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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 24 Dec 2008 07:47:06 -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/24/t12301300678zblmy3o9b1h5ff.htm/, Retrieved Sun, 19 May 2024 10:51:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36598, Retrieved Sun, 19 May 2024 10:51:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD  [Variance Reduction Matrix] [Identification an...] [2008-12-09 21:59:36] [1a689e9ccc515e1757f0522229a687e9]
-    D    [Variance Reduction Matrix] [Paper Variance Re...] [2008-12-24 14:39:33] [1a689e9ccc515e1757f0522229a687e9]
- RMPD      [(Partial) Autocorrelation Function] [Paper Autocorrela...] [2008-12-24 14:44:07] [1a689e9ccc515e1757f0522229a687e9]
-   P           [(Partial) Autocorrelation Function] [Paper Variance Re...] [2008-12-24 14:47:06] [74a138e5b32af267311b5ad4cd13bf7e] [Current]
-   P             [(Partial) Autocorrelation Function] [Paper Autocorrela...] [2008-12-24 14:50:15] [1a689e9ccc515e1757f0522229a687e9]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105.7
109.5
105.3
102.8
100.6
97.6
110.3
107.2
107.2
108.1
97.1
92.2
112.2
111.6
115.7
111.3
104.2
103.2
112.7
106.4
102.6
110.6
95.2
89
112.5
116.8
107.2
113.6
101.8
102.6
122.7
110.3
110.5
121.6
100.3
100.7
123.4
127.1
124.1
131.2
111.6
114.2
130.1
125.9
119
133.8
107.5
113.5
134.4
126.8
135.6
139.9
129.8
131
153.1
134.1
144.1
155.9
123.3
128.1
144.3
153
149.9
150.9
141
138.9
157.4
142.9
151.7
161
138.5
135.9
151.5
164
159.1
157
142.1
144.8
152.1
154.6
148.7
157.7
146.4
136.5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36598&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36598&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36598&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4868354.13094.8e-05
20.5807764.9283e-06
30.546964.64118e-06
40.421423.57590.000314
50.4204623.56770.000323
60.3186142.70350.004277
70.2600442.20650.015268
80.1704091.4460.076263
90.2482052.10610.019342
100.0362930.3080.379503
110.0788780.66930.252723
12-0.020614-0.17490.430819
130.0301380.25570.399443
140.0516430.43820.331276
15-0.010554-0.08960.464445
16-0.001323-0.01120.495536
17-0.067888-0.57610.283188
180.0454510.38570.350442
19-0.169679-1.43980.077133
20-0.102416-0.8690.193858
21-0.108887-0.92390.179303
22-0.158893-1.34830.090902
23-0.067821-0.57550.28338
24-0.246681-2.09320.019929
25-0.201263-1.70780.045993
26-0.207477-1.76050.041285
27-0.227309-1.92880.02885
28-0.27933-2.37020.01023
29-0.170743-1.44880.075867
30-0.311242-2.6410.005066
31-0.220214-1.86860.032875
32-0.2078-1.76320.041051
33-0.323614-2.7460.003808
34-0.262034-2.22340.014663
35-0.311674-2.64460.005016
36-0.242714-2.05950.021532

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.486835 & 4.1309 & 4.8e-05 \tabularnewline
2 & 0.580776 & 4.928 & 3e-06 \tabularnewline
3 & 0.54696 & 4.6411 & 8e-06 \tabularnewline
