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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 17 Aug 2015 00:05:56 +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/Aug/17/t1439766392eqz9gy51ina47cw.htm/, Retrieved Thu, 31 Oct 2024 23:20:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280226, Retrieved Thu, 31 Oct 2024 23:20:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact209
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2014-09-20 19:01:39] [46d78fa4bef23992fc20db72a2a0da97]
- R PD  [Univariate Data Series] [] [2015-08-16 14:59:07] [46d78fa4bef23992fc20db72a2a0da97]
- RMPD    [Harrell-Davis Quantiles] [] [2015-08-16 22:28:46] [46d78fa4bef23992fc20db72a2a0da97]
- RMP         [(Partial) Autocorrelation Function] [] [2015-08-16 23:05:56] [fced41568b3cc41e6659ad201d611503] [Current]
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Dataseries X:
193590
193745
193885
194040
194190
194345
194495
194650
194805
194955
195110
195260
195415
195570
195710
195865
196015
196170
196320
196475
196630
196780
196935
197085
197240
197395
197540
197695
197845
198000
198150
198305
198460
198610
198765
198915
199070
199225
199365
199520
199670
199825
199975
200130
200285
200435
200590
200740
200895
201050
201190
201345
201495
201650
201800
201955
202110
202260
202415
202565
202720
202875
203015
203170
203320
203475
203625
203780
203935
204085
204240
204390
204545
204700
204845
205000
205150
205305
205455
205610
205765
205915
206070
206220
206375
206530
206670
206825
206975
207130
207280
207435
207590
207740
207895
208045
208200
208355
208495
208650
208800
208955
209105
209260
209415
209565
209720
209870




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=280226&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=280226&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280226&T=0

As an alternative you can also use a 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
1-0.478102-4.94551e-06
20.1364451.41140.080514
3-0.02631-0.27220.393013
4-0.105992-1.09640.137686
50.2079612.15120.016857
6-0.445349-4.60676e-06
70.2424392.50780.006825
8-0.141849-1.46730.072615
90.0138480.14320.443182
100.1022571.05780.146274
11-0.420488-4.34961.6e-05
120.8488218.78030
13-0.421595-4.3611.5e-05
140.1237241.27980.10169
15-0.025186-0.26050.39748
16-0.091021-0.94150.174277
170.1813941.87640.031666
18-0.388841-4.02225.4e-05
190.2158722.2330.013815
20-0.126878-1.31240.09609
210.0149730.15490.438604
220.0895360.92620.178221
23-0.36398-3.7650.000136
240.7253347.50290
25-0.365087-3.77650.000131
260.103111.06660.144282
27-0.018109-0.18730.425883
28-0.083944-0.86830.19358
290.160781.66310.049608
30-0.340227-3.51930.000318
310.1814121.87650.031653
32-0.105955-1.0960.137768
330.0082040.08490.466264
340.0748740.77450.220171
35-0.32326-3.34380.00057
360.6691356.92160
37-0.324366-3.35530.000549
380.0963410.99660.160613
39-0.024877-0.25730.398708
40-0.063021-0.65190.257933
410.1263191.30670.097065
42-0.291612-3.01650.001598
430.1607981.66330.049589
44-0.098878-1.02280.154354
450.0152810.15810.43735
460.0621530.64290.260827
47-0.266752-2.75930.003408
