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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 11:57:15 -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/Dec/26/t1261853877vx0tk1pjo915oy9.htm/, Retrieved Tue, 14 May 2024 17:14:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70773, Retrieved Tue, 14 May 2024 17:14:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

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] [0f0e461427f61416e46aeda5f4901bed]
-   P     [(Partial) Autocorrelation Function] [paper4 pacf d0D1] [2009-12-26 18:57:15] [b090d569c0a4c77894e0b029f4429f19] [Current]
-   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=70773&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=70773&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70773&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
10.7053666.46480
20.708716.49540
30.7228646.62520
40.4912444.50231.1e-05
50.4598454.21453.1e-05
60.3710743.4010.000515
70.2055891.88430.031495
80.2063751.89150.031005
90.0737710.67610.250409
100.0174510.15990.436654
110.0210960.19330.423577
12-0.042064-0.38550.350413
13-0.033234-0.30460.380713
140.0133540.12240.45144
15-0.028827-0.26420.396135
16-0.031843-0.29180.385561
170.0109310.10020.46022
180.0162440.14890.441004
19-0.037012-0.33920.367644
200.0452360.41460.339747
210.0220510.20210.420165
22-0.037353-0.34230.366474
230.060610.55550.290015
24-0.057049-0.52290.301223
25-0.054307-0.49770.309986
26-0.013728-0.12580.450088
27-0.124271-1.1390.128979
28-0.10041-0.92030.180032
29-0.105456-0.96650.168279
30-0.204603-1.87520.032119
31-0.170087-1.55890.061393
32-0.203421-1.86440.032881
33-0.230851-2.11580.018662
34-0.178-1.63140.053275
35-0.191477-1.75490.04146
36-0.168264-1.54220.063396

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.705366 & 6.4648 & 0 \tabularnewline
2 & 0.70871 & 6.4954 & 0 \tabularnewline
3 & 0.722864 & 6.6252 & 0 \tabularnewline
4 & 0.491244 & 4.5023 & 1.1e-05 \tabularnewline
5 & 0.459845 & 4.2145 & 3.1e-05 \tabularnewline
6 & 0.371074 & 3.401 & 0.000515 \tabularnewline
7 & 0.205589 & 1.8843 & 0.031495 \tabularnewline
8 & 0.206375 & 1.8915 & 0.031005 \tabularnewline
9 & 0.073771 & 0.6761 & 0.250409 \tabularnewline
10 & 0.017451 & 0.1599 & 0.436654 \tabularnewline
11 & 0.021096 & 0.1933 & 0.423577 \tabularnewline
12 & -0.042064 & -0.3855 & 0.350413 \tabularnewline
13 & -0.033234 & -0.3046 & 0.380713 \tabularnewline
14 & 0.013354 & 0.1224 & 0.45144 \tabularnewline
15 & -0.028827 & -0.2642 & 0.396135 \tabularnewline
16 & -0.031843 & -0.2918 & 0.385561 \tabularnewline
17 & 0.010931 & 0.1002 & 0.46022 \tabularnewline
18 & 0.016244 & 0.1489 & 0.441004 \tabularnewline
19 & -0.037012 & -0.3392 & 0.367644 \tabularnewline
