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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 computationTue, 24 Nov 2009 13:22:15 -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/2009/Nov/24/t1259094323ziikq7vlt5djrp7.htm/, Retrieved Sat, 25 May 2024 04:57:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59264, Retrieved Sat, 25 May 2024 04:57:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact228
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [ws8_2] [2009-11-24 20:22:15] [f0f26816ac6124f58333f11f6c174000] [Current]
-   P             [(Partial) Autocorrelation Function] [WS8_seizonaliteit1] [2009-11-25 17:44:58] [8b1aef4e7013bd33fbc2a5833375c5f5]
-                   [(Partial) Autocorrelation Function] [] [2009-11-27 09:53:19] [08fc5c07292c885b941f0cb515ce13f3]
-                   [(Partial) Autocorrelation Function] [review WS 8 autoc...] [2009-11-30 20:25:55] [12f02da0296cb21dc23d82ae014a8b71]
-                   [(Partial) Autocorrelation Function] [] [2009-12-04 14:22:11] [08fc5c07292c885b941f0cb515ce13f3]
-    D              [(Partial) Autocorrelation Function] [paper timeserie A...] [2010-12-06 19:55:19] [814f53995537cd15c528d8efbf1cf544]
-    D              [(Partial) Autocorrelation Function] [paper timeserie A...] [2010-12-06 20:13:10] [814f53995537cd15c528d8efbf1cf544]
- R  D                [(Partial) Autocorrelation Function] [] [2011-12-10 12:56:10] [74be16979710d4c4e7c6647856088456]
-   PD                  [(Partial) Autocorrelation Function] [] [2011-12-10 14:47:02] [46896e8a404bb9354f2d070359621409]
-    D              [(Partial) Autocorrelation Function] [paper timeserie A...] [2010-12-07 09:43:11] [814f53995537cd15c528d8efbf1cf544]
-    D            [(Partial) Autocorrelation Function] [SHw WS8] [2009-11-25 19:05:23] [af2352cd9a951bedd08ebe247d0de1a2]
-   PD            [(Partial) Autocorrelation Function] [SHw WS8] [2009-11-25 19:14:01] [af2352cd9a951bedd08ebe247d0de1a2]
-   PD              [(Partial) Autocorrelation Function] [WS10] [2009-12-09 17:37:39] [af2352cd9a951bedd08ebe247d0de1a2]
-                 [(Partial) Autocorrelation Function] [] [2009-11-27 09:51:49] [08fc5c07292c885b941f0cb515ce13f3]
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Dataseries X:
153.3
154.5
155.2
156.9
157
157.4
157.2
157.5
158
158.5
159
159.3
160
160.8
161.9
162.5
162.7
162.8
162.9
163
164
164.7
164.8
164.9
165
165.8
166.1
167.2
167.7
168.3
168.6
168.9
169.1
169.5
169.6
169.7
169.8
170.4
170.9
171.9
171.9
172
172
172.4
173
173.7
173.8
173.8
173.9
174.6
175
175.9
176
175.1
175.6
175.9
176.7
176.1
176.1
176.2
176.3
177.8
178.5
179.4
179.5
179.6
179.7
179.7
179.8
179.9
180.2
180.4
180.4
181.3
181.9
182.5
182.7
183.1
183.6
183.7
183.8
183.9
184.1
184.4
