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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 computationWed, 16 Dec 2009 07:01:40 -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/Dec/16/t1260972153rbozfrclzl7ca22.htm/, Retrieved Tue, 30 Apr 2024 11:43:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68352, Retrieved Tue, 30 Apr 2024 11:43:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [ACF (d=1; D=1) ] [2009-12-16 14:01:40] [6df9bd2792d60592b4a24994398a86db] [Current]
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Dataseries X:
7787.0
8474.2
9154.7
8557.2
7951.1
9156.7
7865.7
7337.4
9131.7
8814.6
8598.8
8439.6
7451.8
8016.2
9544.1
8270.7
8102.2
9369.0
7657.7
7816.6
9391.3
9445.4
9533.1
10068.7
8955.5
10423.9
11617.2
9391.1
10872.0
10230.4
9221.0
9428.6
10934.5
10986.0
11724.6
11180.9
11163.2
11240.9
12107.1
10762.3
11340.4
11266.8
9542.7
9227.7
10571.9
10774.4
10392.8
9920.2
9884.9
10174.5
11395.4
10760.2
10570.1
10536.0
9902.6
8889.0
10837.3
11624.1
10509.0
10984.9
10649.1
10855.7
11677.4
10760.2
10046.2
10772.8
9987.7
8638.7
11063.7
11855.7
10684.5
11337.4
10478.0
11123.9
12909.3
11339.9
10462.2
12733.5
10519.2
10414.9
12476.8
12384.6
12266.7
12919.9
11497.3
12142.0
13919.4
12656.8
12034.1
13199.7
10881.3
11301.2
13643.9
12517.0
13981.1
14275.7
13435.0
13565.7
16216.3
12970.0
14079.9
14235.0
12213.4
12581.0
14130.4
14210.8
14378.5
13142.8
13714.7
13621.9
15379.8
13306.3
14391.2
14909.9
14025.4
12951.2
14344.3
16093.4
15413.6
14705.7
15972.8
16241.4
16626.4
17136.2
15622.9
18003.9
16136.1
14423.7
16789.4
16782.2
14133.8
12607.0




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=68352&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=68352&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68352&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
1-0.524489-5.72150
20.1046671.14180.127919
30.2271262.47760.007314
4-0.213463-2.32860.010784
50.0353340.38540.350297
60.2210752.41160.008705
7-0.329754-3.59720.000235
80.108111.17930.120307
90.2346592.55980.005862
10-0.357668-3.90177.9e-05
110.1974092.15350.016649
12-0.02072-0.2260.410784
13-0.229466-2.50320.006832
140.162581.77350.039349
150.0177110.19320.423564
16-0.221626-2.41770.008569
170.1854952.02350.02263
180.0261750.28550.387864
19-0.212453-2.31760.01109
200.2065292.2530.013047
21-0.060632-0.66140.254812
22-0.189913-2.07170.020227
230.3407433.71710.000154
24-0.26711-2.91380.002133
250.0358960.39160.348033
260.1845012.01270.023204
27-0.110308-1.20330.115622
28-0.085088-0.92820.17759
290.2259612.46490.007565
30-0.249859-2.72560.003693
310.0851120.92850.177523
320.0836040.9120.181802
33-0.156012-1.70190.045693
340.0258930.28250.389043
350.1614511.76120.040384
36-0.238316-2.59970.005256

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.524489 & -5.7215 & 0 \tabularnewline
2 & 0.104667 & 1.1418 & 0.127919 \tabularnewline
3 & 0.227126 & 2.4776 & 0.007314 \tabularnewline