20 & 0.045236 & 0.4146 & 0.339747 \tabularnewline
21 & 0.022051 & 0.2021 & 0.420165 \tabularnewline
22 & -0.037353 & -0.3423 & 0.366474 \tabularnewline
23 & 0.06061 & 0.5555 & 0.290015 \tabularnewline
24 & -0.057049 & -0.5229 & 0.301223 \tabularnewline
25 & -0.054307 & -0.4977 & 0.309986 \tabularnewline
26 & -0.013728 & -0.1258 & 0.450088 \tabularnewline
27 & -0.124271 & -1.139 & 0.128979 \tabularnewline
28 & -0.10041 & -0.9203 & 0.180032 \tabularnewline
29 & -0.105456 & -0.9665 & 0.168279 \tabularnewline
30 & -0.204603 & -1.8752 & 0.032119 \tabularnewline
31 & -0.170087 & -1.5589 & 0.061393 \tabularnewline
32 & -0.203421 & -1.8644 & 0.032881 \tabularnewline
33 & -0.230851 & -2.1158 & 0.018662 \tabularnewline
34 & -0.178 & -1.6314 & 0.053275 \tabularnewline
35 & -0.191477 & -1.7549 & 0.04146 \tabularnewline
36 & -0.168264 & -1.5422 & 0.063396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70773&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]0.705366[/C][C]6.4648[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.70871[/C][C]6.4954[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.722864[/C][C]6.6252[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.491244[/C][C]4.5023[/C][C]1.1e-05[/C][/ROW]
[ROW][C]5[/C][C]0.459845[/C][C]4.2145[/C][C]3.1e-05[/C][/ROW]
[ROW][C]6[/C][C]0.371074[/C][C]3.401[/C][C]0.000515[/C][/ROW]
[ROW][C]7[/C][C]0.205589[/C][C]1.8843[/C][C]0.031495[/C][/ROW]
[ROW][C]8[/C][C]0.206375[/C][C]1.8915[/C][C]0.031005[/C][/ROW]
[ROW][C]9[/C][C]0.073771[/C][C]0.6761[/C][C]0.250409[/C][/ROW]
[ROW][C]10[/C][C]0.017451[/C][C]0.1599[/C][C]0.436654[/C][/ROW]
[ROW][C]11[/C][C]0.021096[/C][C]0.1933[/C][C]0.423577[/C][/ROW]
[ROW][C]12[/C][C]-0.042064[/C][C]-0.3855[/C][C]0.350413[/C][/ROW]
[ROW][C]13[/C][C]-0.033234[/C][C]-0.3046[/C][C]0.380713[/C][/ROW]
[ROW][C]14[/C][C]0.013354[/C][C]0.1224[/C][C]0.45144[/C][/ROW]
[ROW][C]15[/C][C]-0.028827[/C][C]-0.2642[/C][C]0.396135[/C][/ROW]
[ROW][C]16[/C][C]-0.031843[/C][C]-0.2918[/C][C]0.385561[/C][/ROW]
[ROW][C]17[/C][C]0.010931[/C][C]0.1002[/C][C]0.46022[/C][/ROW]
[ROW][C]18[/C][C]0.016244[/C][C]0.1489[/C][C]0.441004[/C][/ROW]
[ROW][C]19[/C][C]-0.037012[/C][C]-0.3392[/C][C]0.367644[/C][/ROW]
[ROW][C]20[/C][C]0.045236[/C][C]0.4146[/C][C]0.339747[/C][/ROW]
[ROW][C]21[/C][C]0.022051[/C][C]0.2021[/C][C]0.420165[/C][/ROW]
[ROW][C]22[/C][C]-0.037353[/C][C]-0.3423[/C][C]0.366474[/C][/ROW]
[ROW][C]23[/C][C]0.06061[/C][C]0.5555[/C][C]0.290015[/C][/ROW]
[ROW][C]24[/C][C]-0.057049[/C][C]-0.5229[/C][C]0.301223[/C][/ROW]
[ROW][C]25[/C][C]-0.054307[/C][C]-0.4977[/C][C]0.309986[/C][/ROW]
[ROW][C]26[/C][C]-0.013728[/C][C]-0.1258[/C][C]0.450088[/C][/ROW]
[ROW][C]27[/C][C]-0.124271[/C][C]-1.139[/C][C]0.128979[/C][/ROW]
