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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 computationTue, 02 Dec 2008 12:48:42 -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/02/t1228247377w2gycht35ndv3m0.htm/, Retrieved Sun, 19 May 2024 11:39:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28283, Retrieved Sun, 19 May 2024 11:39:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [nsts Q8] [2008-12-02 19:40:41] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMPD  [(Partial) Autocorrelation Function] [nsts Q8] [2008-12-02 19:45:13] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F   P       [(Partial) Autocorrelation Function] [nsts Q8] [2008-12-02 19:48:42] [821c4b3d195be8e737cf8c9dc649d3cf] [Current]
Feedback Forum
2008-12-09 23:32:09 [Gert-Jan Geudens] [reply] 
Correct. Je hebt inderdaad een stationaire reeks bekomen door enkel lineair te differentiëren.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
109.57
107.08
110.33
110.36
106.5
104.3
107.21
109.34
108.2
109.86
108.68
113.38
117.12
116.23
114.75
115.81
115.86
117.8
117.11
116.31
118.38
121.57
121.65
124.2
126.12
128.6
128.16
130.12
135.83
138.05
134.99
132.38
128.94
128.12
127.84
132.43
134.13
134.78
133.13
129.08
134.48
132.86
134.08
134.54
134.51
135.97
136.09
139.14
135.63
136.55
138.83
138.84
135.37
132.22
134.75
135.98
136.06
138.05
139.59
140.58

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=28283&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=28283&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28283&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
10.0465380.35750.361009
2-0.187322-1.43880.077739
3-0.147004-1.12920.1317
40.0019860.01530.493941
50.0715490.54960.292342
6-0.136628-1.04950.149123
70.0515430.39590.346799
8-0.091914-0.7060.241482
90.0642660.49360.311697
10-0.06536-0.5020.308755
11-0.09732-0.74750.228856
120.0834260.64080.262065
13-0.046323-0.35580.361624
140.1269870.97540.166671
150.0223770.17190.43206
16-0.040631-0.31210.378035
170.0367620.28240.389322
18-0.016215-0.12460.45065
19-0.006553-0.05030.480013
20-0.107151-0.8230.206899
21-0.004312-0.03310.486845
220.1251220.96110.170218
23-0.019571-0.15030.44051
24-0.19213-1.47580.07266
25-0.074166-0.56970.285529
260.0800470.61490.270509
27-0.106908-0.82120.207426
28-0.043998-0.3380.368298
290.1372791.05450.147986
30-0.01081-0.0830.467052
31-0.03112-0.2390.405951
32-0.132588-1.01840.156317
330.0728840.55980.288856
340.1421341.09180.13969
350.0278990.21430.415527
36-0.076294-0.5860.280046

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.046538 & 0.3575 & 0.361009 \tabularnewline
2 & -0.187322 & -1.4388 & 0.077739 \tabularnewline
3 & -0.147004 & -1.1292 & 0.1317 \tabularnewline
4 & 0.001986 & 0.0153 & 0.493941 \tabularnewline
5 & 0.071549 & 0.5496 & 0.292342 \tabularnewline
6 & -0.136628 & -1.0495 & 0.149123 \tabularnewline
