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Description of Statistical Computation

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 computationSat, 26 Dec 2009 11:52:50 -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/26/t12618536353nvn47lpni0lkrz.htm/, Retrieved Sun, 28 Apr 2024 20:43:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70772, Retrieved Sun, 28 Apr 2024 20:43:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

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] [paper3: pacf d,D=0] [2009-12-26 18:52:50] [b090d569c0a4c77894e0b029f4429f19] [Current]
-   P     [(Partial) Autocorrelation Function] [paper4 pacf d0D1] [2009-12-26 18:57:15] [0f0e461427f61416e46aeda5f4901bed]
-   P       [(Partial) Autocorrelation Function] [paper5 pacf dD1] [2009-12-26 19:00:19] [0f0e461427f61416e46aeda5f4901bed]
- RMP       [Variance Reduction Matrix] [paper7: vrm] [2009-12-26 19:02:39] [0f0e461427f61416e46aeda5f4901bed]
- RMP       [Spectral Analysis] [paper 8 spectrum dD0] [2009-12-26 19:06:12] [0f0e461427f61416e46aeda5f4901bed]
-   P         [Spectral Analysis] [paper 9 spectrum ...] [2009-12-26 19:08:13] [0f0e461427f61416e46aeda5f4901bed]
-   P           [Spectral Analysis] [paper 10 spectrum...] [2009-12-26 19:10:27] [0f0e461427f61416e46aeda5f4901bed]
- RMP       [Standard Deviation-Mean Plot] [paper 11 sdm] [2009-12-26 19:11:51] [0f0e461427f61416e46aeda5f4901bed]
- RMP       [ARIMA Backward Selection] [paper 12 backward...] [2009-12-26 19:14:52] [0f0e461427f61416e46aeda5f4901bed]
- RMP         [ARIMA Forecasting] [paper forecast] [2009-12-29 20:55:02] [0f0e461427f61416e46aeda5f4901bed]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
111.6
104.6
91.6
98.3
97.7
106.3
102.3
106.6
108.1
93.8
88.2
108.9
114.2
102.5
94.2
97.4
98.5
106.5
102.9
97.1
103.7
93.4
85.8
108.6
110.2
101.2
101.2
96.9
99.4
118.7
108.0
101.2
119.9
94.8
95.3
118.0
115.9
111.4
108.2
108.8
109.5
124.8
115.3
109.5
124.2
92.9
98.4
120.9
111.7
116.1
109.4
111.7
114.3
133.7
114.3
126.5
131.0
104.0
108.9
128.5
132.4
128.0
116.4
120.9
118.6
133.1
121.1
127.6
135.4
114.9
114.3
128.9
138.9
129.4
115.0
128.0
127.0
128.8
137.9
128.4
135.9
122.2
113.1
136.2
138.0
115.2
111.0
99.2
102.4
112.7
105.5
98.3
116.4
97.4
93.3
117.4

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=70772&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=70772&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70772&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
10.5797915.68080
20.3859133.78120.000136
30.5209725.10451e-06
40.4508614.41751.3e-05
50.5156415.05221e-06
60.575915.64270
70.4328544.24112.6e-05
80.3742843.66720.000201
90.3223113.1580.001062
100.1408051.37960.085458
110.3347553.27990.000724
120.5959245.83880
130.2742042.68660.004253
140.1263851.23830.10931
150.1920881.88210.031428
160.1761821.72620.043762
170.2574262.52220.006653
180.2706732.6520.004681
190.1862041.82440.0356
200.1406891.37850.085631
210.075950.74420.229299
22-0.058776-0.57590.28302
230.1095131.0730.142979
240.2952112.89250.002364
250.0542210.53130.298235
26-0.104935-1.02810.153233
27-0.050185-0.49170.312024
28-0.048037-0.47070.319474
29-0.009922-0.09720.461378
300.0086790.0850.466204
31-0.029787-0.29190.385514
32-0.106184-1.04040.150387
33-0.171052-1.6760.0485
34-0.245613-2.40650.00901
35-0.141391-1.38530.084579
360.0389880.3820.351651