184.5
185.9
186.6
187.6
187.8
187.9
188
188.3
188.4
188.5
188.5
188.6
188.6
189.4
190
191.9
192.5
193
193.5
193.9
194.2
194.9
194.9
194.9
194.9
195.5
196
196.2
196.2
196.2
196.2
197
197.7
198
198.2
198.5
198.6
199.5
200
201.3
202.2
202.9
203.5
203.5
204
204.1
204.3
204.5
204.8
205.1
205.7
206.5
206.9
207.1
207.8
208
208.5
208.6
209
209.1
209.7
209.8
209.9
210
210.8
211.4
211.7
212
212.2
212.4
212.9
213.4
213.7
214
214.3
214.8
215
215.9
216.4
216.9
217.2
217.5
217.9
218.1
218.6
218.9
219.3
220.4
220.9
221
221.8
222
222.2
222.5
222.9
223.1
223.4
224
225.1
225.5
225.9
226.3
226.5
227
227.3
227.8
228.1
228.4
228.5
228.8
229
229.1
229.3
229.6
229.9
230
230.2
230.8
231
231.7
231.9
233
235.1
236
236.9
237.1
237.5
238.2
238.9
239.1
240
240.2
240.5
240.7
241.1
241.4
242.2
242.9
243.2
243.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59264&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59264&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59264&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2179743.2550.000655
20.154272.30370.011079
3-0.183082-2.7340.00338
4-0.123895-1.85020.032807
5-0.020947-0.31280.377363
60.0073690.110.45624
7-0.025383-0.37910.352504
8-0.165948-2.47810.006975
9-0.18068-2.69810.003753
100.0008670.01290.494843
110.0694511.03710.150401
120.2333453.48460.000297
130.0814831.21680.112482
140.0169010.25240.400487
15-0.091955-1.37320.085538
16-0.050379-0.75230.226324
170.0797631.19110.117437
180.0015950.02380.490509
190.0029840.04460.482252
20-0.140768-2.10210.018333
21-0.173335-2.58840.005137
220.0272720.40730.342104
230.1014551.5150.065589
240.3272334.88661e-06
250.1170611.74810.040912
260.0660230.98590.162615
27-0.08161-1.21870.112125
28-0.159758-2.38570.008941
29-0.02412-0.36020.359522
30-0.065371-0.97620.165011
31-0.047762-0.71320.238223
32-0.146587-2.1890.014817
33-0.1538-2.29670.011281
340.0415970.62120.267557
350.0634570.94760.172176
360.2794494.17312.2e-05

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.217974 & 3.255 & 0.000655 \tabularnewline
2 & 0.15427 & 2.3037 & 0.011079 \tabularnewline
3 & -0.183082 & -2.734 & 0.00338 \tabularnewline
4 & -0.123895 & -1.8502 & 0.032807 \tabularnewline
5 & -0.020947 & -0.3128 & 0.377363 \tabularnewline
6 & 0.007369 & 0.11 & 0.45624 \tabularnewline
7 & -0.025383 & -0.3791 & 0.352504 \tabularnewline
8 & -0.165948 & -2.4781 & 0.006975 \tabularnewline
9 & -0.18068 & -2.6981 & 0.003753 \tabularnewline
10 & 0.000867 & 0.0129 & 0.494843 \tabularnewline
11 & 0.069451 & 1.0371 & 0.150401 \tabularnewline
12 & 0.233345 & 3.4846 & 0.000297 \tabularnewline
13 & 0.081483 & 1.2168 & 0.112482 \tabularnewline
14 & 0.016901 & 0.2524 & 0.400487 \tabularnewline
15 & -0.091955 & -1.3732 & 0.085538 \tabularnewline
