Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 02 Jul 2010 17:59:53 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jul/02/t1278094444xwkb5jai8oddw9m.htm/, Retrieved Sat, 04 May 2024 00:09:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77932, Retrieved Sat, 04 May 2024 00:09:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsthomas talboom
Estimated Impact191
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [percentielen] [2010-07-01 11:45:42] [b6623a0531b43a362887826f077b4445]
- RMP   [Mean Plot] [gemiddeldegrafieken] [2010-07-01 13:10:54] [b6623a0531b43a362887826f077b4445]
- RMPD      [(Partial) Autocorrelation Function] [part autocorrelatie] [2010-07-02 17:59:53] [58d9ccda37eeb031a0ffa1e9ea016ece] [Current]
Feedback Forum

Post a new message
Dataseries X:
237
236
235
233
231
230
231
233
234
234
235
237
246
245
240
239
231
224
229
231
238
240
237
239
248
239
237
232
216
209
214
217
217
227
218
220
229
224
216
208
191
190
196
196
200
204
193
194
207
209
193
175
157
150
162
157
160
167
159
161
179
180
169
152
128
125
131
135
141
154
152
147
163
165
147
130
106
107
115
114
124
141
139
129




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77932&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77932&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77932&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 time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8424626.52570
20.7896826.11680
30.6972345.40081e-06
40.5982314.63391e-05
50.5459164.22864.1e-05
60.4437053.43690.000537
70.3685152.85450.002955
80.2966632.29790.012533
90.1574091.21930.113754
100.0934620.7240.235954
110.0255190.19770.421986
12-0.092082-0.71330.239225
13-0.054996-0.4260.335817
14-0.110249-0.8540.198255
15-0.100789-0.78070.219021
16-0.118092-0.91470.181996
17-0.108103-0.83740.202856
18-0.024913-0.1930.423815
190.0078090.06050.475983
200.0288030.22310.412105
210.080620.62450.267341
220.0357240.27670.391475
230.0407120.31540.376793
240.0073940.05730.47726
25-0.004898-0.03790.484932
260.0186560.14450.442793
27-0.014955-0.11580.454084
28-0.023552-0.18240.427928
29-0.071839-0.55650.289981
30-0.149394-1.15720.125888
31-0.204809-1.58640.058948
32-0.239165-1.85260.034433
33-0.283186-2.19350.016077
34-0.281588-2.18120.01655
35-0.331366-2.56670.006389
36-0.307478-2.38170.01021
37-0.330969-2.56370.00644
38-0.337536-2.61450.005641
39-0.304349-2.35750.010839
40-0.294544-2.28150.01304
41-0.26221-2.03110.023343
42-0.258107-1.99930.025056
43-0.2368-1.83420.035789
44-0.212664-1.64730.052363
45-0.192383-1.49020.070706
46-0.157652-1.22120.1134
47-0.104042-0.80590.211739
48-0.092552-0.71690.238106
49-0.065327-0.5060.307348
50-0.053675-0.41580.339532
51-0.049475-0.38320.351451