[ROW][C]28[/C][C]-0.10041[/C][C]-0.9203[/C][C]0.180032[/C][/ROW]
[ROW][C]29[/C][C]-0.105456[/C][C]-0.9665[/C][C]0.168279[/C][/ROW]
[ROW][C]30[/C][C]-0.204603[/C][C]-1.8752[/C][C]0.032119[/C][/ROW]
[ROW][C]31[/C][C]-0.170087[/C][C]-1.5589[/C][C]0.061393[/C][/ROW]
[ROW][C]32[/C][C]-0.203421[/C][C]-1.8644[/C][C]0.032881[/C][/ROW]
[ROW][C]33[/C][C]-0.230851[/C][C]-2.1158[/C][C]0.018662[/C][/ROW]
[ROW][C]34[/C][C]-0.178[/C][C]-1.6314[/C][C]0.053275[/C][/ROW]
[ROW][C]35[/C][C]-0.191477[/C][C]-1.7549[/C][C]0.04146[/C][/ROW]
[ROW][C]36[/C][C]-0.168264[/C][C]-1.5422[/C][C]0.063396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70773&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70773&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
10.7053666.46480
20.708716.49540
30.7228646.62520
40.4912444.50231.1e-05
50.4598454.21453.1e-05
60.3710743.4010.000515
70.2055891.88430.031495
80.2063751.89150.031005
90.0737710.67610.250409
100.0174510.15990.436654
110.0210960.19330.423577
12-0.042064-0.38550.350413
13-0.033234-0.30460.380713
140.0133540.12240.45144
15-0.028827-0.26420.396135
16-0.031843-0.29180.385561
170.0109310.10020.46022
180.0162440.14890.441004
19-0.037012-0.33920.367644
200.0452360.41460.339747
210.0220510.20210.420165
22-0.037353-0.34230.366474
230.060610.55550.290015
24-0.057049-0.52290.301223
25-0.054307-0.49770.309986
26-0.013728-0.12580.450088
27-0.124271-1.1390.128979
28-0.10041-0.92030.180032
29-0.105456-0.96650.168279
30-0.204603-1.87520.032119
31-0.170087-1.55890.061393
32-0.203421-1.86440.032881
33-0.230851-2.11580.018662
34-0.178-1.63140.053275
35-0.191477-1.75490.04146
36-0.168264-1.54220.063396






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7053666.46480
20.4202723.85190.000114
30.3302123.02640.001642
4-0.377389-3.45880.000427
5-0.184001-1.68640.047715
6-0.096498-0.88440.189497
7-0.067456-0.61820.269043
80.1214081.11270.134501
9-0.075891-0.69550.244316
100.0279740.25640.399141
110.0369190.33840.367965
120.0980050.89820.185816
130.0391810.35910.360211
140.1060760.97220.16687
15-0.062941-0.57690.282786
16-0.232677-2.13250.017942
17-0.03021-0.27690.391276
180.175241.60610.056003
19-0.091227-0.83610.202733
200.0986170.90380.184333
210.0146720.13450.446677
22-0.148415-1.36020.088696
230.1316711.20680.115451
24-0.178244-1.63360.05304
25-0.020323-0.18630.426343
26-0.026438-0.24230.404567
270.0089190.08170.467524
28-0.09799-0.89810.185851
290.0177310.16250.435648
30-0.003413-0.03130.487558
31-0.125388-1.14920.126867
320.0422080.38680.349925
330.1052090.96430.168844
340.0426840.39120.348318
350.0100650.09230.463359
360.0147160.13490.446516

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.705366 & 6.4648 & 0 \tabularnewline