4 & -0.213463 & -2.3286 & 0.010784 \tabularnewline
5 & 0.035334 & 0.3854 & 0.350297 \tabularnewline
6 & 0.221075 & 2.4116 & 0.008705 \tabularnewline
7 & -0.329754 & -3.5972 & 0.000235 \tabularnewline
8 & 0.10811 & 1.1793 & 0.120307 \tabularnewline
9 & 0.234659 & 2.5598 & 0.005862 \tabularnewline
10 & -0.357668 & -3.9017 & 7.9e-05 \tabularnewline
11 & 0.197409 & 2.1535 & 0.016649 \tabularnewline
12 & -0.02072 & -0.226 & 0.410784 \tabularnewline
13 & -0.229466 & -2.5032 & 0.006832 \tabularnewline
14 & 0.16258 & 1.7735 & 0.039349 \tabularnewline
15 & 0.017711 & 0.1932 & 0.423564 \tabularnewline
16 & -0.221626 & -2.4177 & 0.008569 \tabularnewline
17 & 0.185495 & 2.0235 & 0.02263 \tabularnewline
18 & 0.026175 & 0.2855 & 0.387864 \tabularnewline
19 & -0.212453 & -2.3176 & 0.01109 \tabularnewline
20 & 0.206529 & 2.253 & 0.013047 \tabularnewline
21 & -0.060632 & -0.6614 & 0.254812 \tabularnewline
22 & -0.189913 & -2.0717 & 0.020227 \tabularnewline
23 & 0.340743 & 3.7171 & 0.000154 \tabularnewline
24 & -0.26711 & -2.9138 & 0.002133 \tabularnewline
25 & 0.035896 & 0.3916 & 0.348033 \tabularnewline
26 & 0.184501 & 2.0127 & 0.023204 \tabularnewline
27 & -0.110308 & -1.2033 & 0.115622 \tabularnewline
28 & -0.085088 & -0.9282 & 0.17759 \tabularnewline
29 & 0.225961 & 2.4649 & 0.007565 \tabularnewline
30 & -0.249859 & -2.7256 & 0.003693 \tabularnewline
31 & 0.085112 & 0.9285 & 0.177523 \tabularnewline
32 & 0.083604 & 0.912 & 0.181802 \tabularnewline
33 & -0.156012 & -1.7019 & 0.045693 \tabularnewline
34 & 0.025893 & 0.2825 & 0.389043 \tabularnewline
35 & 0.161451 & 1.7612 & 0.040384 \tabularnewline
36 & -0.238316 & -2.5997 & 0.005256 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68352&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]-0.524489[/C][C]-5.7215[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.104667[/C][C]1.1418[/C][C]0.127919[/C][/ROW]
[ROW][C]3[/C][C]0.227126[/C][C]2.4776[/C][C]0.007314[/C][/ROW]
[ROW][C]4[/C][C]-0.213463[/C][C]-2.3286[/C][C]0.010784[/C][/ROW]
[ROW][C]5[/C][C]0.035334[/C][C]0.3854[/C][C]0.350297[/C][/ROW]
[ROW][C]6[/C][C]0.221075[/C][C]2.4116[/C][C]0.008705[/C][/ROW]
[ROW][C]7[/C][C]-0.329754[/C][C]-3.5972[/C][C]0.000235[/C][/ROW]
[ROW][C]8[/C][C]0.10811[/C][C]1.1793[/C][C]0.120307[/C][/ROW]
[ROW][C]9[/C][C]0.234659[/C][C]2.5598[/C][C]0.005862[/C][/ROW]
[ROW][C]10[/C][C]-0.357668[/C][C]-3.9017[/C][C]7.9e-05[/C][/ROW]
[ROW][C]11[/C][C]0.197409[/C][C]2.1535[/C][C]0.016649[/C][/ROW]
[ROW][C]12[/C][C]-0.02072[/C][C]-0.226[/C][C]0.410784[/C][/ROW]
[ROW][C]13[/C][C]-0.229466[/C][C]-2.5032[/C][C]0.006832[/C][/ROW]
[ROW][C]14[/C][C]0.16258[/C][C]1.7735[/C][C]0.039349[/C][/ROW]
[ROW][C]15[/C][C]0.017711[/C][C]0.1932[/C][C]0.423564[/C][/ROW]
[ROW][C]16[/C][C]-0.221626[/C][C]-2.4177[/C][C]0.008569[/C][/ROW]
[ROW][C]17[/C][C]0.185495[/C][C]2.0235[/C][C]0.02263[/C][/ROW]
[ROW][C]18[/C][C]0.026175[/C][C]0.2855[/C][C]0.387864[/C][/ROW]
