FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 08 Dec 2008 13:21:14 -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/08/t1228767747i82kwg8u5nrvzke.htm/, Retrieved Tue, 14 May 2024 05:27:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30944, Retrieved Tue, 14 May 2024 05:27:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [opgave 6bis- oefe...] [2008-12-08 20:21:14] [59eb7d50a05a673a4523845c066501a9] [Current]
-    D    [(Partial) Autocorrelation Function] [Kristof Nollekens...] [2009-05-14 13:55:26] [74be16979710d4c4e7c6647856088456]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,6
101,8
102,1
102,1
101,9
102,1
102
102,1
102,2
102,3
102,7
102,8
103,1
103,1
103,3
103,5
103,3
103,5
103,8
103,9
103,9
104,2
104,6
104,9
105,2
105,2
105,6
105,6
106,2
106,3
106,4
106,9
107,2
107,3
107,3
107,4
107,55
107,87
108,37
108,38
107,92
108,03
108,14
108,3
108,64
108,66
109,04
109,03
109,03
109,54
109,75
109,83
109,65
109,82
109,95
110,12
110,15
110,2
109,99
110,14
110,14
110,81
110,97
110,99
109,73
109,81
110,02
110,18
110,21
110,25
110,36
110,51
110,64
110,95
111,18
111,19
111,69
111,7
111,83
111,77
111,73
112,01
111,86
112,04

Tables (Output of Computation)





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=30944&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=30944&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30944&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9663468.85670
20.933488.55550
30.9006898.2550
40.869057.9650
50.8344367.64770
60.7987137.32030
70.7611656.97620
80.7224546.62140
90.6855456.28310
100.6488025.94640
110.6144015.63110
120.5805945.32120
130.547845.0211e-06
140.5141654.71245e-06
150.4816174.41411.5e-05
160.4495544.12024.4e-05
170.4147033.80080.000136
180.3806713.48890.000387
190.3483293.19250.000993
200.316192.89790.002395
210.276752.53650.006524
220.2383832.18480.015844
230.2024171.85520.033539
240.1700711.55870.061411
250.1376021.26110.105375
260.1047810.96030.169822
270.0730870.66990.252395
280.0406520.37260.355198
290.0113040.10360.458866
30-0.017614-0.16140.436069
31-0.046286-0.42420.336245
32-0.071746-0.65760.256308
33-0.096852-0.88770.188627
34-0.121075-1.10970.135154
35-0.144964-1.32860.093786
36-0.166763-1.52840.065085
37-0.187672-1.720.044554
38-0.20763-1.9030.030235
39-0.222769-2.04170.022159
40-0.238988-2.19040.015635
41-0.256922-2.35470.010434
42-0.273622-2.50780.007037
43-0.289359-2.6520.004782
44-0.304016-2.78630.003294
45-0.319828-2.93130.002174
46-0.3362-3.08130.001393
47-0.347829-3.18790.001007
48-0.358424-3.2850.000744

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.966346 & 8.8567 & 0 \tabularnewline
2 & 0.93348 & 8.5555 & 0 \tabularnewline
3 & 0.900689 & 8.255 & 0 \tabularnewline
4 & 0.86905 & 7.965 & 0 \tabularnewline
5 & 0.834436 & 7.6477 & 0 \tabularnewline
6 & 0.798713 & 7.3203 & 0 \tabularnewline
7 & 0.761165 & 6.9762 & 0 \tabularnewline
8 & 0.722454 & 6.6214 & 0 \tabularnewline
9 & 0.685545 & 6.2831 & 0 \tabularnewline
10 & 0.648802 & 5.9464 & 0 \tabularnewline