16 & -0.050379 & -0.7523 & 0.226324 \tabularnewline
17 & 0.079763 & 1.1911 & 0.117437 \tabularnewline
18 & 0.001595 & 0.0238 & 0.490509 \tabularnewline
19 & 0.002984 & 0.0446 & 0.482252 \tabularnewline
20 & -0.140768 & -2.1021 & 0.018333 \tabularnewline
21 & -0.173335 & -2.5884 & 0.005137 \tabularnewline
22 & 0.027272 & 0.4073 & 0.342104 \tabularnewline
23 & 0.101455 & 1.515 & 0.065589 \tabularnewline
24 & 0.327233 & 4.8866 & 1e-06 \tabularnewline
25 & 0.117061 & 1.7481 & 0.040912 \tabularnewline
26 & 0.066023 & 0.9859 & 0.162615 \tabularnewline
27 & -0.08161 & -1.2187 & 0.112125 \tabularnewline
28 & -0.159758 & -2.3857 & 0.008941 \tabularnewline
29 & -0.02412 & -0.3602 & 0.359522 \tabularnewline
30 & -0.065371 & -0.9762 & 0.165011 \tabularnewline
31 & -0.047762 & -0.7132 & 0.238223 \tabularnewline
32 & -0.146587 & -2.189 & 0.014817 \tabularnewline
33 & -0.1538 & -2.2967 & 0.011281 \tabularnewline
34 & 0.041597 & 0.6212 & 0.267557 \tabularnewline
35 & 0.063457 & 0.9476 & 0.172176 \tabularnewline
36 & 0.279449 & 4.1731 & 2.2e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59264&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]0.217974[/C][C]3.255[/C][C]0.000655[/C][/ROW]
[ROW][C]2[/C][C]0.15427[/C][C]2.3037[/C][C]0.011079[/C][/ROW]
[ROW][C]3[/C][C]-0.183082[/C][C]-2.734[/C][C]0.00338[/C][/ROW]
[ROW][C]4[/C][C]-0.123895[/C][C]-1.8502[/C][C]0.032807[/C][/ROW]
[ROW][C]5[/C][C]-0.020947[/C][C]-0.3128[/C][C]0.377363[/C][/ROW]
[ROW][C]6[/C][C]0.007369[/C][C]0.11[/C][C]0.45624[/C][/ROW]
[ROW][C]7[/C][C]-0.025383[/C][C]-0.3791[/C][C]0.352504[/C][/ROW]
[ROW][C]8[/C][C]-0.165948[/C][C]-2.4781[/C][C]0.006975[/C][/ROW]
[ROW][C]9[/C][C]-0.18068[/C][C]-2.6981[/C][C]0.003753[/C][/ROW]
[ROW][C]10[/C][C]0.000867[/C][C]0.0129[/C][C]0.494843[/C][/ROW]
[ROW][C]11[/C][C]0.069451[/C][C]1.0371[/C][C]0.150401[/C][/ROW]
[ROW][C]12[/C][C]0.233345[/C][C]3.4846[/C][C]0.000297[/C][/ROW]
[ROW][C]13[/C][C]0.081483[/C][C]1.2168[/C][C]0.112482[/C][/ROW]
[ROW][C]14[/C][C]0.016901[/C][C]0.2524[/C][C]0.400487[/C][/ROW]
[ROW][C]15[/C][C]-0.091955[/C][C]-1.3732[/C][C]0.085538[/C][/ROW]
[ROW][C]16[/C][C]-0.050379[/C][C]-0.7523[/C][C]0.226324[/C][/ROW]
[ROW][C]17[/C][C]0.079763[/C][C]1.1911[/C][C]0.117437[/C][/ROW]
[ROW][C]18[/C][C]0.001595[/C][C]0.0238[/C][C]0.490509[/C][/ROW]
[ROW][C]19[/C][C]0.002984[/C][C]0.0446[/C][C]0.482252[/C][/ROW]
[ROW][C]20[/C][C]-0.140768[/C][C]-2.1021[/C][C]0.018333[/C][/ROW]
[ROW][C]21[/C][C]-0.173335[/C][C]-2.5884[/C][C]0.005137[/C][/ROW]
[ROW][C]22[/C][C]0.027272[/C][C]0.4073[/C][C]0.342104[/C][/ROW]
[ROW][C]23[/C][C]0.101455[/C][C]1.515[/C][C]0.065589[/C][/ROW]
[ROW][C]24[/C][C]0.327233[/C][C]4.8866[/C][C]1e-06[/C][/ROW]
[ROW][C]25[/C][C]0.117061[/C][C]1.7481[/C][C]0.040912[/C][/ROW]
