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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 12 Dec 2008 05:17:09 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/12/t1229084281aj6hodfenpfnk2w.htm/, Retrieved Sun, 19 May 2024 07:48:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32611, Retrieved Sun, 19 May 2024 07:48:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact229

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- R PD  [Univariate Data Series] [Tijdreeks 2 Buite...] [2008-12-11 16:25:30] [2d4aec5ed1856c4828162be37be304d9]
- RMP     [Central Tendency] [Central tendency ...] [2008-12-11 17:41:16] [2d4aec5ed1856c4828162be37be304d9]
- RMP       [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2008-12-12 08:14:08] [2d4aec5ed1856c4828162be37be304d9]
- RMP         [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-12-12 08:45:26] [2d4aec5ed1856c4828162be37be304d9]
- RMP           [Univariate Explorative Data Analysis] [Lag plot + ACF Ti...] [2008-12-12 08:54:04] [2d4aec5ed1856c4828162be37be304d9]
- RMP             [Variance Reduction Matrix] [VRM tijdreeks 2] [2008-12-12 10:58:24] [2d4aec5ed1856c4828162be37be304d9]
- RMP                 [(Partial) Autocorrelation Function] [P(ACF) Tijdreeks ...] [2008-12-12 12:17:09] [d7f41258beeebb8716e3f5d39f3cdc01] [Current]
- RMP                   [ARIMA Backward Selection] [ARIMA Backward Se...] [2008-12-12 12:29:19] [2d4aec5ed1856c4828162be37be304d9]
- RMPD                    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2008-12-22 09:26:11] [2d4aec5ed1856c4828162be37be304d9]
- RMPD                      [Kendall tau Correlation Matrix] [Kendall Tau Corre...] [2008-12-22 09:35:25] [2d4aec5ed1856c4828162be37be304d9]
- RM D                        [Pearson Correlation] [Pearson correlati...] [2008-12-22 09:46:51] [2d4aec5ed1856c4828162be37be304d9]
- RMP                           [Cross Correlation Function] [Cross Correlation...] [2008-12-22 10:31:31] [2d4aec5ed1856c4828162be37be304d9]
-   P                             [Cross Correlation Function] [Cross Correlation...] [2008-12-22 11:21:14] [2d4aec5ed1856c4828162be37be304d9]
- RMP                     [ARIMA Forecasting] [Arima forecast (p...] [2008-12-22 15:10:16] [2d4aec5ed1856c4828162be37be304d9]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2220.6
2161.5
1863.6
1955.1
1907.4
1889.4
2246.3
2213
1965
2285.6
1983.8
1872.4
2371.4
2287
2198.2
2330.4
2014.4
2066.1
2355.8
2232.5
2091.7
2376.5
1931.9
2025.7
2404.9
2316.1
2368.1
2282.5
2158.6
2174.8
2594.1
2281.4
2547.9
2606.3
2190.8
2262.3
2423.8
2520.4
2482.9
2215.9
2441.9
2333.8
2670.2
2431
2559.3
2661.4
2404.6
2378.3
2489.2
2941
2700.9
2335.6
2770
2764.2
2784.9
2898.8
2853.4
3022.6
2851.4