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.579791 & 5.6808 & 0 \tabularnewline
2 & 0.385913 & 3.7812 & 0.000136 \tabularnewline
3 & 0.520972 & 5.1045 & 1e-06 \tabularnewline
4 & 0.450861 & 4.4175 & 1.3e-05 \tabularnewline
5 & 0.515641 & 5.0522 & 1e-06 \tabularnewline
6 & 0.57591 & 5.6427 & 0 \tabularnewline
7 & 0.432854 & 4.2411 & 2.6e-05 \tabularnewline
8 & 0.374284 & 3.6672 & 0.000201 \tabularnewline
9 & 0.322311 & 3.158 & 0.001062 \tabularnewline
10 & 0.140805 & 1.3796 & 0.085458 \tabularnewline
11 & 0.334755 & 3.2799 & 0.000724 \tabularnewline
12 & 0.595924 & 5.8388 & 0 \tabularnewline
13 & 0.274204 & 2.6866 & 0.004253 \tabularnewline
14 & 0.126385 & 1.2383 & 0.10931 \tabularnewline
15 & 0.192088 & 1.8821 & 0.031428 \tabularnewline
16 & 0.176182 & 1.7262 & 0.043762 \tabularnewline
17 & 0.257426 & 2.5222 & 0.006653 \tabularnewline
18 & 0.270673 & 2.652 & 0.004681 \tabularnewline
19 & 0.186204 & 1.8244 & 0.0356 \tabularnewline
20 & 0.140689 & 1.3785 & 0.085631 \tabularnewline
21 & 0.07595 & 0.7442 & 0.229299 \tabularnewline
22 & -0.058776 & -0.5759 & 0.28302 \tabularnewline
23 & 0.109513 & 1.073 & 0.142979 \tabularnewline
24 & 0.295211 & 2.8925 & 0.002364 \tabularnewline
25 & 0.054221 & 0.5313 & 0.298235 \tabularnewline
26 & -0.104935 & -1.0281 & 0.153233 \tabularnewline
27 & -0.050185 & -0.4917 & 0.312024 \tabularnewline
28 & -0.048037 & -0.4707 & 0.319474 \tabularnewline
29 & -0.009922 & -0.0972 & 0.461378 \tabularnewline
30 & 0.008679 & 0.085 & 0.466204 \tabularnewline
31 & -0.029787 & -0.2919 & 0.385514 \tabularnewline
32 & -0.106184 & -1.0404 & 0.150387 \tabularnewline
33 & -0.171052 & -1.676 & 0.0485 \tabularnewline
34 & -0.245613 & -2.4065 & 0.00901 \tabularnewline
35 & -0.141391 & -1.3853 & 0.084579 \tabularnewline
36 & 0.038988 & 0.382 & 0.351651 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70772&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]0.579791[/C][C]5.6808[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.385913[/C][C]3.7812[/C][C]0.000136[/C][/ROW]
[ROW][C]3[/C][C]0.520972[/C][C]5.1045[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.450861[/C][C]4.4175[/C][C]1.3e-05[/C][/ROW]
[ROW][C]5[/C][C]0.515641[/C][C]5.0522[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.57591[/C][C]5.6427[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.432854[/C][C]4.2411[/C][C]2.6e-05[/C][/ROW]
[ROW][C]8[/C][C]0.374284[/C][C]3.6672[/C][C]0.000201[/C][/ROW]
[ROW][C]9[/C][C]0.322311[/C][C]3.158[/C][C]0.001062[/C][/ROW]
[ROW][C]10[/C][C]0.140805[/C][C]1.3796[/C][C]0.085458[/C][/ROW]
[ROW][C]11[/C][C]0.334755[/C][C]3.2799[/C][C]0.000724[/C][/ROW]
