & 0.201674 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282937&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]0.332449[/C][C]3.2403[/C][C]0.000823[/C][/ROW]
[ROW][C]2[/C][C]0.147668[/C][C]1.4393[/C][C]0.076677[/C][/ROW]
[ROW][C]3[/C][C]0.131993[/C][C]1.2865[/C][C]0.100697[/C][/ROW]
[ROW][C]4[/C][C]0.128639[/C][C]1.2538[/C][C]0.106493[/C][/ROW]
[ROW][C]5[/C][C]-0.251062[/C][C]-2.447[/C][C]0.008121[/C][/ROW]
[ROW][C]6[/C][C]-0.019023[/C][C]-0.1854[/C][C]0.42665[/C][/ROW]
[ROW][C]7[/C][C]0.190403[/C][C]1.8558[/C][C]0.033289[/C][/ROW]
[ROW][C]8[/C][C]-0.103158[/C][C]-1.0055[/C][C]0.158614[/C][/ROW]
[ROW][C]9[/C][C]-0.016464[/C][C]-0.1605[/C][C]0.436425[/C][/ROW]
[ROW][C]10[/C][C]-0.05305[/C][C]-0.5171[/C][C]0.303155[/C][/ROW]
[ROW][C]11[/C][C]0.032602[/C][C]0.3178[/C][C]0.37568[/C][/ROW]
[ROW][C]12[/C][C]-0.016683[/C][C]-0.1626[/C][C]0.435586[/C][/ROW]
[ROW][C]13[/C][C]0.048616[/C][C]0.4739[/C][C]0.318347[/C][/ROW]
[ROW][C]14[/C][C]-0.160538[/C][C]-1.5647[/C][C]0.060485[/C][/ROW]
[ROW][C]15[/C][C]0.027119[/C][C]0.2643[/C][C]0.39605[/C][/ROW]
[ROW][C]16[/C][C]-0.097244[/C][C]-0.9478[/C][C]0.172813[/C][/ROW]
[ROW][C]17[/C][C]0.023295[/C][C]0.2271[/C][C]0.410436[/C][/ROW]
[ROW][C]18[/C][C]-0.120068[/C][C]-1.1703[/C][C]0.122409[/C][/ROW]
[ROW][C]19[/C][C]0.022502[/C][C]0.2193[/C][C]0.413434[/C][/ROW]
[ROW][C]20[/C][C]0.003441[/C][C]0.0335[/C][C]0.486657[/C][/ROW]
[ROW][C]21[/C][C]0.039254[/C][C]0.3826[/C][C]0.351434[/C][/ROW]
[ROW][C]22[/C][C]0.119933[/C][C]1.169[/C][C]0.122671[/C][/ROW]
[ROW][C]23[/C][C]-0.017199[/C][C]-0.1676[/C][C]0.433614[/C][/ROW]
[ROW][C]24[/C][C]0.011049[/C][C]0.1077[/C][C]0.457234[/C][/ROW]
[ROW][C]25[/C][C]-0.104953[/C][C]-1.023[/C][C]0.154463[/C][/ROW]
[ROW][C]26[/C][C]-0.163821[/C][C]-1.5967[/C][C]0.056823[/C][/ROW]
[ROW][C]27[/C][C]0.007103[/C][C]0.0692[/C][C]0.472475[/C][/ROW]
[ROW][C]28[/C][C]-0.111953[/C][C]-1.0912[/C][C]0.138977[/C][/ROW]
[ROW][C]29[/C][C]0.069428[/C][C]0.6767[/C][C]0.25012[/C][/ROW]
[ROW][C]30[/C][C]-0.027599[/C][C]-0.269[/C][C]0.394254[/C][/ROW]
[ROW][C]31[/C][C]-0.109303[/C][C]-1.0654[/C][C]0.144707[/C][/ROW]
[ROW][C]32[/C][C]0.055011[/C][C]0.5362[/C][C]0.296544[/C][/ROW]
[ROW][C]33[/C][C]0.129732[/C][C]1.2645[/C][C]0.104577[/C][/ROW]
[ROW][C]34[/C][C]-0.131623[/C][C]-1.2829[/C][C]0.101324[/C][/ROW]
[ROW][C]35[/C][C]0.069941[/C][C]0.6817[/C][C]0.248543[/C][/ROW]
[ROW][C]36[/C][C]0.06546[/C][C]0.638[/C][C]0.262495[/C][/ROW]
[ROW][C]37[/C][C]-0.124605[/C][C]-1.2145[/C][C]0.113783[/C][/ROW]
[ROW][C]38[/C][C]0.077807[/C][C]0.7584[/C][C]0.225053[/C][/ROW]
[ROW][C]39[/C][C]-0.161323[/C][C]-1.5724[/C][C]0.059594[/C][/ROW]
[ROW][C]40[/C][C]0.007223[/C][C]0.0704[/C][C]0.47201[/C][/ROW]
[ROW][C]41[/C][C]-0.016786[/C][C]-0.1636[/C][C]0.435192[/C][/ROW]
[ROW][C]42[/C][C]0.078968[/C][C]0.7697[/C][C]0.221699[/C][/ROW]
[ROW][C]43[/C][C]-0.011952[/C][C]-0.1165[/C][C]0.453752[/C][/ROW]
[ROW][C]44[/C][C]-0.003579[/C][C]-0.0349[/C][C]0.486122[/C][/ROW]
[ROW][C]45[/C][C]-0.077873[/C][C]-0.759[/C][C]0.224863[/C][/ROW]
[ROW][C]46[/C][C]0.01531[/C][C]0.1492[/C][C]0.440848[/C][/ROW]
[ROW][C]47[/C][C]-0.039491[/C][C]-0.3849[/C][C]0.350583[/C][/ROW]
[ROW][C]48[/C][C]0.086122[/C][C]0.8394[/C][C]0.201674[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282937&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282937&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
10.3324493.24030.000823
20.1476681.43930.076677
30.1319931.28650.100697
40.1286391.25380.106493
5-0.251062-2.4470.008121
6-0.019023-0.18540.42665
70.1904031.85580.033289
8-0.103158-1.00550.158614
9-0.016464-0.16050.436425
10-0.05305-0.51710.303155
110.0326020.31780.37568
12-0.016683-0.16260.435586
130.0486160.47390.318347
14-0.160538-1.56470.060485
150.0271190.26430.39605
16-0.097244-0.94780.172813
170.0232950.22710.410436
18-0.120068-1.17030.122409
190.0225020.21930.413434
200.0034410.03350.486657
210.0392540.38260.351434
220.1199331.1690.122671
23-0.017199-0.16760.433614
240.0110490.10770.457234
25-0.104953-1.0230.154463
26-0.163821-1.59670.056823
270.0071030.06920.472475
28-0.111953-1.09120.138977
290.0694280.67670.25012
30-0.027599-0.2690.394254
31-0.109303-1.06540.144707
320.0550110.53620.296544
330.1297321.26450.104577
34-0.131623-1.28290.101324
350.0699410.68170.248543
360.065460.6380.262495
37-0.124605-1.21450.113783
380.0778070.75840.225053
39-0.161323-1.57240.059594
400.0072230.07040.47201
41-0.016786-0.16360.435192
420.0789680.76970.221699
43-0.011952-0.11650.453752
44-0.003579-0.03490.486122
45-0.077873-0.7590.224863
460.015310.14920.440848
47-0.039491-0.38490.350583
480.0861220.83940.201674


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')