11 & 0.614401 & 5.6311 & 0 \tabularnewline
12 & 0.580594 & 5.3212 & 0 \tabularnewline
13 & 0.54784 & 5.021 & 1e-06 \tabularnewline
14 & 0.514165 & 4.7124 & 5e-06 \tabularnewline
15 & 0.481617 & 4.4141 & 1.5e-05 \tabularnewline
16 & 0.449554 & 4.1202 & 4.4e-05 \tabularnewline
17 & 0.414703 & 3.8008 & 0.000136 \tabularnewline
18 & 0.380671 & 3.4889 & 0.000387 \tabularnewline
19 & 0.348329 & 3.1925 & 0.000993 \tabularnewline
20 & 0.31619 & 2.8979 & 0.002395 \tabularnewline
21 & 0.27675 & 2.5365 & 0.006524 \tabularnewline
22 & 0.238383 & 2.1848 & 0.015844 \tabularnewline
23 & 0.202417 & 1.8552 & 0.033539 \tabularnewline
24 & 0.170071 & 1.5587 & 0.061411 \tabularnewline
25 & 0.137602 & 1.2611 & 0.105375 \tabularnewline
26 & 0.104781 & 0.9603 & 0.169822 \tabularnewline
27 & 0.073087 & 0.6699 & 0.252395 \tabularnewline
28 & 0.040652 & 0.3726 & 0.355198 \tabularnewline
29 & 0.011304 & 0.1036 & 0.458866 \tabularnewline
30 & -0.017614 & -0.1614 & 0.436069 \tabularnewline
31 & -0.046286 & -0.4242 & 0.336245 \tabularnewline
32 & -0.071746 & -0.6576 & 0.256308 \tabularnewline
33 & -0.096852 & -0.8877 & 0.188627 \tabularnewline
34 & -0.121075 & -1.1097 & 0.135154 \tabularnewline
35 & -0.144964 & -1.3286 & 0.093786 \tabularnewline
36 & -0.166763 & -1.5284 & 0.065085 \tabularnewline
37 & -0.187672 & -1.72 & 0.044554 \tabularnewline
38 & -0.20763 & -1.903 & 0.030235 \tabularnewline
39 & -0.222769 & -2.0417 & 0.022159 \tabularnewline
40 & -0.238988 & -2.1904 & 0.015635 \tabularnewline
41 & -0.256922 & -2.3547 & 0.010434 \tabularnewline
42 & -0.273622 & -2.5078 & 0.007037 \tabularnewline
43 & -0.289359 & -2.652 & 0.004782 \tabularnewline
44 & -0.304016 & -2.7863 & 0.003294 \tabularnewline
45 & -0.319828 & -2.9313 & 0.002174 \tabularnewline
46 & -0.3362 & -3.0813 & 0.001393 \tabularnewline
47 & -0.347829 & -3.1879 & 0.001007 \tabularnewline
48 & -0.358424 & -3.285 & 0.000744 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30944&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]0.966346[/C][C]8.8567[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.93348[/C][C]8.5555[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.900689[/C][C]8.255[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.86905[/C][C]7.965[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.834436[/C][C]7.6477[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.798713[/C][C]7.3203[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.761165[/C][C]6.9762[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.722454[/C][C]6.6214[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.685545[/C][C]6.2831[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.648802[/C][C]5.9464[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.614401[/C][C]5.6311[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.580594[/C][C]5.3212[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.54784[/C][C]5.021[/C][C]1e-06[/C][/ROW]
[ROW][C]14[/C][C]0.514165[/C][C]4.7124[/C][C]5e-06[/C][/ROW]