480.5594945.78740

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.478102 & -4.9455 & 1e-06 \tabularnewline
2 & 0.136445 & 1.4114 & 0.080514 \tabularnewline
3 & -0.02631 & -0.2722 & 0.393013 \tabularnewline
4 & -0.105992 & -1.0964 & 0.137686 \tabularnewline
5 & 0.207961 & 2.1512 & 0.016857 \tabularnewline
6 & -0.445349 & -4.6067 & 6e-06 \tabularnewline
7 & 0.242439 & 2.5078 & 0.006825 \tabularnewline
8 & -0.141849 & -1.4673 & 0.072615 \tabularnewline
9 & 0.013848 & 0.1432 & 0.443182 \tabularnewline
10 & 0.102257 & 1.0578 & 0.146274 \tabularnewline
11 & -0.420488 & -4.3496 & 1.6e-05 \tabularnewline
12 & 0.848821 & 8.7803 & 0 \tabularnewline
13 & -0.421595 & -4.361 & 1.5e-05 \tabularnewline
14 & 0.123724 & 1.2798 & 0.10169 \tabularnewline
15 & -0.025186 & -0.2605 & 0.39748 \tabularnewline
16 & -0.091021 & -0.9415 & 0.174277 \tabularnewline
17 & 0.181394 & 1.8764 & 0.031666 \tabularnewline
18 & -0.388841 & -4.0222 & 5.4e-05 \tabularnewline
19 & 0.215872 & 2.233 & 0.013815 \tabularnewline
20 & -0.126878 & -1.3124 & 0.09609 \tabularnewline
21 & 0.014973 & 0.1549 & 0.438604 \tabularnewline
22 & 0.089536 & 0.9262 & 0.178221 \tabularnewline
23 & -0.36398 & -3.765 & 0.000136 \tabularnewline
24 & 0.725334 & 7.5029 & 0 \tabularnewline
25 & -0.365087 & -3.7765 & 0.000131 \tabularnewline
26 & 0.10311 & 1.0666 & 0.144282 \tabularnewline
27 & -0.018109 & -0.1873 & 0.425883 \tabularnewline
28 & -0.083944 & -0.8683 & 0.19358 \tabularnewline
29 & 0.16078 & 1.6631 & 0.049608 \tabularnewline
30 & -0.340227 & -3.5193 & 0.000318 \tabularnewline
31 & 0.181412 & 1.8765 & 0.031653 \tabularnewline
32 & -0.105955 & -1.096 & 0.137768 \tabularnewline
33 & 0.008204 & 0.0849 & 0.466264 \tabularnewline
34 & 0.074874 & 0.7745 & 0.220171 \tabularnewline
35 & -0.32326 & -3.3438 & 0.00057 \tabularnewline
36 & 0.669135 & 6.9216 & 0 \tabularnewline
37 & -0.324366 & -3.3553 & 0.000549 \tabularnewline
38 & 0.096341 & 0.9966 & 0.160613 \tabularnewline
39 & -0.024877 & -0.2573 & 0.398708 \tabularnewline
40 & -0.063021 & -0.6519 & 0.257933 \tabularnewline
41 & 0.126319 & 1.3067 & 0.097065 \tabularnewline
42 & -0.291612 & -3.0165 & 0.001598 \tabularnewline
43 & 0.160798 & 1.6633 & 0.049589 \tabularnewline
44 & -0.098878 & -1.0228 & 0.154354 \tabularnewline
45 & 0.015281 & 0.1581 & 0.43735 \tabularnewline
46 & 0.062153 & 0.6429 & 0.260827 \tabularnewline
47 & -0.266752 & -2.7593 & 0.003408 \tabularnewline
48 & 0.559494 & 5.7874 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280226&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]-0.478102[/C][C]-4.9455[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.136445[/C][C]1.4114[/C][C]0.080514[/C][/ROW]
[ROW][C]3[/C][C]-0.02631[/C][C]-0.2722[/C][C]0.393013[/C][/ROW]
[ROW][C]4[/C][C]-0.105992[/C][C]-1.0964[/C][C]0.137686[/C][/ROW]
[ROW][C]5[/C][C]0.207961[/C][C]2.1512[/C][C]0.016857[/C][/ROW]
[ROW][C]6[/C][C]-0.445349[/C][C]-4.6067[/C][C]6e-06[/C][/ROW]
[ROW][C]7[/C][C]0.242439[/C][C]2.5078[/C][C]0.006825[/C][/ROW]
[ROW][C]8[/C][C]-0.141849[/C][C]-1.4673[/C][C]0.072615[/C][/ROW]
[ROW][C]9[/C][C]0.013848[/C][C]0.1432[/C][C]0.443182[/C][/ROW]