2 & 0.420272 & 3.8519 & 0.000114 \tabularnewline
3 & 0.330212 & 3.0264 & 0.001642 \tabularnewline
4 & -0.377389 & -3.4588 & 0.000427 \tabularnewline
5 & -0.184001 & -1.6864 & 0.047715 \tabularnewline
6 & -0.096498 & -0.8844 & 0.189497 \tabularnewline
7 & -0.067456 & -0.6182 & 0.269043 \tabularnewline
8 & 0.121408 & 1.1127 & 0.134501 \tabularnewline
9 & -0.075891 & -0.6955 & 0.244316 \tabularnewline
10 & 0.027974 & 0.2564 & 0.399141 \tabularnewline
11 & 0.036919 & 0.3384 & 0.367965 \tabularnewline
12 & 0.098005 & 0.8982 & 0.185816 \tabularnewline
13 & 0.039181 & 0.3591 & 0.360211 \tabularnewline
14 & 0.106076 & 0.9722 & 0.16687 \tabularnewline
15 & -0.062941 & -0.5769 & 0.282786 \tabularnewline
16 & -0.232677 & -2.1325 & 0.017942 \tabularnewline
17 & -0.03021 & -0.2769 & 0.391276 \tabularnewline
18 & 0.17524 & 1.6061 & 0.056003 \tabularnewline
19 & -0.091227 & -0.8361 & 0.202733 \tabularnewline
20 & 0.098617 & 0.9038 & 0.184333 \tabularnewline
21 & 0.014672 & 0.1345 & 0.446677 \tabularnewline
22 & -0.148415 & -1.3602 & 0.088696 \tabularnewline
23 & 0.131671 & 1.2068 & 0.115451 \tabularnewline
24 & -0.178244 & -1.6336 & 0.05304 \tabularnewline
25 & -0.020323 & -0.1863 & 0.426343 \tabularnewline
26 & -0.026438 & -0.2423 & 0.404567 \tabularnewline
27 & 0.008919 & 0.0817 & 0.467524 \tabularnewline
28 & -0.09799 & -0.8981 & 0.185851 \tabularnewline
29 & 0.017731 & 0.1625 & 0.435648 \tabularnewline
30 & -0.003413 & -0.0313 & 0.487558 \tabularnewline
31 & -0.125388 & -1.1492 & 0.126867 \tabularnewline
32 & 0.042208 & 0.3868 & 0.349925 \tabularnewline
33 & 0.105209 & 0.9643 & 0.168844 \tabularnewline
34 & 0.042684 & 0.3912 & 0.348318 \tabularnewline
35 & 0.010065 & 0.0923 & 0.463359 \tabularnewline
36 & 0.014716 & 0.1349 & 0.446516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70773&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]0.705366[/C][C]6.4648[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.420272[/C][C]3.8519[/C][C]0.000114[/C][/ROW]
[ROW][C]3[/C][C]0.330212[/C][C]3.0264[/C][C]0.001642[/C][/ROW]
[ROW][C]4[/C][C]-0.377389[/C][C]-3.4588[/C][C]0.000427[/C][/ROW]
[ROW][C]5[/C][C]-0.184001[/C][C]-1.6864[/C][C]0.047715[/C][/ROW]
[ROW][C]6[/C][C]-0.096498[/C][C]-0.8844[/C][C]0.189497[/C][/ROW]
[ROW][C]7[/C][C]-0.067456[/C][C]-0.6182[/C][C]0.269043[/C][/ROW]
[ROW][C]8[/C][C]0.121408[/C][C]1.1127[/C][C]0.134501[/C][/ROW]
[ROW][C]9[/C][C]-0.075891[/C][C]-0.6955[/C][C]0.244316[/C][/ROW]
[ROW][C]10[/C][C]0.027974[/C][C]0.2564[/C][C]0.399141[/C][/ROW]
[ROW][C]11[/C][C]0.036919[/C][C]0.3384[/C][C]0.367965[/C][/ROW]
[ROW][C]12[/C][C]0.098005[/C][C]0.8982[/C][C]0.185816[/C][/ROW]
[ROW][C]13[/C][C]0.039181[/C][C]0.3591[/C][C]0.360211[/C][/ROW]