[ROW][C]15[/C][C]0.481617[/C][C]4.4141[/C][C]1.5e-05[/C][/ROW]
[ROW][C]16[/C][C]0.449554[/C][C]4.1202[/C][C]4.4e-05[/C][/ROW]
[ROW][C]17[/C][C]0.414703[/C][C]3.8008[/C][C]0.000136[/C][/ROW]
[ROW][C]18[/C][C]0.380671[/C][C]3.4889[/C][C]0.000387[/C][/ROW]
[ROW][C]19[/C][C]0.348329[/C][C]3.1925[/C][C]0.000993[/C][/ROW]
[ROW][C]20[/C][C]0.31619[/C][C]2.8979[/C][C]0.002395[/C][/ROW]
[ROW][C]21[/C][C]0.27675[/C][C]2.5365[/C][C]0.006524[/C][/ROW]
[ROW][C]22[/C][C]0.238383[/C][C]2.1848[/C][C]0.015844[/C][/ROW]
[ROW][C]23[/C][C]0.202417[/C][C]1.8552[/C][C]0.033539[/C][/ROW]
[ROW][C]24[/C][C]0.170071[/C][C]1.5587[/C][C]0.061411[/C][/ROW]
[ROW][C]25[/C][C]0.137602[/C][C]1.2611[/C][C]0.105375[/C][/ROW]
[ROW][C]26[/C][C]0.104781[/C][C]0.9603[/C][C]0.169822[/C][/ROW]
[ROW][C]27[/C][C]0.073087[/C][C]0.6699[/C][C]0.252395[/C][/ROW]
[ROW][C]28[/C][C]0.040652[/C][C]0.3726[/C][C]0.355198[/C][/ROW]
[ROW][C]29[/C][C]0.011304[/C][C]0.1036[/C][C]0.458866[/C][/ROW]
[ROW][C]30[/C][C]-0.017614[/C][C]-0.1614[/C][C]0.436069[/C][/ROW]
[ROW][C]31[/C][C]-0.046286[/C][C]-0.4242[/C][C]0.336245[/C][/ROW]
[ROW][C]32[/C][C]-0.071746[/C][C]-0.6576[/C][C]0.256308[/C][/ROW]
[ROW][C]33[/C][C]-0.096852[/C][C]-0.8877[/C][C]0.188627[/C][/ROW]
[ROW][C]34[/C][C]-0.121075[/C][C]-1.1097[/C][C]0.135154[/C][/ROW]
[ROW][C]35[/C][C]-0.144964[/C][C]-1.3286[/C][C]0.093786[/C][/ROW]
[ROW][C]36[/C][C]-0.166763[/C][C]-1.5284[/C][C]0.065085[/C][/ROW]
[ROW][C]37[/C][C]-0.187672[/C][C]-1.72[/C][C]0.044554[/C][/ROW]
[ROW][C]38[/C][C]-0.20763[/C][C]-1.903[/C][C]0.030235[/C][/ROW]
[ROW][C]39[/C][C]-0.222769[/C][C]-2.0417[/C][C]0.022159[/C][/ROW]
[ROW][C]40[/C][C]-0.238988[/C][C]-2.1904[/C][C]0.015635[/C][/ROW]
[ROW][C]41[/C][C]-0.256922[/C][C]-2.3547[/C][C]0.010434[/C][/ROW]
[ROW][C]42[/C][C]-0.273622[/C][C]-2.5078[/C][C]0.007037[/C][/ROW]
[ROW][C]43[/C][C]-0.289359[/C][C]-2.652[/C][C]0.004782[/C][/ROW]
[ROW][C]44[/C][C]-0.304016[/C][C]-2.7863[/C][C]0.003294[/C][/ROW]
[ROW][C]45[/C][C]-0.319828[/C][C]-2.9313[/C][C]0.002174[/C][/ROW]
[ROW][C]46[/C][C]-0.3362[/C][C]-3.0813[/C][C]0.001393[/C][/ROW]
[ROW][C]47[/C][C]-0.347829[/C][C]-3.1879[/C][C]0.001007[/C][/ROW]
[ROW][C]48[/C][C]-0.358424[/C][C]-3.285[/C][C]0.000744[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30944&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30944&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
10.9663468.85670
20.933488.55550
30.9006898.2550
40.869057.9650
50.8344367.64770
60.7987137.32030
70.7611656.97620
80.7224546.62140
90.6855456.28310
100.6488025.94640
110.6144015.63110
120.5805945.32120
130.547845.0211e-06
140.5141654.71245e-06
150.4816174.41411.5e-05
160.4495544.12024.4e-05
170.4147033.80080.000136
180.3806713.48890.000387
190.3483293.19250.000993
200.316192.89790.002395
210.276752.53650.006524
220.2383832.18480.015844
230.2024171.85520.033539
240.1700711.55870.061411
250.1376021.26110.105375
260.1047810.96030.169822
270.0730870.66990.252395
280.0406520.37260.355198
290.0113040.10360.458866
30-0.017614-0.16140.436069