[ROW][C]10[/C][C]0.102257[/C][C]1.0578[/C][C]0.146274[/C][/ROW]
[ROW][C]11[/C][C]-0.420488[/C][C]-4.3496[/C][C]1.6e-05[/C][/ROW]
[ROW][C]12[/C][C]0.848821[/C][C]8.7803[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.421595[/C][C]-4.361[/C][C]1.5e-05[/C][/ROW]
[ROW][C]14[/C][C]0.123724[/C][C]1.2798[/C][C]0.10169[/C][/ROW]
[ROW][C]15[/C][C]-0.025186[/C][C]-0.2605[/C][C]0.39748[/C][/ROW]
[ROW][C]16[/C][C]-0.091021[/C][C]-0.9415[/C][C]0.174277[/C][/ROW]
[ROW][C]17[/C][C]0.181394[/C][C]1.8764[/C][C]0.031666[/C][/ROW]
[ROW][C]18[/C][C]-0.388841[/C][C]-4.0222[/C][C]5.4e-05[/C][/ROW]
[ROW][C]19[/C][C]0.215872[/C][C]2.233[/C][C]0.013815[/C][/ROW]
[ROW][C]20[/C][C]-0.126878[/C][C]-1.3124[/C][C]0.09609[/C][/ROW]
[ROW][C]21[/C][C]0.014973[/C][C]0.1549[/C][C]0.438604[/C][/ROW]
[ROW][C]22[/C][C]0.089536[/C][C]0.9262[/C][C]0.178221[/C][/ROW]
[ROW][C]23[/C][C]-0.36398[/C][C]-3.765[/C][C]0.000136[/C][/ROW]
[ROW][C]24[/C][C]0.725334[/C][C]7.5029[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.365087[/C][C]-3.7765[/C][C]0.000131[/C][/ROW]
[ROW][C]26[/C][C]0.10311[/C][C]1.0666[/C][C]0.144282[/C][/ROW]
[ROW][C]27[/C][C]-0.018109[/C][C]-0.1873[/C][C]0.425883[/C][/ROW]
[ROW][C]28[/C][C]-0.083944[/C][C]-0.8683[/C][C]0.19358[/C][/ROW]
[ROW][C]29[/C][C]0.16078[/C][C]1.6631[/C][C]0.049608[/C][/ROW]
[ROW][C]30[/C][C]-0.340227[/C][C]-3.5193[/C][C]0.000318[/C][/ROW]
[ROW][C]31[/C][C]0.181412[/C][C]1.8765[/C][C]0.031653[/C][/ROW]
[ROW][C]32[/C][C]-0.105955[/C][C]-1.096[/C][C]0.137768[/C][/ROW]
[ROW][C]33[/C][C]0.008204[/C][C]0.0849[/C][C]0.466264[/C][/ROW]
[ROW][C]34[/C][C]0.074874[/C][C]0.7745[/C][C]0.220171[/C][/ROW]
[ROW][C]35[/C][C]-0.32326[/C][C]-3.3438[/C][C]0.00057[/C][/ROW]
[ROW][C]36[/C][C]0.669135[/C][C]6.9216[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.324366[/C][C]-3.3553[/C][C]0.000549[/C][/ROW]
[ROW][C]38[/C][C]0.096341[/C][C]0.9966[/C][C]0.160613[/C][/ROW]
[ROW][C]39[/C][C]-0.024877[/C][C]-0.2573[/C][C]0.398708[/C][/ROW]
[ROW][C]40[/C][C]-0.063021[/C][C]-0.6519[/C][C]0.257933[/C][/ROW]
[ROW][C]41[/C][C]0.126319[/C][C]1.3067[/C][C]0.097065[/C][/ROW]
[ROW][C]42[/C][C]-0.291612[/C][C]-3.0165[/C][C]0.001598[/C][/ROW]
[ROW][C]43[/C][C]0.160798[/C][C]1.6633[/C][C]0.049589[/C][/ROW]
[ROW][C]44[/C][C]-0.098878[/C][C]-1.0228[/C][C]0.154354[/C][/ROW]
[ROW][C]45[/C][C]0.015281[/C][C]0.1581[/C][C]0.43735[/C][/ROW]
[ROW][C]46[/C][C]0.062153[/C][C]0.6429[/C][C]0.260827[/C][/ROW]
[ROW][C]47[/C][C]-0.266752[/C][C]-2.7593[/C][C]0.003408[/C][/ROW]
[ROW][C]48[/C][C]0.559494[/C][C]5.7874[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280226&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280226&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.478102-4.94551e-06
20.1364451.41140.080514
3-0.02631-0.27220.393013
4-0.105992-1.09640.137686
50.2079612.15120.016857
6-0.445349-4.60676e-06
70.2424392.50780.006825
8-0.141849-1.46730.072615
90.0138480.14320.443182
100.1022571.05780.146274
11-0.420488-4.34961.6e-05
120.8488218.78030
13-0.421595-4.3611.5e-05
140.1237241.27980.10169
15-0.025186-0.26050.39748
16-0.091021-0.94150.174277
170.1813941.87640.031666