52-0.0371-0.28740.387409
53-0.037889-0.29350.385081
54-0.016312-0.12640.449938
55-0.008796-0.06810.472952
56-0.006033-0.04670.481442
570.000910.00710.497198
580.0004770.00370.498531
59-3.1e-05-2e-040.499904
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.842462 & 6.5257 & 0 \tabularnewline
2 & 0.789682 & 6.1168 & 0 \tabularnewline
3 & 0.697234 & 5.4008 & 1e-06 \tabularnewline
4 & 0.598231 & 4.6339 & 1e-05 \tabularnewline
5 & 0.545916 & 4.2286 & 4.1e-05 \tabularnewline
6 & 0.443705 & 3.4369 & 0.000537 \tabularnewline
7 & 0.368515 & 2.8545 & 0.002955 \tabularnewline
8 & 0.296663 & 2.2979 & 0.012533 \tabularnewline
9 & 0.157409 & 1.2193 & 0.113754 \tabularnewline
10 & 0.093462 & 0.724 & 0.235954 \tabularnewline
11 & 0.025519 & 0.1977 & 0.421986 \tabularnewline
12 & -0.092082 & -0.7133 & 0.239225 \tabularnewline
13 & -0.054996 & -0.426 & 0.335817 \tabularnewline
14 & -0.110249 & -0.854 & 0.198255 \tabularnewline
15 & -0.100789 & -0.7807 & 0.219021 \tabularnewline
16 & -0.118092 & -0.9147 & 0.181996 \tabularnewline
17 & -0.108103 & -0.8374 & 0.202856 \tabularnewline
18 & -0.024913 & -0.193 & 0.423815 \tabularnewline
19 & 0.007809 & 0.0605 & 0.475983 \tabularnewline
20 & 0.028803 & 0.2231 & 0.412105 \tabularnewline
21 & 0.08062 & 0.6245 & 0.267341 \tabularnewline
22 & 0.035724 & 0.2767 & 0.391475 \tabularnewline
23 & 0.040712 & 0.3154 & 0.376793 \tabularnewline
24 & 0.007394 & 0.0573 & 0.47726 \tabularnewline
25 & -0.004898 & -0.0379 & 0.484932 \tabularnewline
26 & 0.018656 & 0.1445 & 0.442793 \tabularnewline
27 & -0.014955 & -0.1158 & 0.454084 \tabularnewline
28 & -0.023552 & -0.1824 & 0.427928 \tabularnewline
29 & -0.071839 & -0.5565 & 0.289981 \tabularnewline
30 & -0.149394 & -1.1572 & 0.125888 \tabularnewline
31 & -0.204809 & -1.5864 & 0.058948 \tabularnewline
32 & -0.239165 & -1.8526 & 0.034433 \tabularnewline
33 & -0.283186 & -2.1935 & 0.016077 \tabularnewline
34 & -0.281588 & -2.1812 & 0.01655 \tabularnewline
35 & -0.331366 & -2.5667 & 0.006389 \tabularnewline
36 & -0.307478 & -2.3817 & 0.01021 \tabularnewline
37 & -0.330969 & -2.5637 & 0.00644 \tabularnewline
38 & -0.337536 & -2.6145 & 0.005641 \tabularnewline
39 & -0.304349 & -2.3575 & 0.010839 \tabularnewline
40 & -0.294544 & -2.2815 & 0.01304 \tabularnewline
41 & -0.26221 & -2.0311 & 0.023343 \tabularnewline
42 & -0.258107 & -1.9993 & 0.025056 \tabularnewline
43 & -0.2368 & -1.8342 & 0.035789 \tabularnewline
44 & -0.212664 & -1.6473 & 0.052363 \tabularnewline
45 & -0.192383 & -1.4902 & 0.070706 \tabularnewline
46 & -0.157652 & -1.2212 & 0.1134 \tabularnewline
47 & -0.104042 & -0.8059 & 0.211739 \tabularnewline
48 & -0.092552 & -0.7169 & 0.238106 \tabularnewline
49 & -0.065327 & -0.506 & 0.307348 \tabularnewline