31-0.046286-0.42420.336245
32-0.071746-0.65760.256308
33-0.096852-0.88770.188627
34-0.121075-1.10970.135154
35-0.144964-1.32860.093786
36-0.166763-1.52840.065085
37-0.187672-1.720.044554
38-0.20763-1.9030.030235
39-0.222769-2.04170.022159
40-0.238988-2.19040.015635
41-0.256922-2.35470.010434
42-0.273622-2.50780.007037
43-0.289359-2.6520.004782
44-0.304016-2.78630.003294
45-0.319828-2.93130.002174
46-0.3362-3.08130.001393
47-0.347829-3.18790.001007
48-0.358424-3.2850.000744






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9663468.85670
2-0.005213-0.04780.481005
3-0.015735-0.14420.442839
40.0001870.00170.499318
5-0.061501-0.56370.287242
6-0.036669-0.33610.368825
7-0.047864-0.43870.331009
8-0.041424-0.37970.35258
90.0054670.05010.480078
10-0.018342-0.16810.433452
110.0156540.14350.443132
12-0.007692-0.07050.471983
13-0.005637-0.05170.47946
14-0.033547-0.30750.379625
15-0.009323-0.08540.466055
16-0.017215-0.15780.437505
17-0.068255-0.62560.266647
18-0.014038-0.12870.448968
190.0010320.00950.496236
20-0.021914-0.20080.420654
21-0.130591-1.19690.117359
22-0.01663-0.15240.439612
230.0079650.0730.47099
240.0233110.21360.415669
25-0.021682-0.19870.42148
26-0.030518-0.27970.390198
27-0.008313-0.07620.469726
28-0.043226-0.39620.346492
290.0070360.06450.474367
30-0.023135-0.2120.416297
31-0.036271-0.33240.370196
320.0217310.19920.421307
33-0.023148-0.21220.416249
34-0.010311-0.09450.462466
35-0.027158-0.24890.402021
36-0.003556-0.03260.487037
37-0.00293-0.02690.489321
38-0.018925-0.17350.431357
390.0411510.37720.353504
40-0.044507-0.40790.342187
41-0.040524-0.37140.355633
42-0.008262-0.07570.469911
43-0.02834-0.25970.397849
44-0.018994-0.17410.431111
45-0.049308-0.45190.326247
46-0.032996-0.30240.381543
470.0510370.46780.320584
48-0.010706-0.09810.461036

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.966346 & 8.8567 & 0 \tabularnewline
2 & -0.005213 & -0.0478 & 0.481005 \tabularnewline
3 & -0.015735 & -0.1442 & 0.442839 \tabularnewline
4 & 0.000187 & 0.0017 & 0.499318 \tabularnewline
5 & -0.061501 & -0.5637 & 0.287242 \tabularnewline
6 & -0.036669 & -0.3361 & 0.368825 \tabularnewline
7 & -0.047864 & -0.4387 & 0.331009 \tabularnewline
8 & -0.041424 & -0.3797 & 0.35258 \tabularnewline
9 & 0.005467 & 0.0501 & 0.480078 \tabularnewline
10 & -0.018342 & -0.1681 & 0.433452 \tabularnewline
11 & 0.015654 & 0.1435 & 0.443132 \tabularnewline
12 & -0.007692 & -0.0705 & 0.471983 \tabularnewline
13 & -0.005637 & -0.0517 & 0.47946 \tabularnewline
14 & -0.033547 & -0.3075 & 0.379625 \tabularnewline
15 & -0.009323 & -0.0854 & 0.466055 \tabularnewline
16 & -0.017215 & -0.1578 & 0.437505 \tabularnewline
17 & -0.068255 & -0.6256 & 0.266647 \tabularnewline
18 & -0.014038 & -0.1287 & 0.448968 \tabularnewline
19 & 0.001032 & 0.0095 & 0.496236 \tabularnewline
20 & -0.021914 & -0.2008 & 0.420654 \tabularnewline
21 & -0.130591 & -1.1969 & 0.117359 \tabularnewline
22 & -0.01663 & -0.1524 & 0.439612 \tabularnewline
23 & 0.007965 & 0.073 & 0.47099 \tabularnewline