4 & 0.42142 & 3.5759 & 0.000314 \tabularnewline
5 & 0.420462 & 3.5677 & 0.000323 \tabularnewline
6 & 0.318614 & 2.7035 & 0.004277 \tabularnewline
7 & 0.260044 & 2.2065 & 0.015268 \tabularnewline
8 & 0.170409 & 1.446 & 0.076263 \tabularnewline
9 & 0.248205 & 2.1061 & 0.019342 \tabularnewline
10 & 0.036293 & 0.308 & 0.379503 \tabularnewline
11 & 0.078878 & 0.6693 & 0.252723 \tabularnewline
12 & -0.020614 & -0.1749 & 0.430819 \tabularnewline
13 & 0.030138 & 0.2557 & 0.399443 \tabularnewline
14 & 0.051643 & 0.4382 & 0.331276 \tabularnewline
15 & -0.010554 & -0.0896 & 0.464445 \tabularnewline
16 & -0.001323 & -0.0112 & 0.495536 \tabularnewline
17 & -0.067888 & -0.5761 & 0.283188 \tabularnewline
18 & 0.045451 & 0.3857 & 0.350442 \tabularnewline
19 & -0.169679 & -1.4398 & 0.077133 \tabularnewline
20 & -0.102416 & -0.869 & 0.193858 \tabularnewline
21 & -0.108887 & -0.9239 & 0.179303 \tabularnewline
22 & -0.158893 & -1.3483 & 0.090902 \tabularnewline
23 & -0.067821 & -0.5755 & 0.28338 \tabularnewline
24 & -0.246681 & -2.0932 & 0.019929 \tabularnewline
25 & -0.201263 & -1.7078 & 0.045993 \tabularnewline
26 & -0.207477 & -1.7605 & 0.041285 \tabularnewline
27 & -0.227309 & -1.9288 & 0.02885 \tabularnewline
28 & -0.27933 & -2.3702 & 0.01023 \tabularnewline
29 & -0.170743 & -1.4488 & 0.075867 \tabularnewline
30 & -0.311242 & -2.641 & 0.005066 \tabularnewline
31 & -0.220214 & -1.8686 & 0.032875 \tabularnewline
32 & -0.2078 & -1.7632 & 0.041051 \tabularnewline
33 & -0.323614 & -2.746 & 0.003808 \tabularnewline
34 & -0.262034 & -2.2234 & 0.014663 \tabularnewline
35 & -0.311674 & -2.6446 & 0.005016 \tabularnewline
36 & -0.242714 & -2.0595 & 0.021532 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36598&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]0.486835[/C][C]4.1309[/C][C]4.8e-05[/C][/ROW]
[ROW][C]2[/C][C]0.580776[/C][C]4.928[/C][C]3e-06[/C][/ROW]
[ROW][C]3[/C][C]0.54696[/C][C]4.6411[/C][C]8e-06[/C][/ROW]
[ROW][C]4[/C][C]0.42142[/C][C]3.5759[/C][C]0.000314[/C][/ROW]
[ROW][C]5[/C][C]0.420462[/C][C]3.5677[/C][C]0.000323[/C][/ROW]
[ROW][C]6[/C][C]0.318614[/C][C]2.7035[/C][C]0.004277[/C][/ROW]
[ROW][C]7[/C][C]0.260044[/C][C]2.2065[/C][C]0.015268[/C][/ROW]
[ROW][C]8[/C][C]0.170409[/C][C]1.446[/C][C]0.076263[/C][/ROW]
[ROW][C]9[/C][C]0.248205[/C][C]2.1061[/C][C]0.019342[/C][/ROW]
[ROW][C]10[/C][C]0.036293[/C][C]0.308[/C][C]0.379503[/C][/ROW]
[ROW][C]11[/C][C]0.078878[/C][C]0.6693[/C][C]0.252723[/C][/ROW]
[ROW][C]12[/C][C]-0.020614[/C][C]-0.1749[/C][C]0.430819[/C][/ROW]
[ROW][C]13[/C][C]0.030138[/C][C]0.2557[/C][C]0.399443[/C][/ROW]
[ROW][C]14[/C][C]0.051643[/C][C]0.4382[/C][C]0.331276[/C][/ROW]
[ROW][C]15[/C][C]-0.010554[/C][C]-0.0896[/C][C]0.464445[/C][/ROW]
[ROW][C]16[/C][C]-0.001323[/C][C]-0.0112[/C][C]0.495536[/C][/ROW]
[ROW][C]17[/C][C]-0.067888[/C][C]-0.5761[/C][C]0.283188[/C][/ROW]
[ROW][C]18[/C][C]0.045451[/C][C]0.3857[/C][C]0.350442[/C][/ROW]