[ROW][C]12[/C][C]0.595924[/C][C]5.8388[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.274204[/C][C]2.6866[/C][C]0.004253[/C][/ROW]
[ROW][C]14[/C][C]0.126385[/C][C]1.2383[/C][C]0.10931[/C][/ROW]
[ROW][C]15[/C][C]0.192088[/C][C]1.8821[/C][C]0.031428[/C][/ROW]
[ROW][C]16[/C][C]0.176182[/C][C]1.7262[/C][C]0.043762[/C][/ROW]
[ROW][C]17[/C][C]0.257426[/C][C]2.5222[/C][C]0.006653[/C][/ROW]
[ROW][C]18[/C][C]0.270673[/C][C]2.652[/C][C]0.004681[/C][/ROW]
[ROW][C]19[/C][C]0.186204[/C][C]1.8244[/C][C]0.0356[/C][/ROW]
[ROW][C]20[/C][C]0.140689[/C][C]1.3785[/C][C]0.085631[/C][/ROW]
[ROW][C]21[/C][C]0.07595[/C][C]0.7442[/C][C]0.229299[/C][/ROW]
[ROW][C]22[/C][C]-0.058776[/C][C]-0.5759[/C][C]0.28302[/C][/ROW]
[ROW][C]23[/C][C]0.109513[/C][C]1.073[/C][C]0.142979[/C][/ROW]
[ROW][C]24[/C][C]0.295211[/C][C]2.8925[/C][C]0.002364[/C][/ROW]
[ROW][C]25[/C][C]0.054221[/C][C]0.5313[/C][C]0.298235[/C][/ROW]
[ROW][C]26[/C][C]-0.104935[/C][C]-1.0281[/C][C]0.153233[/C][/ROW]
[ROW][C]27[/C][C]-0.050185[/C][C]-0.4917[/C][C]0.312024[/C][/ROW]
[ROW][C]28[/C][C]-0.048037[/C][C]-0.4707[/C][C]0.319474[/C][/ROW]
[ROW][C]29[/C][C]-0.009922[/C][C]-0.0972[/C][C]0.461378[/C][/ROW]
[ROW][C]30[/C][C]0.008679[/C][C]0.085[/C][C]0.466204[/C][/ROW]
[ROW][C]31[/C][C]-0.029787[/C][C]-0.2919[/C][C]0.385514[/C][/ROW]
[ROW][C]32[/C][C]-0.106184[/C][C]-1.0404[/C][C]0.150387[/C][/ROW]
[ROW][C]33[/C][C]-0.171052[/C][C]-1.676[/C][C]0.0485[/C][/ROW]
[ROW][C]34[/C][C]-0.245613[/C][C]-2.4065[/C][C]0.00901[/C][/ROW]
[ROW][C]35[/C][C]-0.141391[/C][C]-1.3853[/C][C]0.084579[/C][/ROW]
[ROW][C]36[/C][C]0.038988[/C][C]0.382[/C][C]0.351651[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70772&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70772&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
10.5797915.68080
20.3859133.78120.000136
30.5209725.10451e-06
40.4508614.41751.3e-05
50.5156415.05221e-06
60.575915.64270
70.4328544.24112.6e-05
80.3742843.66720.000201
90.3223113.1580.001062
100.1408051.37960.085458
110.3347553.27990.000724
120.5959245.83880
130.2742042.68660.004253
140.1263851.23830.10931
150.1920881.88210.031428
160.1761821.72620.043762
170.2574262.52220.006653
180.2706732.6520.004681
190.1862041.82440.0356
200.1406891.37850.085631
210.075950.74420.229299
22-0.058776-0.57590.28302
230.1095131.0730.142979
240.2952112.89250.002364
250.0542210.53130.298235
26-0.104935-1.02810.153233
27-0.050185-0.49170.312024
28-0.048037-0.47070.319474
29-0.009922-0.09720.461378
300.0086790.0850.466204
31-0.029787-0.29190.385514
32-0.106184-1.04040.150387
33-0.171052-1.6760.0485
34-0.245613-2.40650.00901
35-0.141391-1.38530.084579
360.0389880.3820.351651