2630.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32611&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32611&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32611&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1608231.11420.135368
20.2506631.73660.044432
30.4309222.98550.002223
40.0042010.02910.48845
50.0191680.13280.447455
60.2142981.48470.072081
7-0.179766-1.24550.109505
8-0.050754-0.35160.363326
90.1010370.70.243651
10-0.310381-2.15040.018295
11-0.17143-1.18770.120398
12-0.033674-0.23330.408261
13-0.296248-2.05250.022799
14-0.105688-0.73220.233795
150.0630560.43690.332084
16-0.147309-1.02060.156283
170.1990641.37920.08712
180.133830.92720.17923
19-0.035557-0.24630.403233
200.1916261.32760.095291
210.0811880.56250.288202
22-0.086258-0.59760.276455
230.2387561.65420.052311
24-0.049166-0.34060.367433
250.0269680.18680.426286
260.0991310.68680.247757
27-0.087669-0.60740.273227
28-0.177134-1.22720.112862
29-0.080615-0.55850.289544
30-0.218494-1.51380.068321
31-0.228721-1.58460.059809
32-0.054622-0.37840.353388
33-0.220138-1.52520.066891
34-0.128218-0.88830.189399
35-0.018031-0.12490.450552
36-0.152194-1.05440.148481
37-0.091583-0.63450.264383
380.0441280.30570.380566
39-0.050307-0.34850.36448
40-0.00048-0.00330.49868
410.0655110.45390.325983
420.0310520.21510.415287
430.0770160.53360.298046
440.0578340.40070.345214
45-0.003377-0.02340.490716
46-0.010569-0.07320.470966
47-0.00189-0.01310.494804
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.160823 & 1.1142 & 0.135368 \tabularnewline
2 & 0.250663 & 1.7366 & 0.044432 \tabularnewline
3 & 0.430922 & 2.9855 & 0.002223 \tabularnewline
4 & 0.004201 & 0.0291 & 0.48845 \tabularnewline
5 & 0.019168 & 0.1328 & 0.447455 \tabularnewline
6 & 0.214298 & 1.4847 & 0.072081 \tabularnewline
7 & -0.179766 & -1.2455 & 0.109505 \tabularnewline
8 & -0.050754 & -0.3516 & 0.363326 \tabularnewline
9 & 0.101037 & 0.7 & 0.243651 \tabularnewline
10 & -0.310381 & -2.1504 & 0.018295 \tabularnewline
11 & -0.17143 & -1.1877 & 0.120398 \tabularnewline
12 & -0.033674 & -0.2333 & 0.408261 \tabularnewline
13 & -0.296248 & -2.0525 & 0.022799 \tabularnewline
14 & -0.105688 & -0.7322 & 0.233795 \tabularnewline
15 & 0.063056 & 0.4369 & 0.332084 \tabularnewline
16 & -0.147309 & -1.0206 & 0.156283 \tabularnewline
17 & 0.199064 & 1.3792 & 0.08712 \tabularnewline
18 & 0.13383 & 0.9272 & 0.17923 \tabularnewline
19 & -0.035557 & -0.2463 & 0.403233 \tabularnewline
20 & 0.191626 & 1.3276 & 0.095291 \tabularnewline
21 & 0.081188 & 0.5625 & 0.288202 \tabularnewline
22 & -0.086258 & -0.5976 & 0.276455 \tabularnewline
23 & 0.238756 & 1.6542 & 0.052311 \tabularnewline
24 & -0.049166 & -0.3406 & 0.367433 \tabularnewline
25 & 0.026968 & 0.1868 & 0.426286 \tabularnewline
26 & 0.099131 & 0.6868 & 0.247757 \tabularnewline