[ROW][C]19[/C][C]-0.212453[/C][C]-2.3176[/C][C]0.01109[/C][/ROW]
[ROW][C]20[/C][C]0.206529[/C][C]2.253[/C][C]0.013047[/C][/ROW]
[ROW][C]21[/C][C]-0.060632[/C][C]-0.6614[/C][C]0.254812[/C][/ROW]
[ROW][C]22[/C][C]-0.189913[/C][C]-2.0717[/C][C]0.020227[/C][/ROW]
[ROW][C]23[/C][C]0.340743[/C][C]3.7171[/C][C]0.000154[/C][/ROW]
[ROW][C]24[/C][C]-0.26711[/C][C]-2.9138[/C][C]0.002133[/C][/ROW]
[ROW][C]25[/C][C]0.035896[/C][C]0.3916[/C][C]0.348033[/C][/ROW]
[ROW][C]26[/C][C]0.184501[/C][C]2.0127[/C][C]0.023204[/C][/ROW]
[ROW][C]27[/C][C]-0.110308[/C][C]-1.2033[/C][C]0.115622[/C][/ROW]
[ROW][C]28[/C][C]-0.085088[/C][C]-0.9282[/C][C]0.17759[/C][/ROW]
[ROW][C]29[/C][C]0.225961[/C][C]2.4649[/C][C]0.007565[/C][/ROW]
[ROW][C]30[/C][C]-0.249859[/C][C]-2.7256[/C][C]0.003693[/C][/ROW]
[ROW][C]31[/C][C]0.085112[/C][C]0.9285[/C][C]0.177523[/C][/ROW]
[ROW][C]32[/C][C]0.083604[/C][C]0.912[/C][C]0.181802[/C][/ROW]
[ROW][C]33[/C][C]-0.156012[/C][C]-1.7019[/C][C]0.045693[/C][/ROW]
[ROW][C]34[/C][C]0.025893[/C][C]0.2825[/C][C]0.389043[/C][/ROW]
[ROW][C]35[/C][C]0.161451[/C][C]1.7612[/C][C]0.040384[/C][/ROW]
[ROW][C]36[/C][C]-0.238316[/C][C]-2.5997[/C][C]0.005256[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68352&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68352&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
1-0.524489-5.72150
20.1046671.14180.127919
30.2271262.47760.007314
4-0.213463-2.32860.010784
50.0353340.38540.350297
60.2210752.41160.008705
7-0.329754-3.59720.000235
80.108111.17930.120307
90.2346592.55980.005862
10-0.357668-3.90177.9e-05
110.1974092.15350.016649
12-0.02072-0.2260.410784
13-0.229466-2.50320.006832
140.162581.77350.039349
150.0177110.19320.423564
16-0.221626-2.41770.008569
170.1854952.02350.02263
180.0261750.28550.387864
19-0.212453-2.31760.01109
200.2065292.2530.013047
21-0.060632-0.66140.254812
22-0.189913-2.07170.020227
230.3407433.71710.000154
24-0.26711-2.91380.002133
250.0358960.39160.348033
260.1845012.01270.023204
27-0.110308-1.20330.115622
28-0.085088-0.92820.17759
290.2259612.46490.007565
30-0.249859-2.72560.003693
310.0851120.92850.177523
320.0836040.9120.181802
33-0.156012-1.70190.045693
340.0258930.28250.389043
350.1614511.76120.040384
36-0.238316-2.59970.005256







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.524489-5.72150
2-0.235093-2.56460.005787
30.2506032.73380.003609
40.0924521.00850.157624
5-0.100192-1.0930.138309
60.1765411.92580.028255
7-0.103303-1.12690.131025
8-0.218783-2.38660.009289
90.2300262.50930.006721
100.026690.29120.38572
11-0.115878-1.26410.104337
12-0.112465-1.22680.111151
13-0.149583-1.63180.052687
14-0.158821-1.73250.042885
150.0547520.59730.275729
160.0725030.79090.215283
17-0.073322-0.79980.212696
180.0757310.82610.205192
19-0.017664-0.19270.423765
20-0.138511-1.5110.066722
210.0421320.45960.323319
22-0.060644-0.66160.254768
230.1061371.15780.124629
24-0.088583-0.96630.167919