18-0.388841-4.02225.4e-05
190.2158722.2330.013815
20-0.126878-1.31240.09609
210.0149730.15490.438604
220.0895360.92620.178221
23-0.36398-3.7650.000136
240.7253347.50290
25-0.365087-3.77650.000131
260.103111.06660.144282
27-0.018109-0.18730.425883
28-0.083944-0.86830.19358
290.160781.66310.049608
30-0.340227-3.51930.000318
310.1814121.87650.031653
32-0.105955-1.0960.137768
330.0082040.08490.466264
340.0748740.77450.220171
35-0.32326-3.34380.00057
360.6691356.92160
37-0.324366-3.35530.000549
380.0963410.99660.160613
39-0.024877-0.25730.398708
40-0.063021-0.65190.257933
410.1263191.30670.097065
42-0.291612-3.01650.001598
430.1607981.66330.049589
44-0.098878-1.02280.154354
450.0152810.15810.43735
460.0621530.64290.260827
47-0.266752-2.75930.003408
480.5594945.78740







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.478102-4.94551e-06
2-0.119438-1.23550.109679
3-0.013661-0.14130.443946
4-0.143834-1.48780.069868
50.121781.25970.10526
6-0.38741-4.00745.7e-05
7-0.197344-2.04130.021839
8-0.183074-1.89370.030481
9-0.18662-1.93040.028101
10-0.084233-0.87130.192766
11-0.630089-6.51770
120.5612075.80520
130.2301662.38090.00952
14-0.088989-0.92050.17969
150.0116530.12050.452141
16-0.051166-0.52930.29886
17-0.093635-0.96860.167472
180.1389471.43730.076778
19-0.107723-1.11430.133826
20-0.006759-0.06990.472196
21-0.041126-0.42540.335696
22-0.085216-0.88150.190015
230.0196710.20350.419574
240.0212350.21970.413278
25-0.034296-0.35480.361734
26-0.010907-0.11280.455191
27-0.061326-0.63440.263599
28-0.043368-0.44860.327311
29-0.020173-0.20870.417552
30-0.03936-0.40710.342359
31-0.089422-0.9250.178528
32-0.058872-0.6090.271916
33-0.085052-0.87980.190475
34-0.110562-1.14370.127658
35-0.127503-1.31890.095009
360.1124451.16310.12368
370.0403690.41760.338545
380.012390.12820.44913
39-0.048766-0.50440.307495
40-0.0232-0.240.405402
41-0.057521-0.5950.276548
420.0360330.37270.355043
430.0238580.24680.402774
44-0.016439-0.170.432646
45-0.017824-0.18440.427034
460.0244970.25340.400221
470.1076291.11330.134032
48-0.108016-1.11730.13318

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.478102 & -4.9455 & 1e-06 \tabularnewline
2 & -0.119438 & -1.2355 & 0.109679 \tabularnewline
3 & -0.013661 & -0.1413 & 0.443946 \tabularnewline
4 & -0.143834 & -1.4878 & 0.069868 \tabularnewline
5 & 0.12178 & 1.2597 & 0.10526 \tabularnewline
6 & -0.38741 & -4.0074 & 5.7e-05 \tabularnewline
7 & -0.197344 & -2.0413 & 0.021839 \tabularnewline
8 & -0.183074 & -1.8937 & 0.030481 \tabularnewline
9 & -0.18662 & -1.9304 & 0.028101 \tabularnewline
10 & -0.084233 & -0.8713 & 0.192766 \tabularnewline
11 & -0.630089 & -6.5177 & 0 \tabularnewline
12 & 0.561207 & 5.8052 & 0 \tabularnewline
13 & 0.230166 & 2.3809 & 0.00952 \tabularnewline
14 & -0.088989 & -0.9205 & 0.17969 \tabularnewline
15 & 0.011653 & 0.1205 & 0.452141 \tabularnewline
16 & -0.051166 & -0.5293 & 0.29886 \tabularnewline
17 & -0.093635 & -0.9686 & 0.167472 \tabularnewline
18 & 0.138947 & 1.4373 & 0.076778 \tabularnewline
19 & -0.107723 & -1.1143 & 0.133826 \tabularnewline
20 & -0.006759 & -0.0699 & 0.472196 \tabularnewline