27 & -0.087669 & -0.6074 & 0.273227 \tabularnewline
28 & -0.177134 & -1.2272 & 0.112862 \tabularnewline
29 & -0.080615 & -0.5585 & 0.289544 \tabularnewline
30 & -0.218494 & -1.5138 & 0.068321 \tabularnewline
31 & -0.228721 & -1.5846 & 0.059809 \tabularnewline
32 & -0.054622 & -0.3784 & 0.353388 \tabularnewline
33 & -0.220138 & -1.5252 & 0.066891 \tabularnewline
34 & -0.128218 & -0.8883 & 0.189399 \tabularnewline
35 & -0.018031 & -0.1249 & 0.450552 \tabularnewline
36 & -0.152194 & -1.0544 & 0.148481 \tabularnewline
37 & -0.091583 & -0.6345 & 0.264383 \tabularnewline
38 & 0.044128 & 0.3057 & 0.380566 \tabularnewline
39 & -0.050307 & -0.3485 & 0.36448 \tabularnewline
40 & -0.00048 & -0.0033 & 0.49868 \tabularnewline
41 & 0.065511 & 0.4539 & 0.325983 \tabularnewline
42 & 0.031052 & 0.2151 & 0.415287 \tabularnewline
43 & 0.077016 & 0.5336 & 0.298046 \tabularnewline
44 & 0.057834 & 0.4007 & 0.345214 \tabularnewline
45 & -0.003377 & -0.0234 & 0.490716 \tabularnewline
46 & -0.010569 & -0.0732 & 0.470966 \tabularnewline
47 & -0.00189 & -0.0131 & 0.494804 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32611&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]0.160823[/C][C]1.1142[/C][C]0.135368[/C][/ROW]
[ROW][C]2[/C][C]0.250663[/C][C]1.7366[/C][C]0.044432[/C][/ROW]
[ROW][C]3[/C][C]0.430922[/C][C]2.9855[/C][C]0.002223[/C][/ROW]
[ROW][C]4[/C][C]0.004201[/C][C]0.0291[/C][C]0.48845[/C][/ROW]
[ROW][C]5[/C][C]0.019168[/C][C]0.1328[/C][C]0.447455[/C][/ROW]
[ROW][C]6[/C][C]0.214298[/C][C]1.4847[/C][C]0.072081[/C][/ROW]
[ROW][C]7[/C][C]-0.179766[/C][C]-1.2455[/C][C]0.109505[/C][/ROW]
[ROW][C]8[/C][C]-0.050754[/C][C]-0.3516[/C][C]0.363326[/C][/ROW]
[ROW][C]9[/C][C]0.101037[/C][C]0.7[/C][C]0.243651[/C][/ROW]
[ROW][C]10[/C][C]-0.310381[/C][C]-2.1504[/C][C]0.018295[/C][/ROW]
[ROW][C]11[/C][C]-0.17143[/C][C]-1.1877[/C][C]0.120398[/C][/ROW]
[ROW][C]12[/C][C]-0.033674[/C][C]-0.2333[/C][C]0.408261[/C][/ROW]
[ROW][C]13[/C][C]-0.296248[/C][C]-2.0525[/C][C]0.022799[/C][/ROW]
[ROW][C]14[/C][C]-0.105688[/C][C]-0.7322[/C][C]0.233795[/C][/ROW]
[ROW][C]15[/C][C]0.063056[/C][C]0.4369[/C][C]0.332084[/C][/ROW]
[ROW][C]16[/C][C]-0.147309[/C][C]-1.0206[/C][C]0.156283[/C][/ROW]
[ROW][C]17[/C][C]0.199064[/C][C]1.3792[/C][C]0.08712[/C][/ROW]
[ROW][C]18[/C][C]0.13383[/C][C]0.9272[/C][C]0.17923[/C][/ROW]
[ROW][C]19[/C][C]-0.035557[/C][C]-0.2463[/C][C]0.403233[/C][/ROW]
[ROW][C]20[/C][C]0.191626[/C][C]1.3276[/C][C]0.095291[/C][/ROW]
[ROW][C]21[/C][C]0.081188[/C][C]0.5625[/C][C]0.288202[/C][/ROW]
[ROW][C]22[/C][C]-0.086258[/C][C]-0.5976[/C][C]0.276455[/C][/ROW]
[ROW][C]23[/C][C]0.238756[/C][C]1.6542[/C][C]0.052311[/C][/ROW]
[ROW][C]24[/C][C]-0.049166[/C][C]-0.3406[/C][C]0.367433[/C][/ROW]
[ROW][C]25[/C][C]0.026968[/C][C]0.1868[/C][C]0.426286[/C][/ROW]
[ROW][C]26[/C][C]0.099131[/C][C]0.6868[/C][C]0.247757[/C][/ROW]