[ROW][C]19[/C][C]-0.169679[/C][C]-1.4398[/C][C]0.077133[/C][/ROW]
[ROW][C]20[/C][C]-0.102416[/C][C]-0.869[/C][C]0.193858[/C][/ROW]
[ROW][C]21[/C][C]-0.108887[/C][C]-0.9239[/C][C]0.179303[/C][/ROW]
[ROW][C]22[/C][C]-0.158893[/C][C]-1.3483[/C][C]0.090902[/C][/ROW]
[ROW][C]23[/C][C]-0.067821[/C][C]-0.5755[/C][C]0.28338[/C][/ROW]
[ROW][C]24[/C][C]-0.246681[/C][C]-2.0932[/C][C]0.019929[/C][/ROW]
[ROW][C]25[/C][C]-0.201263[/C][C]-1.7078[/C][C]0.045993[/C][/ROW]
[ROW][C]26[/C][C]-0.207477[/C][C]-1.7605[/C][C]0.041285[/C][/ROW]
[ROW][C]27[/C][C]-0.227309[/C][C]-1.9288[/C][C]0.02885[/C][/ROW]
[ROW][C]28[/C][C]-0.27933[/C][C]-2.3702[/C][C]0.01023[/C][/ROW]
[ROW][C]29[/C][C]-0.170743[/C][C]-1.4488[/C][C]0.075867[/C][/ROW]
[ROW][C]30[/C][C]-0.311242[/C][C]-2.641[/C][C]0.005066[/C][/ROW]
[ROW][C]31[/C][C]-0.220214[/C][C]-1.8686[/C][C]0.032875[/C][/ROW]
[ROW][C]32[/C][C]-0.2078[/C][C]-1.7632[/C][C]0.041051[/C][/ROW]
[ROW][C]33[/C][C]-0.323614[/C][C]-2.746[/C][C]0.003808[/C][/ROW]
[ROW][C]34[/C][C]-0.262034[/C][C]-2.2234[/C][C]0.014663[/C][/ROW]
[ROW][C]35[/C][C]-0.311674[/C][C]-2.6446[/C][C]0.005016[/C][/ROW]
[ROW][C]36[/C][C]-0.242714[/C][C]-2.0595[/C][C]0.021532[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36598&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36598&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
10.4868354.13094.8e-05
20.5807764.9283e-06
30.546964.64118e-06
40.421423.57590.000314
50.4204623.56770.000323
60.3186142.70350.004277
70.2600442.20650.015268
80.1704091.4460.076263
90.2482052.10610.019342
100.0362930.3080.379503
110.0788780.66930.252723
12-0.020614-0.17490.430819
130.0301380.25570.399443
140.0516430.43820.331276
15-0.010554-0.08960.464445
16-0.001323-0.01120.495536
17-0.067888-0.57610.283188
180.0454510.38570.350442
19-0.169679-1.43980.077133
20-0.102416-0.8690.193858
21-0.108887-0.92390.179303
22-0.158893-1.34830.090902
23-0.067821-0.57550.28338
24-0.246681-2.09320.019929
25-0.201263-1.70780.045993
26-0.207477-1.76050.041285
27-0.227309-1.92880.02885
28-0.27933-2.37020.01023
29-0.170743-1.44880.075867
30-0.311242-2.6410.005066
31-0.220214-1.86860.032875
32-0.2078-1.76320.041051
33-0.323614-2.7460.003808
34-0.262034-2.22340.014663
35-0.311674-2.64460.005016
36-0.242714-2.05950.021532






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4868354.13094.8e-05
20.4505513.82310.000139
30.2832792.40370.009403
4-0.019039-0.16160.436055
5-0.011519-0.09770.461206
6-0.085527-0.72570.235181
7-0.085433-0.72490.235424
8-0.132008-1.12010.133192
90.1680931.42630.07905
10-0.151188-1.28290.101826
11-0.041297-0.35040.363526
12-0.123572-1.04850.148948
130.1581481.34190.091918
140.1557351.32150.095266
150.0449110.38110.352131
16-0.088616-0.75190.227271
17-0.150093-1.27360.103454
180.0608730.51650.303535
19-0.233347-1.980.025762
20-0.113881-0.96630.16856
210.0846160.7180.237544
220.0279580.23720.406575
230.10960.930.177743