7 & 0.051543 & 0.3959 & 0.346799 \tabularnewline
8 & -0.091914 & -0.706 & 0.241482 \tabularnewline
9 & 0.064266 & 0.4936 & 0.311697 \tabularnewline
10 & -0.06536 & -0.502 & 0.308755 \tabularnewline
11 & -0.09732 & -0.7475 & 0.228856 \tabularnewline
12 & 0.083426 & 0.6408 & 0.262065 \tabularnewline
13 & -0.046323 & -0.3558 & 0.361624 \tabularnewline
14 & 0.126987 & 0.9754 & 0.166671 \tabularnewline
15 & 0.022377 & 0.1719 & 0.43206 \tabularnewline
16 & -0.040631 & -0.3121 & 0.378035 \tabularnewline
17 & 0.036762 & 0.2824 & 0.389322 \tabularnewline
18 & -0.016215 & -0.1246 & 0.45065 \tabularnewline
19 & -0.006553 & -0.0503 & 0.480013 \tabularnewline
20 & -0.107151 & -0.823 & 0.206899 \tabularnewline
21 & -0.004312 & -0.0331 & 0.486845 \tabularnewline
22 & 0.125122 & 0.9611 & 0.170218 \tabularnewline
23 & -0.019571 & -0.1503 & 0.44051 \tabularnewline
24 & -0.19213 & -1.4758 & 0.07266 \tabularnewline
25 & -0.074166 & -0.5697 & 0.285529 \tabularnewline
26 & 0.080047 & 0.6149 & 0.270509 \tabularnewline
27 & -0.106908 & -0.8212 & 0.207426 \tabularnewline
28 & -0.043998 & -0.338 & 0.368298 \tabularnewline
29 & 0.137279 & 1.0545 & 0.147986 \tabularnewline
30 & -0.01081 & -0.083 & 0.467052 \tabularnewline
31 & -0.03112 & -0.239 & 0.405951 \tabularnewline
32 & -0.132588 & -1.0184 & 0.156317 \tabularnewline
33 & 0.072884 & 0.5598 & 0.288856 \tabularnewline
34 & 0.142134 & 1.0918 & 0.13969 \tabularnewline
35 & 0.027899 & 0.2143 & 0.415527 \tabularnewline
36 & -0.076294 & -0.586 & 0.280046 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28283&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]0.046538[/C][C]0.3575[/C][C]0.361009[/C][/ROW]
[ROW][C]2[/C][C]-0.187322[/C][C]-1.4388[/C][C]0.077739[/C][/ROW]
[ROW][C]3[/C][C]-0.147004[/C][C]-1.1292[/C][C]0.1317[/C][/ROW]
[ROW][C]4[/C][C]0.001986[/C][C]0.0153[/C][C]0.493941[/C][/ROW]
[ROW][C]5[/C][C]0.071549[/C][C]0.5496[/C][C]0.292342[/C][/ROW]
[ROW][C]6[/C][C]-0.136628[/C][C]-1.0495[/C][C]0.149123[/C][/ROW]
[ROW][C]7[/C][C]0.051543[/C][C]0.3959[/C][C]0.346799[/C][/ROW]
[ROW][C]8[/C][C]-0.091914[/C][C]-0.706[/C][C]0.241482[/C][/ROW]
[ROW][C]9[/C][C]0.064266[/C][C]0.4936[/C][C]0.311697[/C][/ROW]
[ROW][C]10[/C][C]-0.06536[/C][C]-0.502[/C][C]0.308755[/C][/ROW]
[ROW][C]11[/C][C]-0.09732[/C][C]-0.7475[/C][C]0.228856[/C][/ROW]
[ROW][C]12[/C][C]0.083426[/C][C]0.6408[/C][C]0.262065[/C][/ROW]
[ROW][C]13[/C][C]-0.046323[/C][C]-0.3558[/C][C]0.361624[/C][/ROW]
[ROW][C]14[/C][C]0.126987[/C][C]0.9754[/C][C]0.166671[/C][/ROW]
[ROW][C]15[/C][C]0.022377[/C][C]0.1719[/C][C]0.43206[/C][/ROW]
[ROW][C]16[/C][C]-0.040631[/C][C]-0.3121[/C][C]0.378035[/C][/ROW]
[ROW][C]17[/C][C]0.036762[/C][C]0.2824[/C][C]0.389322[/C][/ROW]
[ROW][C]18[/C][C]-0.016215[/C][C]-0.1246[/C][C]0.45065[/C][/ROW]
[ROW][C]19[/C][C]-0.006553[/C][C]-0.0503[/C][C]0.480013[/C][/ROW]
[ROW][C]20[/C][C]-0.107151[/C][C]-0.823[/C][C]0.206899[/C][/ROW]