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5797915.68080
20.0749520.73440.232256
30.4098354.01555.9e-05
40.0104380.10230.459376
50.3680223.60590.000248
60.1404551.37620.085985
70.0209940.20570.41873
8-0.04522-0.44310.329359
9-0.180892-1.77240.039753
10-0.402751-3.94617.6e-05
110.2287592.24140.013653
120.4803084.7064e-06
13-0.209725-2.05490.021304
14-0.155261-1.52120.065744
15-0.131318-1.28660.100655
160.1821291.78450.038751
17-0.027767-0.27210.393078
18-0.088488-0.8670.194052
19-0.008623-0.08450.466423
20-0.102298-1.00230.159357
210.0855750.83850.201927
22-0.034355-0.33660.368572
23-0.012638-0.12380.450856
24-0.055019-0.53910.295541
25-0.020125-0.19720.422052
26-0.111207-1.08960.139307
270.067010.65660.256518
28-0.069188-0.67790.249732
29-0.083764-0.82070.20692
30-0.022922-0.22460.411387
310.134641.31920.09512
32-0.1045-1.02390.154231
33-0.085449-0.83720.202272
340.0365190.35780.360636
35-0.106341-1.04190.150032
360.0682590.66880.252616

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.579791 & 5.6808 & 0 \tabularnewline
2 & 0.074952 & 0.7344 & 0.232256 \tabularnewline
3 & 0.409835 & 4.0155 & 5.9e-05 \tabularnewline
4 & 0.010438 & 0.1023 & 0.459376 \tabularnewline
5 & 0.368022 & 3.6059 & 0.000248 \tabularnewline
6 & 0.140455 & 1.3762 & 0.085985 \tabularnewline
7 & 0.020994 & 0.2057 & 0.41873 \tabularnewline
8 & -0.04522 & -0.4431 & 0.329359 \tabularnewline
9 & -0.180892 & -1.7724 & 0.039753 \tabularnewline
10 & -0.402751 & -3.9461 & 7.6e-05 \tabularnewline
11 & 0.228759 & 2.2414 & 0.013653 \tabularnewline
12 & 0.480308 & 4.706 & 4e-06 \tabularnewline
13 & -0.209725 & -2.0549 & 0.021304 \tabularnewline
14 & -0.155261 & -1.5212 & 0.065744 \tabularnewline
15 & -0.131318 & -1.2866 & 0.100655 \tabularnewline
16 & 0.182129 & 1.7845 & 0.038751 \tabularnewline
17 & -0.027767 & -0.2721 & 0.393078 \tabularnewline
18 & -0.088488 & -0.867 & 0.194052 \tabularnewline
19 & -0.008623 & -0.0845 & 0.466423 \tabularnewline
20 & -0.102298 & -1.0023 & 0.159357 \tabularnewline
21 & 0.085575 & 0.8385 & 0.201927 \tabularnewline
22 & -0.034355 & -0.3366 & 0.368572 \tabularnewline
23 & -0.012638 & -0.1238 & 0.450856 \tabularnewline
24 & -0.055019 & -0.5391 & 0.295541 \tabularnewline
25 & -0.020125 & -0.1972 & 0.422052 \tabularnewline
26 & -0.111207 & -1.0896 & 0.139307 \tabularnewline
27 & 0.06701 & 0.6566 & 0.256518 \tabularnewline
28 & -0.069188 & -0.6779 & 0.249732 \tabularnewline
29 & -0.083764 & -0.8207 & 0.20692 \tabularnewline
30 & -0.022922 & -0.2246 & 0.411387 \tabularnewline
31 & 0.13464 & 1.3192 & 0.09512 \tabularnewline
32 & -0.1045 & -1.0239 & 0.154231 \tabularnewline
33 & -0.085449 & -0.8372 & 0.202272 \tabularnewline
34 & 0.036519 & 0.3578 & 0.360636 \tabularnewline
35 & -0.106341 & -1.0419 & 0.150032 \tabularnewline
36 & 0.068259 & 0.6688 & 0.252616 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70772&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]0.579791[/C][C]5.6808[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.074952[/C][C]0.7344[/C][C]0.232256[/C][/ROW]
[ROW][C]3[/C][C]0.409835[/C][C]4.0155[/C][C]5.9e-05[/C][/ROW]
[ROW][C]4[/C][C]0.010438[/C][C]0.1023[/C][C]0.459376[/C][/ROW]
[ROW][C]5[/C][C]0.368022[/C][C]3.6059[/C][C]0.000248[/C][/ROW]