[ROW][C]27[/C][C]-0.087669[/C][C]-0.6074[/C][C]0.273227[/C][/ROW]
[ROW][C]28[/C][C]-0.177134[/C][C]-1.2272[/C][C]0.112862[/C][/ROW]
[ROW][C]29[/C][C]-0.080615[/C][C]-0.5585[/C][C]0.289544[/C][/ROW]
[ROW][C]30[/C][C]-0.218494[/C][C]-1.5138[/C][C]0.068321[/C][/ROW]
[ROW][C]31[/C][C]-0.228721[/C][C]-1.5846[/C][C]0.059809[/C][/ROW]
[ROW][C]32[/C][C]-0.054622[/C][C]-0.3784[/C][C]0.353388[/C][/ROW]
[ROW][C]33[/C][C]-0.220138[/C][C]-1.5252[/C][C]0.066891[/C][/ROW]
[ROW][C]34[/C][C]-0.128218[/C][C]-0.8883[/C][C]0.189399[/C][/ROW]
[ROW][C]35[/C][C]-0.018031[/C][C]-0.1249[/C][C]0.450552[/C][/ROW]
[ROW][C]36[/C][C]-0.152194[/C][C]-1.0544[/C][C]0.148481[/C][/ROW]
[ROW][C]37[/C][C]-0.091583[/C][C]-0.6345[/C][C]0.264383[/C][/ROW]
[ROW][C]38[/C][C]0.044128[/C][C]0.3057[/C][C]0.380566[/C][/ROW]
[ROW][C]39[/C][C]-0.050307[/C][C]-0.3485[/C][C]0.36448[/C][/ROW]
[ROW][C]40[/C][C]-0.00048[/C][C]-0.0033[/C][C]0.49868[/C][/ROW]
[ROW][C]41[/C][C]0.065511[/C][C]0.4539[/C][C]0.325983[/C][/ROW]
[ROW][C]42[/C][C]0.031052[/C][C]0.2151[/C][C]0.415287[/C][/ROW]
[ROW][C]43[/C][C]0.077016[/C][C]0.5336[/C][C]0.298046[/C][/ROW]
[ROW][C]44[/C][C]0.057834[/C][C]0.4007[/C][C]0.345214[/C][/ROW]
[ROW][C]45[/C][C]-0.003377[/C][C]-0.0234[/C][C]0.490716[/C][/ROW]
[ROW][C]46[/C][C]-0.010569[/C][C]-0.0732[/C][C]0.470966[/C][/ROW]
[ROW][C]47[/C][C]-0.00189[/C][C]-0.0131[/C][C]0.494804[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32611&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32611&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
10.1608231.11420.135368
20.2506631.73660.044432
30.4309222.98550.002223
40.0042010.02910.48845
50.0191680.13280.447455
60.2142981.48470.072081
7-0.179766-1.24550.109505
8-0.050754-0.35160.363326
90.1010370.70.243651
10-0.310381-2.15040.018295
11-0.17143-1.18770.120398
12-0.033674-0.23330.408261
13-0.296248-2.05250.022799
14-0.105688-0.73220.233795
150.0630560.43690.332084
16-0.147309-1.02060.156283
170.1990641.37920.08712
180.133830.92720.17923
19-0.035557-0.24630.403233
200.1916261.32760.095291
210.0811880.56250.288202
22-0.086258-0.59760.276455
230.2387561.65420.052311
24-0.049166-0.34060.367433
250.0269680.18680.426286
260.0991310.68680.247757
27-0.087669-0.60740.273227
28-0.177134-1.22720.112862
29-0.080615-0.55850.289544
30-0.218494-1.51380.068321
31-0.228721-1.58460.059809
32-0.054622-0.37840.353388
33-0.220138-1.52520.066891
34-0.128218-0.88830.189399
35-0.018031-0.12490.450552
36-0.152194-1.05440.148481
37-0.091583-0.63450.264383
380.0441280.30570.380566
39-0.050307-0.34850.36448
40-0.00048-0.00330.49868
410.0655110.45390.325983
420.0310520.21510.415287
430.0770160.53360.298046
440.0578340.40070.345214
45-0.003377-0.02340.490716
46-0.010569-0.07320.470966
47-0.00189-0.01310.494804