[ROW][C]26[/C][C]0.066023[/C][C]0.9859[/C][C]0.162615[/C][/ROW]
[ROW][C]27[/C][C]-0.08161[/C][C]-1.2187[/C][C]0.112125[/C][/ROW]
[ROW][C]28[/C][C]-0.159758[/C][C]-2.3857[/C][C]0.008941[/C][/ROW]
[ROW][C]29[/C][C]-0.02412[/C][C]-0.3602[/C][C]0.359522[/C][/ROW]
[ROW][C]30[/C][C]-0.065371[/C][C]-0.9762[/C][C]0.165011[/C][/ROW]
[ROW][C]31[/C][C]-0.047762[/C][C]-0.7132[/C][C]0.238223[/C][/ROW]
[ROW][C]32[/C][C]-0.146587[/C][C]-2.189[/C][C]0.014817[/C][/ROW]
[ROW][C]33[/C][C]-0.1538[/C][C]-2.2967[/C][C]0.011281[/C][/ROW]
[ROW][C]34[/C][C]0.041597[/C][C]0.6212[/C][C]0.267557[/C][/ROW]
[ROW][C]35[/C][C]0.063457[/C][C]0.9476[/C][C]0.172176[/C][/ROW]
[ROW][C]36[/C][C]0.279449[/C][C]4.1731[/C][C]2.2e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59264&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59264&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
10.2179743.2550.000655
20.154272.30370.011079
3-0.183082-2.7340.00338
4-0.123895-1.85020.032807
5-0.020947-0.31280.377363
60.0073690.110.45624
7-0.025383-0.37910.352504
8-0.165948-2.47810.006975
9-0.18068-2.69810.003753
100.0008670.01290.494843
110.0694511.03710.150401
120.2333453.48460.000297
130.0814831.21680.112482
140.0169010.25240.400487
15-0.091955-1.37320.085538
16-0.050379-0.75230.226324
170.0797631.19110.117437
180.0015950.02380.490509
190.0029840.04460.482252
20-0.140768-2.10210.018333
21-0.173335-2.58840.005137
220.0272720.40730.342104
230.1014551.5150.065589
240.3272334.88661e-06
250.1170611.74810.040912
260.0660230.98590.162615
27-0.08161-1.21870.112125
28-0.159758-2.38570.008941
29-0.02412-0.36020.359522
30-0.065371-0.97620.165011
31-0.047762-0.71320.238223
32-0.146587-2.1890.014817
33-0.1538-2.29670.011281
340.0415970.62120.267557
350.0634570.94760.172176
360.2794494.17312.2e-05







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2179743.2550.000655
20.1120821.67370.047791
3-0.252382-3.76890.000105
4-0.060295-0.90040.184442
50.0979081.46210.072564
6-0.022872-0.34150.366506
7-0.092275-1.3780.084799
8-0.159591-2.38320.009001
9-0.100792-1.50520.06685
100.1192931.78140.038103
110.0324750.4850.31409
120.1137271.69830.045422
13-0.010188-0.15210.43961
14-0.027149-0.40540.34278
15-0.032105-0.47940.316052
16-0.008863-0.13240.44741
170.0869261.29810.097801
18-0.063495-0.94820.172032
19-0.017824-0.26620.395177
20-0.049429-0.73810.230604
21-0.094801-1.41570.079132
220.1164261.73860.041742
230.070451.0520.146959
240.1976052.95090.001754
250.0091840.13720.445518
260.0061810.09230.463273
27-0.01057-0.15790.437359
28-0.152927-2.28370.011666
29-0.016252-0.24270.404234
30-0.03292-0.49160.311744
31-0.035839-0.53520.296527
32-0.030615-0.45720.323994
33-0.039199-0.58540.279448
340.1009851.5080.066481
35-0.001947-0.02910.488416
360.1023171.52790.063974