[ROW][C]21[/C][C]-0.004312[/C][C]-0.0331[/C][C]0.486845[/C][/ROW]
[ROW][C]22[/C][C]0.125122[/C][C]0.9611[/C][C]0.170218[/C][/ROW]
[ROW][C]23[/C][C]-0.019571[/C][C]-0.1503[/C][C]0.44051[/C][/ROW]
[ROW][C]24[/C][C]-0.19213[/C][C]-1.4758[/C][C]0.07266[/C][/ROW]
[ROW][C]25[/C][C]-0.074166[/C][C]-0.5697[/C][C]0.285529[/C][/ROW]
[ROW][C]26[/C][C]0.080047[/C][C]0.6149[/C][C]0.270509[/C][/ROW]
[ROW][C]27[/C][C]-0.106908[/C][C]-0.8212[/C][C]0.207426[/C][/ROW]
[ROW][C]28[/C][C]-0.043998[/C][C]-0.338[/C][C]0.368298[/C][/ROW]
[ROW][C]29[/C][C]0.137279[/C][C]1.0545[/C][C]0.147986[/C][/ROW]
[ROW][C]30[/C][C]-0.01081[/C][C]-0.083[/C][C]0.467052[/C][/ROW]
[ROW][C]31[/C][C]-0.03112[/C][C]-0.239[/C][C]0.405951[/C][/ROW]
[ROW][C]32[/C][C]-0.132588[/C][C]-1.0184[/C][C]0.156317[/C][/ROW]
[ROW][C]33[/C][C]0.072884[/C][C]0.5598[/C][C]0.288856[/C][/ROW]
[ROW][C]34[/C][C]0.142134[/C][C]1.0918[/C][C]0.13969[/C][/ROW]
[ROW][C]35[/C][C]0.027899[/C][C]0.2143[/C][C]0.415527[/C][/ROW]
[ROW][C]36[/C][C]-0.076294[/C][C]-0.586[/C][C]0.280046[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28283&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28283&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
10.0465380.35750.361009
2-0.187322-1.43880.077739
3-0.147004-1.12920.1317
40.0019860.01530.493941
50.0715490.54960.292342
6-0.136628-1.04950.149123
70.0515430.39590.346799
8-0.091914-0.7060.241482
90.0642660.49360.311697
10-0.06536-0.5020.308755
11-0.09732-0.74750.228856
120.0834260.64080.262065
13-0.046323-0.35580.361624
140.1269870.97540.166671
150.0223770.17190.43206
16-0.040631-0.31210.378035
170.0367620.28240.389322
18-0.016215-0.12460.45065
19-0.006553-0.05030.480013
20-0.107151-0.8230.206899
21-0.004312-0.03310.486845
220.1251220.96110.170218
23-0.019571-0.15030.44051
24-0.19213-1.47580.07266
25-0.074166-0.56970.285529
260.0800470.61490.270509
27-0.106908-0.82120.207426
28-0.043998-0.3380.368298
290.1372791.05450.147986
30-0.01081-0.0830.467052
31-0.03112-0.2390.405951
32-0.132588-1.01840.156317
330.0728840.55980.288856
340.1421341.09180.13969
350.0278990.21430.415527
36-0.076294-0.5860.280046






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0465380.35750.361009
2-0.189899-1.45860.074984
3-0.132862-1.02050.155821
4-0.022853-0.17550.430628
50.0215510.16550.434545
6-0.172119-1.32210.095624
70.0812280.62390.267542
8-0.153955-1.18260.120866
90.0663410.50960.306124
10-0.123734-0.95040.172889
11-0.083987-0.64510.260676
120.0386350.29680.383845
13-0.090641-0.69620.244511
140.0942310.72380.236023
150.0405720.31160.378208
16-0.067793-0.52070.302253
170.0949340.72920.234381
18-0.024608-0.1890.425363
19-0.047123-0.3620.359339
20-0.034089-0.26180.397178
21-0.06374-0.48960.313118
220.135151.03810.151728
23-0.064258-0.49360.31172
24-0.211262-1.62270.054989
250.0496290.38120.352209
26-0.081385-0.62510.267148
27-0.223247-1.71480.045816