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1608231.11420.135368
20.2307681.59880.058213
30.3933812.72540.004468
4-0.152526-1.05670.147962
5-0.193063-1.33760.093669
60.1193940.82720.206113
7-0.141018-0.9770.166734
8-0.056104-0.38870.349608
90.0895240.62020.269017
10-0.211663-1.46640.074525
11-0.184465-1.2780.103695
120.0125280.08680.465598
130.0241830.16750.433823
140.0150840.10450.458601
150.1089450.75480.227031
160.05480.37970.352934
170.23131.60250.057804
18-0.023521-0.1630.435618
19-0.075926-0.5260.300643
20-0.004898-0.03390.486534
21-0.094988-0.65810.25681
22-0.107925-0.74770.229137
230.1588241.10040.13833
24-0.136659-0.94680.174241
250.0966370.66950.253185
26-0.074176-0.51390.304837
270.0010270.00710.497176
28-0.11215-0.7770.220487
29-0.166948-1.15670.12657
300.0488490.33840.368257
31-0.012828-0.08890.464774
32-0.040374-0.27970.390448
33-0.026653-0.18470.427137
34-0.07015-0.4860.314584
35-0.032806-0.22730.410584
360.0053470.0370.485301
37-0.025801-0.17880.429441
380.0237440.16450.435012
390.0835620.57890.282671
40-0.172527-1.19530.11892
41-0.044086-0.30540.380676
42-0.0072-0.04990.480212
430.0051240.03550.485915
44-0.028355-0.19640.422544
450.0012390.00860.496592
46-0.043458-0.30110.382324
470.0343410.23790.406479
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.160823 & 1.1142 & 0.135368 \tabularnewline
2 & 0.230768 & 1.5988 & 0.058213 \tabularnewline
3 & 0.393381 & 2.7254 & 0.004468 \tabularnewline
4 & -0.152526 & -1.0567 & 0.147962 \tabularnewline
5 & -0.193063 & -1.3376 & 0.093669 \tabularnewline
6 & 0.119394 & 0.8272 & 0.206113 \tabularnewline
7 & -0.141018 & -0.977 & 0.166734 \tabularnewline
8 & -0.056104 & -0.3887 & 0.349608 \tabularnewline
9 & 0.089524 & 0.6202 & 0.269017 \tabularnewline
10 & -0.211663 & -1.4664 & 0.074525 \tabularnewline
11 & -0.184465 & -1.278 & 0.103695 \tabularnewline
12 & 0.012528 & 0.0868 & 0.465598 \tabularnewline
13 & 0.024183 & 0.1675 & 0.433823 \tabularnewline
14 & 0.015084 & 0.1045 & 0.458601 \tabularnewline
15 & 0.108945 & 0.7548 & 0.227031 \tabularnewline
16 & 0.0548 & 0.3797 & 0.352934 \tabularnewline
17 & 0.2313 & 1.6025 & 0.057804 \tabularnewline
18 & -0.023521 & -0.163 & 0.435618 \tabularnewline
19 & -0.075926 & -0.526 & 0.300643 \tabularnewline
20 & -0.004898 & -0.0339 & 0.486534 \tabularnewline
21 & -0.094988 & -0.6581 & 0.25681 \tabularnewline
22 & -0.107925 & -0.7477 & 0.229137 \tabularnewline
23 & 0.158824 & 1.1004 & 0.13833 \tabularnewline
24 & -0.136659 & -0.9468 & 0.174241 \tabularnewline
25 & 0.096637 & 0.6695 & 0.253185 \tabularnewline
26 & -0.074176 & -0.5139 & 0.304837 \tabularnewline
27 & 0.001027 & 0.0071 & 0.497176 \tabularnewline
28 & -0.11215 & -0.777 & 0.220487 \tabularnewline
29 & -0.166948 & -1.1567 & 0.12657 \tabularnewline