50 & -0.053675 & -0.4158 & 0.339532 \tabularnewline
51 & -0.049475 & -0.3832 & 0.351451 \tabularnewline
52 & -0.0371 & -0.2874 & 0.387409 \tabularnewline
53 & -0.037889 & -0.2935 & 0.385081 \tabularnewline
54 & -0.016312 & -0.1264 & 0.449938 \tabularnewline
55 & -0.008796 & -0.0681 & 0.472952 \tabularnewline
56 & -0.006033 & -0.0467 & 0.481442 \tabularnewline
57 & 0.00091 & 0.0071 & 0.497198 \tabularnewline
58 & 0.000477 & 0.0037 & 0.498531 \tabularnewline
59 & -3.1e-05 & -2e-04 & 0.499904 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77932&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]0.842462[/C][C]6.5257[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.789682[/C][C]6.1168[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.697234[/C][C]5.4008[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.598231[/C][C]4.6339[/C][C]1e-05[/C][/ROW]
[ROW][C]5[/C][C]0.545916[/C][C]4.2286[/C][C]4.1e-05[/C][/ROW]
[ROW][C]6[/C][C]0.443705[/C][C]3.4369[/C][C]0.000537[/C][/ROW]
[ROW][C]7[/C][C]0.368515[/C][C]2.8545[/C][C]0.002955[/C][/ROW]
[ROW][C]8[/C][C]0.296663[/C][C]2.2979[/C][C]0.012533[/C][/ROW]
[ROW][C]9[/C][C]0.157409[/C][C]1.2193[/C][C]0.113754[/C][/ROW]
[ROW][C]10[/C][C]0.093462[/C][C]0.724[/C][C]0.235954[/C][/ROW]
[ROW][C]11[/C][C]0.025519[/C][C]0.1977[/C][C]0.421986[/C][/ROW]
[ROW][C]12[/C][C]-0.092082[/C][C]-0.7133[/C][C]0.239225[/C][/ROW]
[ROW][C]13[/C][C]-0.054996[/C][C]-0.426[/C][C]0.335817[/C][/ROW]
[ROW][C]14[/C][C]-0.110249[/C][C]-0.854[/C][C]0.198255[/C][/ROW]
[ROW][C]15[/C][C]-0.100789[/C][C]-0.7807[/C][C]0.219021[/C][/ROW]
[ROW][C]16[/C][C]-0.118092[/C][C]-0.9147[/C][C]0.181996[/C][/ROW]
[ROW][C]17[/C][C]-0.108103[/C][C]-0.8374[/C][C]0.202856[/C][/ROW]
[ROW][C]18[/C][C]-0.024913[/C][C]-0.193[/C][C]0.423815[/C][/ROW]
[ROW][C]19[/C][C]0.007809[/C][C]0.0605[/C][C]0.475983[/C][/ROW]
[ROW][C]20[/C][C]0.028803[/C][C]0.2231[/C][C]0.412105[/C][/ROW]
[ROW][C]21[/C][C]0.08062[/C][C]0.6245[/C][C]0.267341[/C][/ROW]
[ROW][C]22[/C][C]0.035724[/C][C]0.2767[/C][C]0.391475[/C][/ROW]
[ROW][C]23[/C][C]0.040712[/C][C]0.3154[/C][C]0.376793[/C][/ROW]
[ROW][C]24[/C][C]0.007394[/C][C]0.0573[/C][C]0.47726[/C][/ROW]
[ROW][C]25[/C][C]-0.004898[/C][C]-0.0379[/C][C]0.484932[/C][/ROW]
[ROW][C]26[/C][C]0.018656[/C][C]0.1445[/C][C]0.442793[/C][/ROW]
[ROW][C]27[/C][C]-0.014955[/C][C]-0.1158[/C][C]0.454084[/C][/ROW]
[ROW][C]28[/C][C]-0.023552[/C][C]-0.1824[/C][C]0.427928[/C][/ROW]
[ROW][C]29[/C][C]-0.071839[/C][C]-0.5565[/C][C]0.289981[/C][/ROW]
[ROW][C]30[/C][C]-0.149394[/C][C]-1.1572[/C][C]0.125888[/C][/ROW]
[ROW][C]31[/C][C]-0.204809[/C][C]-1.5864[/C][C]0.058948[/C][/ROW]
[ROW][C]32[/C][C]-0.239165[/C][C]-1.8526[/C][C]0.034433[/C][/ROW]
[ROW][C]33[/C][C]-0.283186[/C][C]-2.1935[/C][C]0.016077[/C][/ROW]