280.0156340.12010.452411
290.0237720.18260.42787
30-0.128399-0.98630.164018
31-0.036781-0.28250.389267
32-0.201717-1.54940.063315
330.0887230.68150.249112
340.0236390.18160.428269
35-0.071473-0.5490.292541
36-0.017317-0.1330.447318

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.046538 & 0.3575 & 0.361009 \tabularnewline
2 & -0.189899 & -1.4586 & 0.074984 \tabularnewline
3 & -0.132862 & -1.0205 & 0.155821 \tabularnewline
4 & -0.022853 & -0.1755 & 0.430628 \tabularnewline
5 & 0.021551 & 0.1655 & 0.434545 \tabularnewline
6 & -0.172119 & -1.3221 & 0.095624 \tabularnewline
7 & 0.081228 & 0.6239 & 0.267542 \tabularnewline
8 & -0.153955 & -1.1826 & 0.120866 \tabularnewline
9 & 0.066341 & 0.5096 & 0.306124 \tabularnewline
10 & -0.123734 & -0.9504 & 0.172889 \tabularnewline
11 & -0.083987 & -0.6451 & 0.260676 \tabularnewline
12 & 0.038635 & 0.2968 & 0.383845 \tabularnewline
13 & -0.090641 & -0.6962 & 0.244511 \tabularnewline
14 & 0.094231 & 0.7238 & 0.236023 \tabularnewline
15 & 0.040572 & 0.3116 & 0.378208 \tabularnewline
16 & -0.067793 & -0.5207 & 0.302253 \tabularnewline
17 & 0.094934 & 0.7292 & 0.234381 \tabularnewline
18 & -0.024608 & -0.189 & 0.425363 \tabularnewline
19 & -0.047123 & -0.362 & 0.359339 \tabularnewline
20 & -0.034089 & -0.2618 & 0.397178 \tabularnewline
21 & -0.06374 & -0.4896 & 0.313118 \tabularnewline
22 & 0.13515 & 1.0381 & 0.151728 \tabularnewline
23 & -0.064258 & -0.4936 & 0.31172 \tabularnewline
24 & -0.211262 & -1.6227 & 0.054989 \tabularnewline
25 & 0.049629 & 0.3812 & 0.352209 \tabularnewline
26 & -0.081385 & -0.6251 & 0.267148 \tabularnewline
27 & -0.223247 & -1.7148 & 0.045816 \tabularnewline
28 & 0.015634 & 0.1201 & 0.452411 \tabularnewline
29 & 0.023772 & 0.1826 & 0.42787 \tabularnewline
30 & -0.128399 & -0.9863 & 0.164018 \tabularnewline
31 & -0.036781 & -0.2825 & 0.389267 \tabularnewline
32 & -0.201717 & -1.5494 & 0.063315 \tabularnewline
33 & 0.088723 & 0.6815 & 0.249112 \tabularnewline
34 & 0.023639 & 0.1816 & 0.428269 \tabularnewline
35 & -0.071473 & -0.549 & 0.292541 \tabularnewline
36 & -0.017317 & -0.133 & 0.447318 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28283&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]0.046538[/C][C]0.3575[/C][C]0.361009[/C][/ROW]
[ROW][C]2[/C][C]-0.189899[/C][C]-1.4586[/C][C]0.074984[/C][/ROW]
[ROW][C]3[/C][C]-0.132862[/C][C]-1.0205[/C][C]0.155821[/C][/ROW]
[ROW][C]4[/C][C]-0.022853[/C][C]-0.1755[/C][C]0.430628[/C][/ROW]
[ROW][C]5[/C][C]0.021551[/C][C]0.1655[/C][C]0.434545[/C][/ROW]
[ROW][C]6[/C][C]-0.172119[/C][C]-1.3221[/C][C]0.095624[/C][/ROW]
[ROW][C]7[/C][C]0.081228[/C][C]0.6239[/C][C]0.267542[/C][/ROW]
[ROW][C]8[/C][C]-0.153955[/C][C]-1.1826[/C][C]0.120866[/C][/ROW]
[ROW][C]9[/C][C]0.066341[/C][C]0.5096[/C][C]0.306124[/C][/ROW]
[ROW][C]10[/C][C]-0.123734[/C][C]-0.9504[/C][C]0.172889[/C][/ROW]