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.217974 & 3.255 & 0.000655 \tabularnewline
2 & 0.112082 & 1.6737 & 0.047791 \tabularnewline
3 & -0.252382 & -3.7689 & 0.000105 \tabularnewline
4 & -0.060295 & -0.9004 & 0.184442 \tabularnewline
5 & 0.097908 & 1.4621 & 0.072564 \tabularnewline
6 & -0.022872 & -0.3415 & 0.366506 \tabularnewline
7 & -0.092275 & -1.378 & 0.084799 \tabularnewline
8 & -0.159591 & -2.3832 & 0.009001 \tabularnewline
9 & -0.100792 & -1.5052 & 0.06685 \tabularnewline
10 & 0.119293 & 1.7814 & 0.038103 \tabularnewline
11 & 0.032475 & 0.485 & 0.31409 \tabularnewline
12 & 0.113727 & 1.6983 & 0.045422 \tabularnewline
13 & -0.010188 & -0.1521 & 0.43961 \tabularnewline
14 & -0.027149 & -0.4054 & 0.34278 \tabularnewline
15 & -0.032105 & -0.4794 & 0.316052 \tabularnewline
16 & -0.008863 & -0.1324 & 0.44741 \tabularnewline
17 & 0.086926 & 1.2981 & 0.097801 \tabularnewline
18 & -0.063495 & -0.9482 & 0.172032 \tabularnewline
19 & -0.017824 & -0.2662 & 0.395177 \tabularnewline
20 & -0.049429 & -0.7381 & 0.230604 \tabularnewline
21 & -0.094801 & -1.4157 & 0.079132 \tabularnewline
22 & 0.116426 & 1.7386 & 0.041742 \tabularnewline
23 & 0.07045 & 1.052 & 0.146959 \tabularnewline
24 & 0.197605 & 2.9509 & 0.001754 \tabularnewline
25 & 0.009184 & 0.1372 & 0.445518 \tabularnewline
26 & 0.006181 & 0.0923 & 0.463273 \tabularnewline
27 & -0.01057 & -0.1579 & 0.437359 \tabularnewline
28 & -0.152927 & -2.2837 & 0.011666 \tabularnewline
29 & -0.016252 & -0.2427 & 0.404234 \tabularnewline
30 & -0.03292 & -0.4916 & 0.311744 \tabularnewline
31 & -0.035839 & -0.5352 & 0.296527 \tabularnewline
32 & -0.030615 & -0.4572 & 0.323994 \tabularnewline
33 & -0.039199 & -0.5854 & 0.279448 \tabularnewline
34 & 0.100985 & 1.508 & 0.066481 \tabularnewline
35 & -0.001947 & -0.0291 & 0.488416 \tabularnewline
36 & 0.102317 & 1.5279 & 0.063974 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59264&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]0.217974[/C][C]3.255[/C][C]0.000655[/C][/ROW]
[ROW][C]2[/C][C]0.112082[/C][C]1.6737[/C][C]0.047791[/C][/ROW]
[ROW][C]3[/C][C]-0.252382[/C][C]-3.7689[/C][C]0.000105[/C][/ROW]
[ROW][C]4[/C][C]-0.060295[/C][C]-0.9004[/C][C]0.184442[/C][/ROW]
[ROW][C]5[/C][C]0.097908[/C][C]1.4621[/C][C]0.072564[/C][/ROW]
[ROW][C]6[/C][C]-0.022872[/C][C]-0.3415[/C][C]0.366506[/C][/ROW]
[ROW][C]7[/C][C]-0.092275[/C][C]-1.378[/C][C]0.084799[/C][/ROW]
[ROW][C]8[/C][C]-0.159591[/C][C]-2.3832[/C][C]0.009001[/C][/ROW]
[ROW][C]9[/C][C]-0.100792[/C][C]-1.5052[/C][C]0.06685[/C][/ROW]
[ROW][C]10[/C][C]0.119293[/C][C]1.7814[/C][C]0.038103[/C][/ROW]
[ROW][C]11[/C][C]0.032475[/C][C]0.485[/C][C]0.31409[/C][/ROW]
[ROW][C]12[/C][C]0.113727[/C][C]1.6983[/C][C]0.045422[/C][/ROW]