[ROW][C]34[/C][C]-0.281588[/C][C]-2.1812[/C][C]0.01655[/C][/ROW]
[ROW][C]35[/C][C]-0.331366[/C][C]-2.5667[/C][C]0.006389[/C][/ROW]
[ROW][C]36[/C][C]-0.307478[/C][C]-2.3817[/C][C]0.01021[/C][/ROW]
[ROW][C]37[/C][C]-0.330969[/C][C]-2.5637[/C][C]0.00644[/C][/ROW]
[ROW][C]38[/C][C]-0.337536[/C][C]-2.6145[/C][C]0.005641[/C][/ROW]
[ROW][C]39[/C][C]-0.304349[/C][C]-2.3575[/C][C]0.010839[/C][/ROW]
[ROW][C]40[/C][C]-0.294544[/C][C]-2.2815[/C][C]0.01304[/C][/ROW]
[ROW][C]41[/C][C]-0.26221[/C][C]-2.0311[/C][C]0.023343[/C][/ROW]
[ROW][C]42[/C][C]-0.258107[/C][C]-1.9993[/C][C]0.025056[/C][/ROW]
[ROW][C]43[/C][C]-0.2368[/C][C]-1.8342[/C][C]0.035789[/C][/ROW]
[ROW][C]44[/C][C]-0.212664[/C][C]-1.6473[/C][C]0.052363[/C][/ROW]
[ROW][C]45[/C][C]-0.192383[/C][C]-1.4902[/C][C]0.070706[/C][/ROW]
[ROW][C]46[/C][C]-0.157652[/C][C]-1.2212[/C][C]0.1134[/C][/ROW]
[ROW][C]47[/C][C]-0.104042[/C][C]-0.8059[/C][C]0.211739[/C][/ROW]
[ROW][C]48[/C][C]-0.092552[/C][C]-0.7169[/C][C]0.238106[/C][/ROW]
[ROW][C]49[/C][C]-0.065327[/C][C]-0.506[/C][C]0.307348[/C][/ROW]
[ROW][C]50[/C][C]-0.053675[/C][C]-0.4158[/C][C]0.339532[/C][/ROW]
[ROW][C]51[/C][C]-0.049475[/C][C]-0.3832[/C][C]0.351451[/C][/ROW]
[ROW][C]52[/C][C]-0.0371[/C][C]-0.2874[/C][C]0.387409[/C][/ROW]
[ROW][C]53[/C][C]-0.037889[/C][C]-0.2935[/C][C]0.385081[/C][/ROW]
[ROW][C]54[/C][C]-0.016312[/C][C]-0.1264[/C][C]0.449938[/C][/ROW]
[ROW][C]55[/C][C]-0.008796[/C][C]-0.0681[/C][C]0.472952[/C][/ROW]
[ROW][C]56[/C][C]-0.006033[/C][C]-0.0467[/C][C]0.481442[/C][/ROW]
[ROW][C]57[/C][C]0.00091[/C][C]0.0071[/C][C]0.497198[/C][/ROW]
[ROW][C]58[/C][C]0.000477[/C][C]0.0037[/C][C]0.498531[/C][/ROW]
[ROW][C]59[/C][C]-3.1e-05[/C][C]-2e-04[/C][C]0.499904[/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=77932&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77932&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
10.8424626.52570
20.7896826.11680
30.6972345.40081e-06
40.5982314.63391e-05
50.5459164.22864.1e-05
60.4437053.43690.000537
70.3685152.85450.002955
80.2966632.29790.012533
90.1574091.21930.113754
100.0934620.7240.235954
110.0255190.19770.421986
12-0.092082-0.71330.239225
13-0.054996-0.4260.335817
14-0.110249-0.8540.198255
15-0.100789-0.78070.219021
16-0.118092-0.91470.181996
17-0.108103-0.83740.202856
18-0.024913-0.1930.423815
190.0078090.06050.475983
200.0288030.22310.412105
210.080620.62450.267341
220.0357240.27670.391475
230.0407120.31540.376793
240.0073940.05730.47726
25-0.004898-0.03790.484932
260.0186560.14450.442793
27-0.014955-0.11580.454084
28-0.023552-0.18240.427928
29-0.071839-0.55650.289981
30-0.149394-1.15720.125888
31-0.204809-1.58640.058948
32-0.239165-1.85260.034433
33-0.283186-2.19350.016077
34-0.281588-2.18120.01655
35-0.331366-2.56670.006389