[ROW][C]14[/C][C]0.106076[/C][C]0.9722[/C][C]0.16687[/C][/ROW]
[ROW][C]15[/C][C]-0.062941[/C][C]-0.5769[/C][C]0.282786[/C][/ROW]
[ROW][C]16[/C][C]-0.232677[/C][C]-2.1325[/C][C]0.017942[/C][/ROW]
[ROW][C]17[/C][C]-0.03021[/C][C]-0.2769[/C][C]0.391276[/C][/ROW]
[ROW][C]18[/C][C]0.17524[/C][C]1.6061[/C][C]0.056003[/C][/ROW]
[ROW][C]19[/C][C]-0.091227[/C][C]-0.8361[/C][C]0.202733[/C][/ROW]
[ROW][C]20[/C][C]0.098617[/C][C]0.9038[/C][C]0.184333[/C][/ROW]
[ROW][C]21[/C][C]0.014672[/C][C]0.1345[/C][C]0.446677[/C][/ROW]
[ROW][C]22[/C][C]-0.148415[/C][C]-1.3602[/C][C]0.088696[/C][/ROW]
[ROW][C]23[/C][C]0.131671[/C][C]1.2068[/C][C]0.115451[/C][/ROW]
[ROW][C]24[/C][C]-0.178244[/C][C]-1.6336[/C][C]0.05304[/C][/ROW]
[ROW][C]25[/C][C]-0.020323[/C][C]-0.1863[/C][C]0.426343[/C][/ROW]
[ROW][C]26[/C][C]-0.026438[/C][C]-0.2423[/C][C]0.404567[/C][/ROW]
[ROW][C]27[/C][C]0.008919[/C][C]0.0817[/C][C]0.467524[/C][/ROW]
[ROW][C]28[/C][C]-0.09799[/C][C]-0.8981[/C][C]0.185851[/C][/ROW]
[ROW][C]29[/C][C]0.017731[/C][C]0.1625[/C][C]0.435648[/C][/ROW]
[ROW][C]30[/C][C]-0.003413[/C][C]-0.0313[/C][C]0.487558[/C][/ROW]
[ROW][C]31[/C][C]-0.125388[/C][C]-1.1492[/C][C]0.126867[/C][/ROW]
[ROW][C]32[/C][C]0.042208[/C][C]0.3868[/C][C]0.349925[/C][/ROW]
[ROW][C]33[/C][C]0.105209[/C][C]0.9643[/C][C]0.168844[/C][/ROW]
[ROW][C]34[/C][C]0.042684[/C][C]0.3912[/C][C]0.348318[/C][/ROW]
[ROW][C]35[/C][C]0.010065[/C][C]0.0923[/C][C]0.463359[/C][/ROW]
[ROW][C]36[/C][C]0.014716[/C][C]0.1349[/C][C]0.446516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70773&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70773&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
10.7053666.46480
20.4202723.85190.000114
30.3302123.02640.001642
4-0.377389-3.45880.000427
5-0.184001-1.68640.047715
6-0.096498-0.88440.189497
7-0.067456-0.61820.269043
80.1214081.11270.134501
9-0.075891-0.69550.244316
100.0279740.25640.399141
110.0369190.33840.367965
120.0980050.89820.185816
130.0391810.35910.360211
140.1060760.97220.16687
15-0.062941-0.57690.282786
16-0.232677-2.13250.017942
17-0.03021-0.27690.391276
180.175241.60610.056003
19-0.091227-0.83610.202733
200.0986170.90380.184333
210.0146720.13450.446677
22-0.148415-1.36020.088696
230.1316711.20680.115451
24-0.178244-1.63360.05304
25-0.020323-0.18630.426343
26-0.026438-0.24230.404567
270.0089190.08170.467524
28-0.09799-0.89810.185851
290.0177310.16250.435648
30-0.003413-0.03130.487558
31-0.125388-1.14920.126867
320.0422080.38680.349925
330.1052090.96430.168844
340.0426840.39120.348318
350.0100650.09230.463359
360.0147160.13490.446516


Figures (Output of Computation)

Input Parameters & R Code

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