[ROW][C]6[/C][C]0.140455[/C][C]1.3762[/C][C]0.085985[/C][/ROW]
[ROW][C]7[/C][C]0.020994[/C][C]0.2057[/C][C]0.41873[/C][/ROW]
[ROW][C]8[/C][C]-0.04522[/C][C]-0.4431[/C][C]0.329359[/C][/ROW]
[ROW][C]9[/C][C]-0.180892[/C][C]-1.7724[/C][C]0.039753[/C][/ROW]
[ROW][C]10[/C][C]-0.402751[/C][C]-3.9461[/C][C]7.6e-05[/C][/ROW]
[ROW][C]11[/C][C]0.228759[/C][C]2.2414[/C][C]0.013653[/C][/ROW]
[ROW][C]12[/C][C]0.480308[/C][C]4.706[/C][C]4e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.209725[/C][C]-2.0549[/C][C]0.021304[/C][/ROW]
[ROW][C]14[/C][C]-0.155261[/C][C]-1.5212[/C][C]0.065744[/C][/ROW]
[ROW][C]15[/C][C]-0.131318[/C][C]-1.2866[/C][C]0.100655[/C][/ROW]
[ROW][C]16[/C][C]0.182129[/C][C]1.7845[/C][C]0.038751[/C][/ROW]
[ROW][C]17[/C][C]-0.027767[/C][C]-0.2721[/C][C]0.393078[/C][/ROW]
[ROW][C]18[/C][C]-0.088488[/C][C]-0.867[/C][C]0.194052[/C][/ROW]
[ROW][C]19[/C][C]-0.008623[/C][C]-0.0845[/C][C]0.466423[/C][/ROW]
[ROW][C]20[/C][C]-0.102298[/C][C]-1.0023[/C][C]0.159357[/C][/ROW]
[ROW][C]21[/C][C]0.085575[/C][C]0.8385[/C][C]0.201927[/C][/ROW]
[ROW][C]22[/C][C]-0.034355[/C][C]-0.3366[/C][C]0.368572[/C][/ROW]
[ROW][C]23[/C][C]-0.012638[/C][C]-0.1238[/C][C]0.450856[/C][/ROW]
[ROW][C]24[/C][C]-0.055019[/C][C]-0.5391[/C][C]0.295541[/C][/ROW]
[ROW][C]25[/C][C]-0.020125[/C][C]-0.1972[/C][C]0.422052[/C][/ROW]
[ROW][C]26[/C][C]-0.111207[/C][C]-1.0896[/C][C]0.139307[/C][/ROW]
[ROW][C]27[/C][C]0.06701[/C][C]0.6566[/C][C]0.256518[/C][/ROW]
[ROW][C]28[/C][C]-0.069188[/C][C]-0.6779[/C][C]0.249732[/C][/ROW]
[ROW][C]29[/C][C]-0.083764[/C][C]-0.8207[/C][C]0.20692[/C][/ROW]
[ROW][C]30[/C][C]-0.022922[/C][C]-0.2246[/C][C]0.411387[/C][/ROW]
[ROW][C]31[/C][C]0.13464[/C][C]1.3192[/C][C]0.09512[/C][/ROW]
[ROW][C]32[/C][C]-0.1045[/C][C]-1.0239[/C][C]0.154231[/C][/ROW]
[ROW][C]33[/C][C]-0.085449[/C][C]-0.8372[/C][C]0.202272[/C][/ROW]
[ROW][C]34[/C][C]0.036519[/C][C]0.3578[/C][C]0.360636[/C][/ROW]
[ROW][C]35[/C][C]-0.106341[/C][C]-1.0419[/C][C]0.150032[/C][/ROW]
[ROW][C]36[/C][C]0.068259[/C][C]0.6688[/C][C]0.252616[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70772&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70772&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
10.5797915.68080
20.0749520.73440.232256
30.4098354.01555.9e-05
40.0104380.10230.459376
50.3680223.60590.000248
60.1404551.37620.085985
70.0209940.20570.41873
8-0.04522-0.44310.329359
9-0.180892-1.77240.039753
10-0.402751-3.94617.6e-05
110.2287592.24140.013653
120.4803084.7064e-06
13-0.209725-2.05490.021304
14-0.155261-1.52120.065744
15-0.131318-1.28660.100655
160.1821291.78450.038751
17-0.027767-0.27210.393078
18-0.088488-0.8670.194052
19-0.008623-0.08450.466423
20-0.102298-1.00230.159357
210.0855750.83850.201927
22-0.034355-0.33660.368572
23-0.012638-0.12380.450856
24-0.055019-0.53910.295541
25-0.020125-0.19720.422052
26-0.111207-1.08960.139307
270.067010.65660.256518
28-0.069188-0.67790.249732
29-0.083764-0.82070.20692
30-0.022922-0.22460.411387
310.134641.31920.09512
32-0.1045-1.02390.154231
33-0.085449-0.83720.202272
340.0365190.35780.360636
35-0.106341-1.04190.150032
360.0682590.66880.252616


Figures (Output of Computation)

Input Parameters & R Code

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