36-0.307478-2.38170.01021
37-0.330969-2.56370.00644
38-0.337536-2.61450.005641
39-0.304349-2.35750.010839
40-0.294544-2.28150.01304
41-0.26221-2.03110.023343
42-0.258107-1.99930.025056
43-0.2368-1.83420.035789
44-0.212664-1.64730.052363
45-0.192383-1.49020.070706
46-0.157652-1.22120.1134
47-0.104042-0.80590.211739
48-0.092552-0.71690.238106
49-0.065327-0.5060.307348
50-0.053675-0.41580.339532
51-0.049475-0.38320.351451
52-0.0371-0.28740.387409
53-0.037889-0.29350.385081
54-0.016312-0.12640.449938
55-0.008796-0.06810.472952
56-0.006033-0.04670.481442
570.000910.00710.497198
580.0004770.00370.498531
59-3.1e-05-2e-040.499904
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8424626.52570
20.275412.13330.018499
3-0.062783-0.48630.314257
4-0.128386-0.99450.161993
50.0855310.66250.255088
6-0.121032-0.93750.176127
7-0.066578-0.51570.303976
8-0.007982-0.06180.475453
9-0.27785-2.15220.017707
100.0097230.07530.470109
110.0976980.75680.226076
12-0.269812-2.090.020434
130.3826252.96380.002176
14-0.004725-0.03660.485463
15-0.058226-0.4510.326801
160.000470.00360.498553
170.2242221.73680.043776
180.1476241.14350.128688
190.0110690.08570.465978
20-0.133416-1.03340.152774
21-0.108865-0.84330.201216
22-0.237719-1.84140.035257
23-0.024595-0.19050.424776
24-0.295802-2.29130.012737
250.1925891.49180.070497
260.0310010.24010.405523
270.0436270.33790.368296
28-0.099387-0.76980.222205
290.0609870.47240.319176
300.0151670.11750.453434
31-0.100921-0.78170.218724
320.0379110.29370.385018
33-0.018235-0.14120.444074
34-0.084049-0.6510.258752
350.020290.15720.437821
36-0.108909-0.84360.20112
37-0.010772-0.08340.46689
38-0.07858-0.60870.272518
390.0781780.60560.273545
40-0.141183-1.09360.13925
410.0748490.57980.282119
42-0.030251-0.23430.407766
430.0642060.49730.310384
44-0.008053-0.06240.475233
450.018270.14150.443966
46-0.042256-0.32730.372286
470.0270820.20980.417277
48-0.018518-0.14340.443212
490.0351960.27260.393037
500.0271450.21030.417086
510.0697160.540.295593
52-0.077527-0.60050.275211
530.0014080.01090.495667
54-0.142441-1.10330.137141
550.0370040.28660.387692
560.0366910.28420.388616
57-0.062652-0.48530.314615
580.0323290.25040.40156
590.0177890.13780.445432
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.842462 & 6.5257 & 0 \tabularnewline
2 & 0.27541 & 2.1333 & 0.018499 \tabularnewline
3 & -0.062783 & -0.4863 & 0.314257 \tabularnewline
4 & -0.128386 & -0.9945 & 0.161993 \tabularnewline
5 & 0.085531 & 0.6625 & 0.255088 \tabularnewline
6 & -0.121032 & -0.9375 & 0.176127 \tabularnewline
7 & -0.066578 & -0.5157 & 0.303976 \tabularnewline
8 & -0.007982 & -0.0618 & 0.475453 \tabularnewline
9 & -0.27785 & -2.1522 & 0.017707 \tabularnewline
10 & 0.009723 & 0.0753 & 0.470109 \tabularnewline