24-0.224346-1.90360.030477
25-0.068172-0.57850.282381
260.0649650.55120.291586
27-0.051246-0.43480.33249
28-0.071836-0.60950.272041
290.1261251.07020.14405
30-0.148426-1.25940.105971
31-0.095697-0.8120.209729
32-0.106666-0.90510.184218
330.0425790.36130.35947
34-0.047356-0.40180.3445
35-0.079472-0.67430.251126
36-0.034444-0.29230.385463

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.486835 & 4.1309 & 4.8e-05 \tabularnewline
2 & 0.450551 & 3.8231 & 0.000139 \tabularnewline
3 & 0.283279 & 2.4037 & 0.009403 \tabularnewline
4 & -0.019039 & -0.1616 & 0.436055 \tabularnewline
5 & -0.011519 & -0.0977 & 0.461206 \tabularnewline
6 & -0.085527 & -0.7257 & 0.235181 \tabularnewline
7 & -0.085433 & -0.7249 & 0.235424 \tabularnewline
8 & -0.132008 & -1.1201 & 0.133192 \tabularnewline
9 & 0.168093 & 1.4263 & 0.07905 \tabularnewline
10 & -0.151188 & -1.2829 & 0.101826 \tabularnewline
11 & -0.041297 & -0.3504 & 0.363526 \tabularnewline
12 & -0.123572 & -1.0485 & 0.148948 \tabularnewline
13 & 0.158148 & 1.3419 & 0.091918 \tabularnewline
14 & 0.155735 & 1.3215 & 0.095266 \tabularnewline
15 & 0.044911 & 0.3811 & 0.352131 \tabularnewline
16 & -0.088616 & -0.7519 & 0.227271 \tabularnewline
17 & -0.150093 & -1.2736 & 0.103454 \tabularnewline
18 & 0.060873 & 0.5165 & 0.303535 \tabularnewline
19 & -0.233347 & -1.98 & 0.025762 \tabularnewline
20 & -0.113881 & -0.9663 & 0.16856 \tabularnewline
21 & 0.084616 & 0.718 & 0.237544 \tabularnewline
22 & 0.027958 & 0.2372 & 0.406575 \tabularnewline
23 & 0.1096 & 0.93 & 0.177743 \tabularnewline
24 & -0.224346 & -1.9036 & 0.030477 \tabularnewline
25 & -0.068172 & -0.5785 & 0.282381 \tabularnewline
26 & 0.064965 & 0.5512 & 0.291586 \tabularnewline
27 & -0.051246 & -0.4348 & 0.33249 \tabularnewline
28 & -0.071836 & -0.6095 & 0.272041 \tabularnewline
29 & 0.126125 & 1.0702 & 0.14405 \tabularnewline
30 & -0.148426 & -1.2594 & 0.105971 \tabularnewline
31 & -0.095697 & -0.812 & 0.209729 \tabularnewline
32 & -0.106666 & -0.9051 & 0.184218 \tabularnewline
33 & 0.042579 & 0.3613 & 0.35947 \tabularnewline
34 & -0.047356 & -0.4018 & 0.3445 \tabularnewline
35 & -0.079472 & -0.6743 & 0.251126 \tabularnewline
36 & -0.034444 & -0.2923 & 0.385463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36598&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]0.486835[/C][C]4.1309[/C][C]4.8e-05[/C][/ROW]
[ROW][C]2[/C][C]0.450551[/C][C]3.8231[/C][C]0.000139[/C][/ROW]
[ROW][C]3[/C][C]0.283279[/C][C]2.4037[/C][C]0.009403[/C][/ROW]
[ROW][C]4[/C][C]-0.019039[/C][C]-0.1616[/C][C]0.436055[/C][/ROW]
[ROW][C]5[/C][C]-0.011519[/C][C]-0.0977[/C][C]0.461206[/C][/ROW]
[ROW][C]6[/C][C]-0.085527[/C][C]-0.7257[/C][C]0.235181[/C][/ROW]
[ROW][C]7[/C][C]-0.085433[/C][C]-0.7249[/C][C]0.235424[/C][/ROW]
[ROW][C]8[/C][C]-0.132008[/C][C]-1.1201[/C][C]0.133192[/C][/ROW]
[ROW][C]9[/C][C]0.168093[/C][C]1.4263[/C][C]0.07905[/C][/ROW]
[ROW][C]10[/C][C]-0.151188[/C][C]-1.2829[/C][C]0.101826[/C][/ROW]