25-0.041899-0.45710.324228
260.0231090.25210.400704
270.1117261.21880.112667
28-0.059574-0.64990.258513
29-0.060385-0.65870.255672
30-0.035663-0.3890.348971
31-0.048229-0.52610.299893
32-0.122712-1.33860.091622
330.0978111.0670.144068
34-0.078541-0.85680.196643
350.0237090.25860.398183
36-0.045541-0.49680.310125

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.524489 & -5.7215 & 0 \tabularnewline
2 & -0.235093 & -2.5646 & 0.005787 \tabularnewline
3 & 0.250603 & 2.7338 & 0.003609 \tabularnewline
4 & 0.092452 & 1.0085 & 0.157624 \tabularnewline
5 & -0.100192 & -1.093 & 0.138309 \tabularnewline
6 & 0.176541 & 1.9258 & 0.028255 \tabularnewline
7 & -0.103303 & -1.1269 & 0.131025 \tabularnewline
8 & -0.218783 & -2.3866 & 0.009289 \tabularnewline
9 & 0.230026 & 2.5093 & 0.006721 \tabularnewline
10 & 0.02669 & 0.2912 & 0.38572 \tabularnewline
11 & -0.115878 & -1.2641 & 0.104337 \tabularnewline
12 & -0.112465 & -1.2268 & 0.111151 \tabularnewline
13 & -0.149583 & -1.6318 & 0.052687 \tabularnewline
14 & -0.158821 & -1.7325 & 0.042885 \tabularnewline
15 & 0.054752 & 0.5973 & 0.275729 \tabularnewline
16 & 0.072503 & 0.7909 & 0.215283 \tabularnewline
17 & -0.073322 & -0.7998 & 0.212696 \tabularnewline
18 & 0.075731 & 0.8261 & 0.205192 \tabularnewline
19 & -0.017664 & -0.1927 & 0.423765 \tabularnewline
20 & -0.138511 & -1.511 & 0.066722 \tabularnewline
21 & 0.042132 & 0.4596 & 0.323319 \tabularnewline
22 & -0.060644 & -0.6616 & 0.254768 \tabularnewline
23 & 0.106137 & 1.1578 & 0.124629 \tabularnewline
24 & -0.088583 & -0.9663 & 0.167919 \tabularnewline
25 & -0.041899 & -0.4571 & 0.324228 \tabularnewline
26 & 0.023109 & 0.2521 & 0.400704 \tabularnewline
27 & 0.111726 & 1.2188 & 0.112667 \tabularnewline
28 & -0.059574 & -0.6499 & 0.258513 \tabularnewline
29 & -0.060385 & -0.6587 & 0.255672 \tabularnewline
30 & -0.035663 & -0.389 & 0.348971 \tabularnewline
31 & -0.048229 & -0.5261 & 0.299893 \tabularnewline
32 & -0.122712 & -1.3386 & 0.091622 \tabularnewline
33 & 0.097811 & 1.067 & 0.144068 \tabularnewline
34 & -0.078541 & -0.8568 & 0.196643 \tabularnewline
35 & 0.023709 & 0.2586 & 0.398183 \tabularnewline
36 & -0.045541 & -0.4968 & 0.310125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68352&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]-0.524489[/C][C]-5.7215[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.235093[/C][C]-2.5646[/C][C]0.005787[/C][/ROW]
[ROW][C]3[/C][C]0.250603[/C][C]2.7338[/C][C]0.003609[/C][/ROW]
[ROW][C]4[/C][C]0.092452[/C][C]1.0085[/C][C]0.157624[/C][/ROW]
[ROW][C]5[/C][C]-0.100192[/C][C]-1.093[/C][C]0.138309[/C][/ROW]
[ROW][C]6[/C][C]0.176541[/C][C]1.9258[/C][C]0.028255[/C][/ROW]
[ROW][C]7[/C][C]-0.103303[/C][C]-1.1269[/C][C]0.131025[/C][/ROW]
[ROW][C]8[/C][C]-0.218783[/C][C]-2.3866[/C][C]0.009289[/C][/ROW]
[ROW][C]9[/C][C]0.230026[/C][C]2.5093[/C][C]0.006721[/C][/ROW]
[ROW][C]10[/C][C]0.02669[/C][C]0.2912[/C][C]0.38572[/C][/ROW]