21 & -0.041126 & -0.4254 & 0.335696 \tabularnewline
22 & -0.085216 & -0.8815 & 0.190015 \tabularnewline
23 & 0.019671 & 0.2035 & 0.419574 \tabularnewline
24 & 0.021235 & 0.2197 & 0.413278 \tabularnewline
25 & -0.034296 & -0.3548 & 0.361734 \tabularnewline
26 & -0.010907 & -0.1128 & 0.455191 \tabularnewline
27 & -0.061326 & -0.6344 & 0.263599 \tabularnewline
28 & -0.043368 & -0.4486 & 0.327311 \tabularnewline
29 & -0.020173 & -0.2087 & 0.417552 \tabularnewline
30 & -0.03936 & -0.4071 & 0.342359 \tabularnewline
31 & -0.089422 & -0.925 & 0.178528 \tabularnewline
32 & -0.058872 & -0.609 & 0.271916 \tabularnewline
33 & -0.085052 & -0.8798 & 0.190475 \tabularnewline
34 & -0.110562 & -1.1437 & 0.127658 \tabularnewline
35 & -0.127503 & -1.3189 & 0.095009 \tabularnewline
36 & 0.112445 & 1.1631 & 0.12368 \tabularnewline
37 & 0.040369 & 0.4176 & 0.338545 \tabularnewline
38 & 0.01239 & 0.1282 & 0.44913 \tabularnewline
39 & -0.048766 & -0.5044 & 0.307495 \tabularnewline
40 & -0.0232 & -0.24 & 0.405402 \tabularnewline
41 & -0.057521 & -0.595 & 0.276548 \tabularnewline
42 & 0.036033 & 0.3727 & 0.355043 \tabularnewline
43 & 0.023858 & 0.2468 & 0.402774 \tabularnewline
44 & -0.016439 & -0.17 & 0.432646 \tabularnewline
45 & -0.017824 & -0.1844 & 0.427034 \tabularnewline
46 & 0.024497 & 0.2534 & 0.400221 \tabularnewline
47 & 0.107629 & 1.1133 & 0.134032 \tabularnewline
48 & -0.108016 & -1.1173 & 0.13318 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280226&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]-0.478102[/C][C]-4.9455[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.119438[/C][C]-1.2355[/C][C]0.109679[/C][/ROW]
[ROW][C]3[/C][C]-0.013661[/C][C]-0.1413[/C][C]0.443946[/C][/ROW]
[ROW][C]4[/C][C]-0.143834[/C][C]-1.4878[/C][C]0.069868[/C][/ROW]
[ROW][C]5[/C][C]0.12178[/C][C]1.2597[/C][C]0.10526[/C][/ROW]
[ROW][C]6[/C][C]-0.38741[/C][C]-4.0074[/C][C]5.7e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.197344[/C][C]-2.0413[/C][C]0.021839[/C][/ROW]
[ROW][C]8[/C][C]-0.183074[/C][C]-1.8937[/C][C]0.030481[/C][/ROW]
[ROW][C]9[/C][C]-0.18662[/C][C]-1.9304[/C][C]0.028101[/C][/ROW]
[ROW][C]10[/C][C]-0.084233[/C][C]-0.8713[/C][C]0.192766[/C][/ROW]
[ROW][C]11[/C][C]-0.630089[/C][C]-6.5177[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.561207[/C][C]5.8052[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.230166[/C][C]2.3809[/C][C]0.00952[/C][/ROW]
[ROW][C]14[/C][C]-0.088989[/C][C]-0.9205[/C][C]0.17969[/C][/ROW]
[ROW][C]15[/C][C]0.011653[/C][C]0.1205[/C][C]0.452141[/C][/ROW]
[ROW][C]16[/C][C]-0.051166[/C][C]-0.5293[/C][C]0.29886[/C][/ROW]
[ROW][C]17[/C][C]-0.093635[/C][C]-0.9686[/C][C]0.167472[/C][/ROW]
[ROW][C]18[/C][C]0.138947[/C][C]1.4373[/C][C]0.076778[/C][/ROW]
[ROW][C]19[/C][C]-0.107723[/C][C]-1.1143[/C][C]0.133826[/C][/ROW]
[ROW][C]20[/C][C]-0.006759[/C][C]-0.0699[/C][C]0.472196[/C][/ROW]
[ROW][C]21[/C][C]-0.041126[/C][C]-0.4254[/C][C]0.335696[/C][/ROW]
[ROW][C]22[/C][C]-0.085216[/C][C]-0.8815[/C][C]0.190015[/C][/ROW]
[ROW][C]23[/C][C]0.019671[/C][C]0.2035[/C][C]0.419574[/C][/ROW]
[ROW][C]24[/C][C]0.021235[/C][C]0.2197[/C][C]0.413278[/C][/ROW]