[ROW][C]13[/C][C]-0.010188[/C][C]-0.1521[/C][C]0.43961[/C][/ROW]
[ROW][C]14[/C][C]-0.027149[/C][C]-0.4054[/C][C]0.34278[/C][/ROW]
[ROW][C]15[/C][C]-0.032105[/C][C]-0.4794[/C][C]0.316052[/C][/ROW]
[ROW][C]16[/C][C]-0.008863[/C][C]-0.1324[/C][C]0.44741[/C][/ROW]
[ROW][C]17[/C][C]0.086926[/C][C]1.2981[/C][C]0.097801[/C][/ROW]
[ROW][C]18[/C][C]-0.063495[/C][C]-0.9482[/C][C]0.172032[/C][/ROW]
[ROW][C]19[/C][C]-0.017824[/C][C]-0.2662[/C][C]0.395177[/C][/ROW]
[ROW][C]20[/C][C]-0.049429[/C][C]-0.7381[/C][C]0.230604[/C][/ROW]
[ROW][C]21[/C][C]-0.094801[/C][C]-1.4157[/C][C]0.079132[/C][/ROW]
[ROW][C]22[/C][C]0.116426[/C][C]1.7386[/C][C]0.041742[/C][/ROW]
[ROW][C]23[/C][C]0.07045[/C][C]1.052[/C][C]0.146959[/C][/ROW]
[ROW][C]24[/C][C]0.197605[/C][C]2.9509[/C][C]0.001754[/C][/ROW]
[ROW][C]25[/C][C]0.009184[/C][C]0.1372[/C][C]0.445518[/C][/ROW]
[ROW][C]26[/C][C]0.006181[/C][C]0.0923[/C][C]0.463273[/C][/ROW]
[ROW][C]27[/C][C]-0.01057[/C][C]-0.1579[/C][C]0.437359[/C][/ROW]
[ROW][C]28[/C][C]-0.152927[/C][C]-2.2837[/C][C]0.011666[/C][/ROW]
[ROW][C]29[/C][C]-0.016252[/C][C]-0.2427[/C][C]0.404234[/C][/ROW]
[ROW][C]30[/C][C]-0.03292[/C][C]-0.4916[/C][C]0.311744[/C][/ROW]
[ROW][C]31[/C][C]-0.035839[/C][C]-0.5352[/C][C]0.296527[/C][/ROW]
[ROW][C]32[/C][C]-0.030615[/C][C]-0.4572[/C][C]0.323994[/C][/ROW]
[ROW][C]33[/C][C]-0.039199[/C][C]-0.5854[/C][C]0.279448[/C][/ROW]
[ROW][C]34[/C][C]0.100985[/C][C]1.508[/C][C]0.066481[/C][/ROW]
[ROW][C]35[/C][C]-0.001947[/C][C]-0.0291[/C][C]0.488416[/C][/ROW]
[ROW][C]36[/C][C]0.102317[/C][C]1.5279[/C][C]0.063974[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59264&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59264&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
10.2179743.2550.000655
20.1120821.67370.047791
3-0.252382-3.76890.000105
4-0.060295-0.90040.184442
50.0979081.46210.072564
6-0.022872-0.34150.366506
7-0.092275-1.3780.084799
8-0.159591-2.38320.009001
9-0.100792-1.50520.06685
100.1192931.78140.038103
110.0324750.4850.31409
120.1137271.69830.045422
13-0.010188-0.15210.43961
14-0.027149-0.40540.34278
15-0.032105-0.47940.316052
16-0.008863-0.13240.44741
170.0869261.29810.097801
18-0.063495-0.94820.172032
19-0.017824-0.26620.395177
20-0.049429-0.73810.230604
21-0.094801-1.41570.079132
220.1164261.73860.041742
230.070451.0520.146959
240.1976052.95090.001754
250.0091840.13720.445518
260.0061810.09230.463273
27-0.01057-0.15790.437359
28-0.152927-2.28370.011666
29-0.016252-0.24270.404234
30-0.03292-0.49160.311744
31-0.035839-0.53520.296527
32-0.030615-0.45720.323994
33-0.039199-0.58540.279448
340.1009851.5080.066481
35-0.001947-0.02910.488416
360.1023171.52790.063974



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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')