[ROW][C]11[/C][C]-0.041297[/C][C]-0.3504[/C][C]0.363526[/C][/ROW]
[ROW][C]12[/C][C]-0.123572[/C][C]-1.0485[/C][C]0.148948[/C][/ROW]
[ROW][C]13[/C][C]0.158148[/C][C]1.3419[/C][C]0.091918[/C][/ROW]
[ROW][C]14[/C][C]0.155735[/C][C]1.3215[/C][C]0.095266[/C][/ROW]
[ROW][C]15[/C][C]0.044911[/C][C]0.3811[/C][C]0.352131[/C][/ROW]
[ROW][C]16[/C][C]-0.088616[/C][C]-0.7519[/C][C]0.227271[/C][/ROW]
[ROW][C]17[/C][C]-0.150093[/C][C]-1.2736[/C][C]0.103454[/C][/ROW]
[ROW][C]18[/C][C]0.060873[/C][C]0.5165[/C][C]0.303535[/C][/ROW]
[ROW][C]19[/C][C]-0.233347[/C][C]-1.98[/C][C]0.025762[/C][/ROW]
[ROW][C]20[/C][C]-0.113881[/C][C]-0.9663[/C][C]0.16856[/C][/ROW]
[ROW][C]21[/C][C]0.084616[/C][C]0.718[/C][C]0.237544[/C][/ROW]
[ROW][C]22[/C][C]0.027958[/C][C]0.2372[/C][C]0.406575[/C][/ROW]
[ROW][C]23[/C][C]0.1096[/C][C]0.93[/C][C]0.177743[/C][/ROW]
[ROW][C]24[/C][C]-0.224346[/C][C]-1.9036[/C][C]0.030477[/C][/ROW]
[ROW][C]25[/C][C]-0.068172[/C][C]-0.5785[/C][C]0.282381[/C][/ROW]
[ROW][C]26[/C][C]0.064965[/C][C]0.5512[/C][C]0.291586[/C][/ROW]
[ROW][C]27[/C][C]-0.051246[/C][C]-0.4348[/C][C]0.33249[/C][/ROW]
[ROW][C]28[/C][C]-0.071836[/C][C]-0.6095[/C][C]0.272041[/C][/ROW]
[ROW][C]29[/C][C]0.126125[/C][C]1.0702[/C][C]0.14405[/C][/ROW]
[ROW][C]30[/C][C]-0.148426[/C][C]-1.2594[/C][C]0.105971[/C][/ROW]
[ROW][C]31[/C][C]-0.095697[/C][C]-0.812[/C][C]0.209729[/C][/ROW]
[ROW][C]32[/C][C]-0.106666[/C][C]-0.9051[/C][C]0.184218[/C][/ROW]
[ROW][C]33[/C][C]0.042579[/C][C]0.3613[/C][C]0.35947[/C][/ROW]
[ROW][C]34[/C][C]-0.047356[/C][C]-0.4018[/C][C]0.3445[/C][/ROW]
[ROW][C]35[/C][C]-0.079472[/C][C]-0.6743[/C][C]0.251126[/C][/ROW]
[ROW][C]36[/C][C]-0.034444[/C][C]-0.2923[/C][C]0.385463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36598&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36598&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
10.4868354.13094.8e-05
20.4505513.82310.000139
30.2832792.40370.009403
4-0.019039-0.16160.436055
5-0.011519-0.09770.461206
6-0.085527-0.72570.235181
7-0.085433-0.72490.235424
8-0.132008-1.12010.133192
90.1680931.42630.07905
10-0.151188-1.28290.101826
11-0.041297-0.35040.363526
12-0.123572-1.04850.148948
130.1581481.34190.091918
140.1557351.32150.095266
150.0449110.38110.352131
16-0.088616-0.75190.227271
17-0.150093-1.27360.103454
180.0608730.51650.303535
19-0.233347-1.980.025762
20-0.113881-0.96630.16856
210.0846160.7180.237544
220.0279580.23720.406575
230.10960.930.177743
24-0.224346-1.90360.030477
25-0.068172-0.57850.282381
260.0649650.55120.291586
27-0.051246-0.43480.33249
28-0.071836-0.60950.272041
290.1261251.07020.14405
30-0.148426-1.25940.105971
31-0.095697-0.8120.209729
32-0.106666-0.90510.184218
330.0425790.36130.35947
34-0.047356-0.40180.3445
35-0.079472-0.67430.251126
36-0.034444-0.29230.385463


Figures (Output of Computation)

Input Parameters & R Code

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