24 & 0.023311 & 0.2136 & 0.415669 \tabularnewline
25 & -0.021682 & -0.1987 & 0.42148 \tabularnewline
26 & -0.030518 & -0.2797 & 0.390198 \tabularnewline
27 & -0.008313 & -0.0762 & 0.469726 \tabularnewline
28 & -0.043226 & -0.3962 & 0.346492 \tabularnewline
29 & 0.007036 & 0.0645 & 0.474367 \tabularnewline
30 & -0.023135 & -0.212 & 0.416297 \tabularnewline
31 & -0.036271 & -0.3324 & 0.370196 \tabularnewline
32 & 0.021731 & 0.1992 & 0.421307 \tabularnewline
33 & -0.023148 & -0.2122 & 0.416249 \tabularnewline
34 & -0.010311 & -0.0945 & 0.462466 \tabularnewline
35 & -0.027158 & -0.2489 & 0.402021 \tabularnewline
36 & -0.003556 & -0.0326 & 0.487037 \tabularnewline
37 & -0.00293 & -0.0269 & 0.489321 \tabularnewline
38 & -0.018925 & -0.1735 & 0.431357 \tabularnewline
39 & 0.041151 & 0.3772 & 0.353504 \tabularnewline
40 & -0.044507 & -0.4079 & 0.342187 \tabularnewline
41 & -0.040524 & -0.3714 & 0.355633 \tabularnewline
42 & -0.008262 & -0.0757 & 0.469911 \tabularnewline
43 & -0.02834 & -0.2597 & 0.397849 \tabularnewline
44 & -0.018994 & -0.1741 & 0.431111 \tabularnewline
45 & -0.049308 & -0.4519 & 0.326247 \tabularnewline
46 & -0.032996 & -0.3024 & 0.381543 \tabularnewline
47 & 0.051037 & 0.4678 & 0.320584 \tabularnewline
48 & -0.010706 & -0.0981 & 0.461036 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30944&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]0.966346[/C][C]8.8567[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.005213[/C][C]-0.0478[/C][C]0.481005[/C][/ROW]
[ROW][C]3[/C][C]-0.015735[/C][C]-0.1442[/C][C]0.442839[/C][/ROW]
[ROW][C]4[/C][C]0.000187[/C][C]0.0017[/C][C]0.499318[/C][/ROW]
[ROW][C]5[/C][C]-0.061501[/C][C]-0.5637[/C][C]0.287242[/C][/ROW]
[ROW][C]6[/C][C]-0.036669[/C][C]-0.3361[/C][C]0.368825[/C][/ROW]
[ROW][C]7[/C][C]-0.047864[/C][C]-0.4387[/C][C]0.331009[/C][/ROW]
[ROW][C]8[/C][C]-0.041424[/C][C]-0.3797[/C][C]0.35258[/C][/ROW]
[ROW][C]9[/C][C]0.005467[/C][C]0.0501[/C][C]0.480078[/C][/ROW]
[ROW][C]10[/C][C]-0.018342[/C][C]-0.1681[/C][C]0.433452[/C][/ROW]
[ROW][C]11[/C][C]0.015654[/C][C]0.1435[/C][C]0.443132[/C][/ROW]
[ROW][C]12[/C][C]-0.007692[/C][C]-0.0705[/C][C]0.471983[/C][/ROW]
[ROW][C]13[/C][C]-0.005637[/C][C]-0.0517[/C][C]0.47946[/C][/ROW]
[ROW][C]14[/C][C]-0.033547[/C][C]-0.3075[/C][C]0.379625[/C][/ROW]
[ROW][C]15[/C][C]-0.009323[/C][C]-0.0854[/C][C]0.466055[/C][/ROW]
[ROW][C]16[/C][C]-0.017215[/C][C]-0.1578[/C][C]0.437505[/C][/ROW]
[ROW][C]17[/C][C]-0.068255[/C][C]-0.6256[/C][C]0.266647[/C][/ROW]
[ROW][C]18[/C][C]-0.014038[/C][C]-0.1287[/C][C]0.448968[/C][/ROW]
[ROW][C]19[/C][C]0.001032[/C][C]0.0095[/C][C]0.496236[/C][/ROW]
[ROW][C]20[/C][C]-0.021914[/C][C]-0.2008[/C][C]0.420654[/C][/ROW]
[ROW][C]21[/C][C]-0.130591[/C][C]-1.1969[/C][C]0.117359[/C][/ROW]
[ROW][C]22[/C][C]-0.01663[/C][C]-0.1524[/C][C]0.439612[/C][/ROW]
[ROW][C]23[/C][C]0.007965[/C][C]0.073[/C][C]0.47099[/C][/ROW]
[ROW][C]24[/C][C]0.023311[/C][C]0.2136[/C][C]0.415669[/C][/ROW]
[ROW][C]25[/C][C]-0.021682[/C][C]-0.1987[/C][C]0.42148[/C][/ROW]