11 & 0.097698 & 0.7568 & 0.226076 \tabularnewline
12 & -0.269812 & -2.09 & 0.020434 \tabularnewline
13 & 0.382625 & 2.9638 & 0.002176 \tabularnewline
14 & -0.004725 & -0.0366 & 0.485463 \tabularnewline
15 & -0.058226 & -0.451 & 0.326801 \tabularnewline
16 & 0.00047 & 0.0036 & 0.498553 \tabularnewline
17 & 0.224222 & 1.7368 & 0.043776 \tabularnewline
18 & 0.147624 & 1.1435 & 0.128688 \tabularnewline
19 & 0.011069 & 0.0857 & 0.465978 \tabularnewline
20 & -0.133416 & -1.0334 & 0.152774 \tabularnewline
21 & -0.108865 & -0.8433 & 0.201216 \tabularnewline
22 & -0.237719 & -1.8414 & 0.035257 \tabularnewline
23 & -0.024595 & -0.1905 & 0.424776 \tabularnewline
24 & -0.295802 & -2.2913 & 0.012737 \tabularnewline
25 & 0.192589 & 1.4918 & 0.070497 \tabularnewline
26 & 0.031001 & 0.2401 & 0.405523 \tabularnewline
27 & 0.043627 & 0.3379 & 0.368296 \tabularnewline
28 & -0.099387 & -0.7698 & 0.222205 \tabularnewline
29 & 0.060987 & 0.4724 & 0.319176 \tabularnewline
30 & 0.015167 & 0.1175 & 0.453434 \tabularnewline
31 & -0.100921 & -0.7817 & 0.218724 \tabularnewline
32 & 0.037911 & 0.2937 & 0.385018 \tabularnewline
33 & -0.018235 & -0.1412 & 0.444074 \tabularnewline
34 & -0.084049 & -0.651 & 0.258752 \tabularnewline
35 & 0.02029 & 0.1572 & 0.437821 \tabularnewline
36 & -0.108909 & -0.8436 & 0.20112 \tabularnewline
37 & -0.010772 & -0.0834 & 0.46689 \tabularnewline
38 & -0.07858 & -0.6087 & 0.272518 \tabularnewline
39 & 0.078178 & 0.6056 & 0.273545 \tabularnewline
40 & -0.141183 & -1.0936 & 0.13925 \tabularnewline
41 & 0.074849 & 0.5798 & 0.282119 \tabularnewline
42 & -0.030251 & -0.2343 & 0.407766 \tabularnewline
43 & 0.064206 & 0.4973 & 0.310384 \tabularnewline
44 & -0.008053 & -0.0624 & 0.475233 \tabularnewline
45 & 0.01827 & 0.1415 & 0.443966 \tabularnewline
46 & -0.042256 & -0.3273 & 0.372286 \tabularnewline
47 & 0.027082 & 0.2098 & 0.417277 \tabularnewline
48 & -0.018518 & -0.1434 & 0.443212 \tabularnewline
49 & 0.035196 & 0.2726 & 0.393037 \tabularnewline
50 & 0.027145 & 0.2103 & 0.417086 \tabularnewline
51 & 0.069716 & 0.54 & 0.295593 \tabularnewline
52 & -0.077527 & -0.6005 & 0.275211 \tabularnewline
53 & 0.001408 & 0.0109 & 0.495667 \tabularnewline
54 & -0.142441 & -1.1033 & 0.137141 \tabularnewline
55 & 0.037004 & 0.2866 & 0.387692 \tabularnewline
56 & 0.036691 & 0.2842 & 0.388616 \tabularnewline
57 & -0.062652 & -0.4853 & 0.314615 \tabularnewline
58 & 0.032329 & 0.2504 & 0.40156 \tabularnewline
59 & 0.017789 & 0.1378 & 0.445432 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77932&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]0.842462[/C][C]6.5257[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.27541[/C][C]2.1333[/C][C]0.018499[/C][/ROW]