[ROW][C]25[/C][C]-0.034296[/C][C]-0.3548[/C][C]0.361734[/C][/ROW]
[ROW][C]26[/C][C]-0.010907[/C][C]-0.1128[/C][C]0.455191[/C][/ROW]
[ROW][C]27[/C][C]-0.061326[/C][C]-0.6344[/C][C]0.263599[/C][/ROW]
[ROW][C]28[/C][C]-0.043368[/C][C]-0.4486[/C][C]0.327311[/C][/ROW]
[ROW][C]29[/C][C]-0.020173[/C][C]-0.2087[/C][C]0.417552[/C][/ROW]
[ROW][C]30[/C][C]-0.03936[/C][C]-0.4071[/C][C]0.342359[/C][/ROW]
[ROW][C]31[/C][C]-0.089422[/C][C]-0.925[/C][C]0.178528[/C][/ROW]
[ROW][C]32[/C][C]-0.058872[/C][C]-0.609[/C][C]0.271916[/C][/ROW]
[ROW][C]33[/C][C]-0.085052[/C][C]-0.8798[/C][C]0.190475[/C][/ROW]
[ROW][C]34[/C][C]-0.110562[/C][C]-1.1437[/C][C]0.127658[/C][/ROW]
[ROW][C]35[/C][C]-0.127503[/C][C]-1.3189[/C][C]0.095009[/C][/ROW]
[ROW][C]36[/C][C]0.112445[/C][C]1.1631[/C][C]0.12368[/C][/ROW]
[ROW][C]37[/C][C]0.040369[/C][C]0.4176[/C][C]0.338545[/C][/ROW]
[ROW][C]38[/C][C]0.01239[/C][C]0.1282[/C][C]0.44913[/C][/ROW]
[ROW][C]39[/C][C]-0.048766[/C][C]-0.5044[/C][C]0.307495[/C][/ROW]
[ROW][C]40[/C][C]-0.0232[/C][C]-0.24[/C][C]0.405402[/C][/ROW]
[ROW][C]41[/C][C]-0.057521[/C][C]-0.595[/C][C]0.276548[/C][/ROW]
[ROW][C]42[/C][C]0.036033[/C][C]0.3727[/C][C]0.355043[/C][/ROW]
[ROW][C]43[/C][C]0.023858[/C][C]0.2468[/C][C]0.402774[/C][/ROW]
[ROW][C]44[/C][C]-0.016439[/C][C]-0.17[/C][C]0.432646[/C][/ROW]
[ROW][C]45[/C][C]-0.017824[/C][C]-0.1844[/C][C]0.427034[/C][/ROW]
[ROW][C]46[/C][C]0.024497[/C][C]0.2534[/C][C]0.400221[/C][/ROW]
[ROW][C]47[/C][C]0.107629[/C][C]1.1133[/C][C]0.134032[/C][/ROW]
[ROW][C]48[/C][C]-0.108016[/C][C]-1.1173[/C][C]0.13318[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280226&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280226&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.478102-4.94551e-06
2-0.119438-1.23550.109679
3-0.013661-0.14130.443946
4-0.143834-1.48780.069868
50.121781.25970.10526
6-0.38741-4.00745.7e-05
7-0.197344-2.04130.021839
8-0.183074-1.89370.030481
9-0.18662-1.93040.028101
10-0.084233-0.87130.192766
11-0.630089-6.51770
120.5612075.80520
130.2301662.38090.00952
14-0.088989-0.92050.17969
150.0116530.12050.452141
16-0.051166-0.52930.29886
17-0.093635-0.96860.167472
180.1389471.43730.076778
19-0.107723-1.11430.133826
20-0.006759-0.06990.472196
21-0.041126-0.42540.335696
22-0.085216-0.88150.190015
230.0196710.20350.419574
240.0212350.21970.413278
25-0.034296-0.35480.361734
26-0.010907-0.11280.455191
27-0.061326-0.63440.263599
28-0.043368-0.44860.327311
29-0.020173-0.20870.417552
30-0.03936-0.40710.342359
31-0.089422-0.9250.178528
32-0.058872-0.6090.271916
33-0.085052-0.87980.190475
34-0.110562-1.14370.127658
35-0.127503-1.31890.095009
360.1124451.16310.12368
370.0403690.41760.338545
380.012390.12820.44913
39-0.048766-0.50440.307495
40-0.0232-0.240.405402
41-0.057521-0.5950.276548
420.0360330.37270.355043
430.0238580.24680.402774
44-0.016439-0.170.432646
45-0.017824-0.18440.427034
460.0244970.25340.400221
470.1076291.11330.134032
48-0.108016-1.11730.13318



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):
par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '0'
par2 <- '1'
par1 <- '48'
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')