[ROW][C]26[/C][C]-0.030518[/C][C]-0.2797[/C][C]0.390198[/C][/ROW]
[ROW][C]27[/C][C]-0.008313[/C][C]-0.0762[/C][C]0.469726[/C][/ROW]
[ROW][C]28[/C][C]-0.043226[/C][C]-0.3962[/C][C]0.346492[/C][/ROW]
[ROW][C]29[/C][C]0.007036[/C][C]0.0645[/C][C]0.474367[/C][/ROW]
[ROW][C]30[/C][C]-0.023135[/C][C]-0.212[/C][C]0.416297[/C][/ROW]
[ROW][C]31[/C][C]-0.036271[/C][C]-0.3324[/C][C]0.370196[/C][/ROW]
[ROW][C]32[/C][C]0.021731[/C][C]0.1992[/C][C]0.421307[/C][/ROW]
[ROW][C]33[/C][C]-0.023148[/C][C]-0.2122[/C][C]0.416249[/C][/ROW]
[ROW][C]34[/C][C]-0.010311[/C][C]-0.0945[/C][C]0.462466[/C][/ROW]
[ROW][C]35[/C][C]-0.027158[/C][C]-0.2489[/C][C]0.402021[/C][/ROW]
[ROW][C]36[/C][C]-0.003556[/C][C]-0.0326[/C][C]0.487037[/C][/ROW]
[ROW][C]37[/C][C]-0.00293[/C][C]-0.0269[/C][C]0.489321[/C][/ROW]
[ROW][C]38[/C][C]-0.018925[/C][C]-0.1735[/C][C]0.431357[/C][/ROW]
[ROW][C]39[/C][C]0.041151[/C][C]0.3772[/C][C]0.353504[/C][/ROW]
[ROW][C]40[/C][C]-0.044507[/C][C]-0.4079[/C][C]0.342187[/C][/ROW]
[ROW][C]41[/C][C]-0.040524[/C][C]-0.3714[/C][C]0.355633[/C][/ROW]
[ROW][C]42[/C][C]-0.008262[/C][C]-0.0757[/C][C]0.469911[/C][/ROW]
[ROW][C]43[/C][C]-0.02834[/C][C]-0.2597[/C][C]0.397849[/C][/ROW]
[ROW][C]44[/C][C]-0.018994[/C][C]-0.1741[/C][C]0.431111[/C][/ROW]
[ROW][C]45[/C][C]-0.049308[/C][C]-0.4519[/C][C]0.326247[/C][/ROW]
[ROW][C]46[/C][C]-0.032996[/C][C]-0.3024[/C][C]0.381543[/C][/ROW]
[ROW][C]47[/C][C]0.051037[/C][C]0.4678[/C][C]0.320584[/C][/ROW]
[ROW][C]48[/C][C]-0.010706[/C][C]-0.0981[/C][C]0.461036[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30944&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30944&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
10.9663468.85670
2-0.005213-0.04780.481005
3-0.015735-0.14420.442839
40.0001870.00170.499318
5-0.061501-0.56370.287242
6-0.036669-0.33610.368825
7-0.047864-0.43870.331009
8-0.041424-0.37970.35258
90.0054670.05010.480078
10-0.018342-0.16810.433452
110.0156540.14350.443132
12-0.007692-0.07050.471983
13-0.005637-0.05170.47946
14-0.033547-0.30750.379625
15-0.009323-0.08540.466055
16-0.017215-0.15780.437505
17-0.068255-0.62560.266647
18-0.014038-0.12870.448968
190.0010320.00950.496236
20-0.021914-0.20080.420654
21-0.130591-1.19690.117359
22-0.01663-0.15240.439612
230.0079650.0730.47099
240.0233110.21360.415669
25-0.021682-0.19870.42148
26-0.030518-0.27970.390198
27-0.008313-0.07620.469726
28-0.043226-0.39620.346492
290.0070360.06450.474367
30-0.023135-0.2120.416297
31-0.036271-0.33240.370196
320.0217310.19920.421307
33-0.023148-0.21220.416249
34-0.010311-0.09450.462466
35-0.027158-0.24890.402021
36-0.003556-0.03260.487037
37-0.00293-0.02690.489321
38-0.018925-0.17350.431357
390.0411510.37720.353504
40-0.044507-0.40790.342187
41-0.040524-0.37140.355633
42-0.008262-0.07570.469911
43-0.02834-0.25970.397849
44-0.018994-0.17410.431111
45-0.049308-0.45190.326247
46-0.032996-0.30240.381543
470.0510370.46780.320584
48-0.010706-0.09810.461036


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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')