[ROW][C]11[/C][C]-0.115878[/C][C]-1.2641[/C][C]0.104337[/C][/ROW]
[ROW][C]12[/C][C]-0.112465[/C][C]-1.2268[/C][C]0.111151[/C][/ROW]
[ROW][C]13[/C][C]-0.149583[/C][C]-1.6318[/C][C]0.052687[/C][/ROW]
[ROW][C]14[/C][C]-0.158821[/C][C]-1.7325[/C][C]0.042885[/C][/ROW]
[ROW][C]15[/C][C]0.054752[/C][C]0.5973[/C][C]0.275729[/C][/ROW]
[ROW][C]16[/C][C]0.072503[/C][C]0.7909[/C][C]0.215283[/C][/ROW]
[ROW][C]17[/C][C]-0.073322[/C][C]-0.7998[/C][C]0.212696[/C][/ROW]
[ROW][C]18[/C][C]0.075731[/C][C]0.8261[/C][C]0.205192[/C][/ROW]
[ROW][C]19[/C][C]-0.017664[/C][C]-0.1927[/C][C]0.423765[/C][/ROW]
[ROW][C]20[/C][C]-0.138511[/C][C]-1.511[/C][C]0.066722[/C][/ROW]
[ROW][C]21[/C][C]0.042132[/C][C]0.4596[/C][C]0.323319[/C][/ROW]
[ROW][C]22[/C][C]-0.060644[/C][C]-0.6616[/C][C]0.254768[/C][/ROW]
[ROW][C]23[/C][C]0.106137[/C][C]1.1578[/C][C]0.124629[/C][/ROW]
[ROW][C]24[/C][C]-0.088583[/C][C]-0.9663[/C][C]0.167919[/C][/ROW]
[ROW][C]25[/C][C]-0.041899[/C][C]-0.4571[/C][C]0.324228[/C][/ROW]
[ROW][C]26[/C][C]0.023109[/C][C]0.2521[/C][C]0.400704[/C][/ROW]
[ROW][C]27[/C][C]0.111726[/C][C]1.2188[/C][C]0.112667[/C][/ROW]
[ROW][C]28[/C][C]-0.059574[/C][C]-0.6499[/C][C]0.258513[/C][/ROW]
[ROW][C]29[/C][C]-0.060385[/C][C]-0.6587[/C][C]0.255672[/C][/ROW]
[ROW][C]30[/C][C]-0.035663[/C][C]-0.389[/C][C]0.348971[/C][/ROW]
[ROW][C]31[/C][C]-0.048229[/C][C]-0.5261[/C][C]0.299893[/C][/ROW]
[ROW][C]32[/C][C]-0.122712[/C][C]-1.3386[/C][C]0.091622[/C][/ROW]
[ROW][C]33[/C][C]0.097811[/C][C]1.067[/C][C]0.144068[/C][/ROW]
[ROW][C]34[/C][C]-0.078541[/C][C]-0.8568[/C][C]0.196643[/C][/ROW]
[ROW][C]35[/C][C]0.023709[/C][C]0.2586[/C][C]0.398183[/C][/ROW]
[ROW][C]36[/C][C]-0.045541[/C][C]-0.4968[/C][C]0.310125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68352&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68352&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
1-0.524489-5.72150
2-0.235093-2.56460.005787
30.2506032.73380.003609
40.0924521.00850.157624
5-0.100192-1.0930.138309
60.1765411.92580.028255
7-0.103303-1.12690.131025
8-0.218783-2.38660.009289
90.2300262.50930.006721
100.026690.29120.38572
11-0.115878-1.26410.104337
12-0.112465-1.22680.111151
13-0.149583-1.63180.052687
14-0.158821-1.73250.042885
150.0547520.59730.275729
160.0725030.79090.215283
17-0.073322-0.79980.212696
180.0757310.82610.205192
19-0.017664-0.19270.423765
20-0.138511-1.5110.066722
210.0421320.45960.323319
22-0.060644-0.66160.254768
230.1061371.15780.124629
24-0.088583-0.96630.167919
25-0.041899-0.45710.324228
260.0231090.25210.400704
270.1117261.21880.112667
28-0.059574-0.64990.258513
29-0.060385-0.65870.255672
30-0.035663-0.3890.348971
31-0.048229-0.52610.299893
32-0.122712-1.33860.091622
330.0978111.0670.144068
34-0.078541-0.85680.196643
350.0237090.25860.398183
36-0.045541-0.49680.310125



Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; 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')