[ROW][C]3[/C][C]-0.062783[/C][C]-0.4863[/C][C]0.314257[/C][/ROW]
[ROW][C]4[/C][C]-0.128386[/C][C]-0.9945[/C][C]0.161993[/C][/ROW]
[ROW][C]5[/C][C]0.085531[/C][C]0.6625[/C][C]0.255088[/C][/ROW]
[ROW][C]6[/C][C]-0.121032[/C][C]-0.9375[/C][C]0.176127[/C][/ROW]
[ROW][C]7[/C][C]-0.066578[/C][C]-0.5157[/C][C]0.303976[/C][/ROW]
[ROW][C]8[/C][C]-0.007982[/C][C]-0.0618[/C][C]0.475453[/C][/ROW]
[ROW][C]9[/C][C]-0.27785[/C][C]-2.1522[/C][C]0.017707[/C][/ROW]
[ROW][C]10[/C][C]0.009723[/C][C]0.0753[/C][C]0.470109[/C][/ROW]
[ROW][C]11[/C][C]0.097698[/C][C]0.7568[/C][C]0.226076[/C][/ROW]
[ROW][C]12[/C][C]-0.269812[/C][C]-2.09[/C][C]0.020434[/C][/ROW]
[ROW][C]13[/C][C]0.382625[/C][C]2.9638[/C][C]0.002176[/C][/ROW]
[ROW][C]14[/C][C]-0.004725[/C][C]-0.0366[/C][C]0.485463[/C][/ROW]
[ROW][C]15[/C][C]-0.058226[/C][C]-0.451[/C][C]0.326801[/C][/ROW]
[ROW][C]16[/C][C]0.00047[/C][C]0.0036[/C][C]0.498553[/C][/ROW]
[ROW][C]17[/C][C]0.224222[/C][C]1.7368[/C][C]0.043776[/C][/ROW]
[ROW][C]18[/C][C]0.147624[/C][C]1.1435[/C][C]0.128688[/C][/ROW]
[ROW][C]19[/C][C]0.011069[/C][C]0.0857[/C][C]0.465978[/C][/ROW]
[ROW][C]20[/C][C]-0.133416[/C][C]-1.0334[/C][C]0.152774[/C][/ROW]
[ROW][C]21[/C][C]-0.108865[/C][C]-0.8433[/C][C]0.201216[/C][/ROW]
[ROW][C]22[/C][C]-0.237719[/C][C]-1.8414[/C][C]0.035257[/C][/ROW]
[ROW][C]23[/C][C]-0.024595[/C][C]-0.1905[/C][C]0.424776[/C][/ROW]
[ROW][C]24[/C][C]-0.295802[/C][C]-2.2913[/C][C]0.012737[/C][/ROW]
[ROW][C]25[/C][C]0.192589[/C][C]1.4918[/C][C]0.070497[/C][/ROW]
[ROW][C]26[/C][C]0.031001[/C][C]0.2401[/C][C]0.405523[/C][/ROW]
[ROW][C]27[/C][C]0.043627[/C][C]0.3379[/C][C]0.368296[/C][/ROW]
[ROW][C]28[/C][C]-0.099387[/C][C]-0.7698[/C][C]0.222205[/C][/ROW]
[ROW][C]29[/C][C]0.060987[/C][C]0.4724[/C][C]0.319176[/C][/ROW]
[ROW][C]30[/C][C]0.015167[/C][C]0.1175[/C][C]0.453434[/C][/ROW]
[ROW][C]31[/C][C]-0.100921[/C][C]-0.7817[/C][C]0.218724[/C][/ROW]
[ROW][C]32[/C][C]0.037911[/C][C]0.2937[/C][C]0.385018[/C][/ROW]
[ROW][C]33[/C][C]-0.018235[/C][C]-0.1412[/C][C]0.444074[/C][/ROW]
[ROW][C]34[/C][C]-0.084049[/C][C]-0.651[/C][C]0.258752[/C][/ROW]
[ROW][C]35[/C][C]0.02029[/C][C]0.1572[/C][C]0.437821[/C][/ROW]
[ROW][C]36[/C][C]-0.108909[/C][C]-0.8436[/C][C]0.20112[/C][/ROW]
[ROW][C]37[/C][C]-0.010772[/C][C]-0.0834[/C][C]0.46689[/C][/ROW]
[ROW][C]38[/C][C]-0.07858[/C][C]-0.6087[/C][C]0.272518[/C][/ROW]
[ROW][C]39[/C][C]0.078178[/C][C]0.6056[/C][C]0.273545[/C][/ROW]
[ROW][C]40[/C][C]-0.141183[/C][C]-1.0936[/C][C]0.13925[/C][/ROW]
[ROW][C]41[/C][C]0.074849[/C][C]0.5798[/C][C]0.282119[/C][/ROW]
[ROW][C]42[/C][C]-0.030251[/C][C]-0.2343[/C][C]0.407766[/C][/ROW]
[ROW][C]43[/C][C]0.064206[/C][C]0.4973[/C][C]0.310384[/C][/ROW]
[ROW][C]44[/C][C]-0.008053[/C][C]-0.0624[/C][C]0.475233[/C][/ROW]