30 & 0.048849 & 0.3384 & 0.368257 \tabularnewline
31 & -0.012828 & -0.0889 & 0.464774 \tabularnewline
32 & -0.040374 & -0.2797 & 0.390448 \tabularnewline
33 & -0.026653 & -0.1847 & 0.427137 \tabularnewline
34 & -0.07015 & -0.486 & 0.314584 \tabularnewline
35 & -0.032806 & -0.2273 & 0.410584 \tabularnewline
36 & 0.005347 & 0.037 & 0.485301 \tabularnewline
37 & -0.025801 & -0.1788 & 0.429441 \tabularnewline
38 & 0.023744 & 0.1645 & 0.435012 \tabularnewline
39 & 0.083562 & 0.5789 & 0.282671 \tabularnewline
40 & -0.172527 & -1.1953 & 0.11892 \tabularnewline
41 & -0.044086 & -0.3054 & 0.380676 \tabularnewline
42 & -0.0072 & -0.0499 & 0.480212 \tabularnewline
43 & 0.005124 & 0.0355 & 0.485915 \tabularnewline
44 & -0.028355 & -0.1964 & 0.422544 \tabularnewline
45 & 0.001239 & 0.0086 & 0.496592 \tabularnewline
46 & -0.043458 & -0.3011 & 0.382324 \tabularnewline
47 & 0.034341 & 0.2379 & 0.406479 \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32611&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]0.160823[/C][C]1.1142[/C][C]0.135368[/C][/ROW]
[ROW][C]2[/C][C]0.230768[/C][C]1.5988[/C][C]0.058213[/C][/ROW]
[ROW][C]3[/C][C]0.393381[/C][C]2.7254[/C][C]0.004468[/C][/ROW]
[ROW][C]4[/C][C]-0.152526[/C][C]-1.0567[/C][C]0.147962[/C][/ROW]
[ROW][C]5[/C][C]-0.193063[/C][C]-1.3376[/C][C]0.093669[/C][/ROW]
[ROW][C]6[/C][C]0.119394[/C][C]0.8272[/C][C]0.206113[/C][/ROW]
[ROW][C]7[/C][C]-0.141018[/C][C]-0.977[/C][C]0.166734[/C][/ROW]
[ROW][C]8[/C][C]-0.056104[/C][C]-0.3887[/C][C]0.349608[/C][/ROW]
[ROW][C]9[/C][C]0.089524[/C][C]0.6202[/C][C]0.269017[/C][/ROW]
[ROW][C]10[/C][C]-0.211663[/C][C]-1.4664[/C][C]0.074525[/C][/ROW]
[ROW][C]11[/C][C]-0.184465[/C][C]-1.278[/C][C]0.103695[/C][/ROW]
[ROW][C]12[/C][C]0.012528[/C][C]0.0868[/C][C]0.465598[/C][/ROW]
[ROW][C]13[/C][C]0.024183[/C][C]0.1675[/C][C]0.433823[/C][/ROW]
[ROW][C]14[/C][C]0.015084[/C][C]0.1045[/C][C]0.458601[/C][/ROW]
[ROW][C]15[/C][C]0.108945[/C][C]0.7548[/C][C]0.227031[/C][/ROW]
[ROW][C]16[/C][C]0.0548[/C][C]0.3797[/C][C]0.352934[/C][/ROW]
[ROW][C]17[/C][C]0.2313[/C][C]1.6025[/C][C]0.057804[/C][/ROW]
[ROW][C]18[/C][C]-0.023521[/C][C]-0.163[/C][C]0.435618[/C][/ROW]
[ROW][C]19[/C][C]-0.075926[/C][C]-0.526[/C][C]0.300643[/C][/ROW]
[ROW][C]20[/C][C]-0.004898[/C][C]-0.0339[/C][C]0.486534[/C][/ROW]
[ROW][C]21[/C][C]-0.094988[/C][C]-0.6581[/C][C]0.25681[/C][/ROW]
[ROW][C]22[/C][C]-0.107925[/C][C]-0.7477[/C][C]0.229137[/C][/ROW]
[ROW][C]23[/C][C]0.158824[/C][C]1.1004[/C][C]0.13833[/C][/ROW]
[ROW][C]24[/C][C]-0.136659[/C][C]-0.9468[/C][C]0.174241[/C][/ROW]
[ROW][C]25[/C][C]0.096637[/C][C]0.6695[/C][C]0.253185[/C][/ROW]
[ROW][C]26[/C][C]-0.074176[/C][C]-0.5139[/C][C]0.304837[/C][/ROW]
[ROW][C]27[/C][C]0.001027[/C][C]0.0071[/C][C]0.497176[/C][/ROW]
[ROW][C]28[/C][C]-0.11215[/C][C]-0.777[/C][C]0.220487[/C][/ROW]