[ROW][C]11[/C][C]-0.083987[/C][C]-0.6451[/C][C]0.260676[/C][/ROW]
[ROW][C]12[/C][C]0.038635[/C][C]0.2968[/C][C]0.383845[/C][/ROW]
[ROW][C]13[/C][C]-0.090641[/C][C]-0.6962[/C][C]0.244511[/C][/ROW]
[ROW][C]14[/C][C]0.094231[/C][C]0.7238[/C][C]0.236023[/C][/ROW]
[ROW][C]15[/C][C]0.040572[/C][C]0.3116[/C][C]0.378208[/C][/ROW]
[ROW][C]16[/C][C]-0.067793[/C][C]-0.5207[/C][C]0.302253[/C][/ROW]
[ROW][C]17[/C][C]0.094934[/C][C]0.7292[/C][C]0.234381[/C][/ROW]
[ROW][C]18[/C][C]-0.024608[/C][C]-0.189[/C][C]0.425363[/C][/ROW]
[ROW][C]19[/C][C]-0.047123[/C][C]-0.362[/C][C]0.359339[/C][/ROW]
[ROW][C]20[/C][C]-0.034089[/C][C]-0.2618[/C][C]0.397178[/C][/ROW]
[ROW][C]21[/C][C]-0.06374[/C][C]-0.4896[/C][C]0.313118[/C][/ROW]
[ROW][C]22[/C][C]0.13515[/C][C]1.0381[/C][C]0.151728[/C][/ROW]
[ROW][C]23[/C][C]-0.064258[/C][C]-0.4936[/C][C]0.31172[/C][/ROW]
[ROW][C]24[/C][C]-0.211262[/C][C]-1.6227[/C][C]0.054989[/C][/ROW]
[ROW][C]25[/C][C]0.049629[/C][C]0.3812[/C][C]0.352209[/C][/ROW]
[ROW][C]26[/C][C]-0.081385[/C][C]-0.6251[/C][C]0.267148[/C][/ROW]
[ROW][C]27[/C][C]-0.223247[/C][C]-1.7148[/C][C]0.045816[/C][/ROW]
[ROW][C]28[/C][C]0.015634[/C][C]0.1201[/C][C]0.452411[/C][/ROW]
[ROW][C]29[/C][C]0.023772[/C][C]0.1826[/C][C]0.42787[/C][/ROW]
[ROW][C]30[/C][C]-0.128399[/C][C]-0.9863[/C][C]0.164018[/C][/ROW]
[ROW][C]31[/C][C]-0.036781[/C][C]-0.2825[/C][C]0.389267[/C][/ROW]
[ROW][C]32[/C][C]-0.201717[/C][C]-1.5494[/C][C]0.063315[/C][/ROW]
[ROW][C]33[/C][C]0.088723[/C][C]0.6815[/C][C]0.249112[/C][/ROW]
[ROW][C]34[/C][C]0.023639[/C][C]0.1816[/C][C]0.428269[/C][/ROW]
[ROW][C]35[/C][C]-0.071473[/C][C]-0.549[/C][C]0.292541[/C][/ROW]
[ROW][C]36[/C][C]-0.017317[/C][C]-0.133[/C][C]0.447318[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28283&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28283&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
10.0465380.35750.361009
2-0.189899-1.45860.074984
3-0.132862-1.02050.155821
4-0.022853-0.17550.430628
50.0215510.16550.434545
6-0.172119-1.32210.095624
70.0812280.62390.267542
8-0.153955-1.18260.120866
90.0663410.50960.306124
10-0.123734-0.95040.172889
11-0.083987-0.64510.260676
120.0386350.29680.383845
13-0.090641-0.69620.244511
140.0942310.72380.236023
150.0405720.31160.378208
16-0.067793-0.52070.302253
170.0949340.72920.234381
18-0.024608-0.1890.425363
19-0.047123-0.3620.359339
20-0.034089-0.26180.397178
21-0.06374-0.48960.313118
220.135151.03810.151728
23-0.064258-0.49360.31172
24-0.211262-1.62270.054989
250.0496290.38120.352209
26-0.081385-0.62510.267148
27-0.223247-1.71480.045816
280.0156340.12010.452411
290.0237720.18260.42787
30-0.128399-0.98630.164018
31-0.036781-0.28250.389267
32-0.201717-1.54940.063315
330.0887230.68150.249112
340.0236390.18160.428269
35-0.071473-0.5490.292541
36-0.017317-0.1330.447318


Figures (Output of Computation)

Input Parameters & R Code

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