[ROW][C]45[/C][C]0.01827[/C][C]0.1415[/C][C]0.443966[/C][/ROW]
[ROW][C]46[/C][C]-0.042256[/C][C]-0.3273[/C][C]0.372286[/C][/ROW]
[ROW][C]47[/C][C]0.027082[/C][C]0.2098[/C][C]0.417277[/C][/ROW]
[ROW][C]48[/C][C]-0.018518[/C][C]-0.1434[/C][C]0.443212[/C][/ROW]
[ROW][C]49[/C][C]0.035196[/C][C]0.2726[/C][C]0.393037[/C][/ROW]
[ROW][C]50[/C][C]0.027145[/C][C]0.2103[/C][C]0.417086[/C][/ROW]
[ROW][C]51[/C][C]0.069716[/C][C]0.54[/C][C]0.295593[/C][/ROW]
[ROW][C]52[/C][C]-0.077527[/C][C]-0.6005[/C][C]0.275211[/C][/ROW]
[ROW][C]53[/C][C]0.001408[/C][C]0.0109[/C][C]0.495667[/C][/ROW]
[ROW][C]54[/C][C]-0.142441[/C][C]-1.1033[/C][C]0.137141[/C][/ROW]
[ROW][C]55[/C][C]0.037004[/C][C]0.2866[/C][C]0.387692[/C][/ROW]
[ROW][C]56[/C][C]0.036691[/C][C]0.2842[/C][C]0.388616[/C][/ROW]
[ROW][C]57[/C][C]-0.062652[/C][C]-0.4853[/C][C]0.314615[/C][/ROW]
[ROW][C]58[/C][C]0.032329[/C][C]0.2504[/C][C]0.40156[/C][/ROW]
[ROW][C]59[/C][C]0.017789[/C][C]0.1378[/C][C]0.445432[/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=77932&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77932&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
10.8424626.52570
20.275412.13330.018499
3-0.062783-0.48630.314257
4-0.128386-0.99450.161993
50.0855310.66250.255088
6-0.121032-0.93750.176127
7-0.066578-0.51570.303976
8-0.007982-0.06180.475453
9-0.27785-2.15220.017707
100.0097230.07530.470109
110.0976980.75680.226076
12-0.269812-2.090.020434
130.3826252.96380.002176
14-0.004725-0.03660.485463
15-0.058226-0.4510.326801
160.000470.00360.498553
170.2242221.73680.043776
180.1476241.14350.128688
190.0110690.08570.465978
20-0.133416-1.03340.152774
21-0.108865-0.84330.201216
22-0.237719-1.84140.035257
23-0.024595-0.19050.424776
24-0.295802-2.29130.012737
250.1925891.49180.070497
260.0310010.24010.405523
270.0436270.33790.368296
28-0.099387-0.76980.222205
290.0609870.47240.319176
300.0151670.11750.453434
31-0.100921-0.78170.218724
320.0379110.29370.385018
33-0.018235-0.14120.444074
34-0.084049-0.6510.258752
350.020290.15720.437821
36-0.108909-0.84360.20112
37-0.010772-0.08340.46689
38-0.07858-0.60870.272518
390.0781780.60560.273545
40-0.141183-1.09360.13925
410.0748490.57980.282119
42-0.030251-0.23430.407766
430.0642060.49730.310384
44-0.008053-0.06240.475233
450.018270.14150.443966
46-0.042256-0.32730.372286
470.0270820.20980.417277
48-0.018518-0.14340.443212
490.0351960.27260.393037
500.0271450.21030.417086
510.0697160.540.295593
52-0.077527-0.60050.275211
530.0014080.01090.495667
54-0.142441-1.10330.137141
550.0370040.28660.387692
560.0366910.28420.388616
57-0.062652-0.48530.314615
580.0323290.25040.40156
590.0177890.13780.445432
60NANANA



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 2 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')