[ROW][C]29[/C][C]-0.166948[/C][C]-1.1567[/C][C]0.12657[/C][/ROW]
[ROW][C]30[/C][C]0.048849[/C][C]0.3384[/C][C]0.368257[/C][/ROW]
[ROW][C]31[/C][C]-0.012828[/C][C]-0.0889[/C][C]0.464774[/C][/ROW]
[ROW][C]32[/C][C]-0.040374[/C][C]-0.2797[/C][C]0.390448[/C][/ROW]
[ROW][C]33[/C][C]-0.026653[/C][C]-0.1847[/C][C]0.427137[/C][/ROW]
[ROW][C]34[/C][C]-0.07015[/C][C]-0.486[/C][C]0.314584[/C][/ROW]
[ROW][C]35[/C][C]-0.032806[/C][C]-0.2273[/C][C]0.410584[/C][/ROW]
[ROW][C]36[/C][C]0.005347[/C][C]0.037[/C][C]0.485301[/C][/ROW]
[ROW][C]37[/C][C]-0.025801[/C][C]-0.1788[/C][C]0.429441[/C][/ROW]
[ROW][C]38[/C][C]0.023744[/C][C]0.1645[/C][C]0.435012[/C][/ROW]
[ROW][C]39[/C][C]0.083562[/C][C]0.5789[/C][C]0.282671[/C][/ROW]
[ROW][C]40[/C][C]-0.172527[/C][C]-1.1953[/C][C]0.11892[/C][/ROW]
[ROW][C]41[/C][C]-0.044086[/C][C]-0.3054[/C][C]0.380676[/C][/ROW]
[ROW][C]42[/C][C]-0.0072[/C][C]-0.0499[/C][C]0.480212[/C][/ROW]
[ROW][C]43[/C][C]0.005124[/C][C]0.0355[/C][C]0.485915[/C][/ROW]
[ROW][C]44[/C][C]-0.028355[/C][C]-0.1964[/C][C]0.422544[/C][/ROW]
[ROW][C]45[/C][C]0.001239[/C][C]0.0086[/C][C]0.496592[/C][/ROW]
[ROW][C]46[/C][C]-0.043458[/C][C]-0.3011[/C][C]0.382324[/C][/ROW]
[ROW][C]47[/C][C]0.034341[/C][C]0.2379[/C][C]0.406479[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32611&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32611&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
10.1608231.11420.135368
20.2307681.59880.058213
30.3933812.72540.004468
4-0.152526-1.05670.147962
5-0.193063-1.33760.093669
60.1193940.82720.206113
7-0.141018-0.9770.166734
8-0.056104-0.38870.349608
90.0895240.62020.269017
10-0.211663-1.46640.074525
11-0.184465-1.2780.103695
120.0125280.08680.465598
130.0241830.16750.433823
140.0150840.10450.458601
150.1089450.75480.227031
160.05480.37970.352934
170.23131.60250.057804
18-0.023521-0.1630.435618
19-0.075926-0.5260.300643
20-0.004898-0.03390.486534
21-0.094988-0.65810.25681
22-0.107925-0.74770.229137
230.1588241.10040.13833
24-0.136659-0.94680.174241
250.0966370.66950.253185
26-0.074176-0.51390.304837
270.0010270.00710.497176
28-0.11215-0.7770.220487
29-0.166948-1.15670.12657
300.0488490.33840.368257
31-0.012828-0.08890.464774
32-0.040374-0.27970.390448
33-0.026653-0.18470.427137
34-0.07015-0.4860.314584
35-0.032806-0.22730.410584
360.0053470.0370.485301
37-0.025801-0.17880.429441
380.0237440.16450.435012
390.0835620.57890.282671
40-0.172527-1.19530.11892
41-0.044086-0.30540.380676
42-0.0072-0.04990.480212
430.0051240.03550.485915
44-0.028355-0.19640.422544
450.0012390.00860.496592
46-0.043458-0.30110.382324
470.0343410.23790.406479
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 0.6 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 0.6 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')