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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 computationTue, 02 Dec 2008 16:24:19 -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/03/t1228260289wu5zsdl52yppypp.htm/, Retrieved Fri, 17 May 2024 16:43:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28533, Retrieved Fri, 17 May 2024 16:43:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact224

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RM D  [(Partial) Autocorrelation Function] [Non stationary ti...] [2008-12-02 22:44:03] [1a689e9ccc515e1757f0522229a687e9]
-    D    [(Partial) Autocorrelation Function] [Non stationary ti...] [2008-12-02 22:53:08] [1a689e9ccc515e1757f0522229a687e9]
-    D        [(Partial) Autocorrelation Function] [Non stationary ti...] [2008-12-02 23:24:19] [74a138e5b32af267311b5ad4cd13bf7e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
89,8
103,3
107,9
101
94,6
94,2
92,3
107,1
102,6
103,1
104,1
92,7
87
109,3
113,9
103,3
100,8
97,4
98,9
110,8
103,5
99,8
104,9
95,2
85,7
110
113,7
101,1
103,6
96,2
98,3
119,7
109,4
103,5
118,2
98,7
96,8
121,8
124
119,6
122,5
109,7
111,6
131,2
124,4
116,9
131,8
107,4
111
134
126,2
131,2
130,1
123,1
126,3
148,6
130,1
142,3
154,4
121,6
124,8
143,6
146,9
144,6
137,1
134,7
130,8
153,5
137,6
146,5
156,7
137,6
131,4
147,4
158,5
151,5
142,5
131,3
133,4
136,9
143,2
136,4
145,9
138,8
122,9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28533&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]0 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=28533&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28533&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 time0 seconds
R Server'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.563466-4.78124e-06
20.0460710.39090.348505
30.1889281.60310.056645
4-0.158924-1.34850.09086
50.0659920.560.288623
60.0675570.57320.284133
7-0.096562-0.81940.207644
8-0.136722-1.16010.124915
90.3169092.68910.004449
10-0.212021-1.79910.0381
11-0.014064-0.11930.452669
120.0604730.51310.304716
13-0.060293-0.51160.305247
140.1016180.86230.195704
15-0.036555-0.31020.37866
16-0.052325-0.4440.329189
170.0056210.04770.481045
180.2019661.71370.045439
19-0.202182-1.71560.045271
200.0505030.42850.334773
210.1203811.02150.155227
22-0.282548-2.39750.009552
230.3904173.31280.000724
24-0.291247-2.47130.007914
250.0126950.10770.457258
260.1746431.48190.071366
27-0.084666-0.71840.237413
28-0.094631-0.8030.212318
290.1468761.24630.10835
30-0.12545-1.06450.145335
310.0231540.19650.4224
320.1391231.18050.120844
33-0.216775-1.83940.03499
340.072560.61570.270021
350.0875150.74260.230072
36-0.112162-0.95170.172209

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.563466 & -4.7812 & 4e-06 \tabularnewline
2 & 0.046071 & 0.3909 & 0.348505 \tabularnewline
3 & 0.188928 & 1.6031 & 0.056645 \tabularnewline
4 & -0.158924 & -1.3485 & 0.09086 \tabularnewline
5 & 0.065992 & 0.56 & 0.288623 \tabularnewline
6 & 0.067557 & 0.5732 & 0.284133 \tabularnewline
7 & -0.096562 & -0.8194 & 0.207644 \tabularnewline
8 & -0.136722 & -1.1601 & 0.124915 \tabularnewline
9 & 0.316909 & 2.6891 & 0.004449 \tabularnewline
10 & -0.212021 & -1.7991 & 0.0381 \tabularnewline
11 & -0.014064 & -0.1193 & 0.452669 \tabularnewline
12 & 0.060473 & 0.5131 & 0.304716 \tabularnewline
13 & -0.060293 & -0.5116 & 0.305247 \tabularnewline
14 & 0.101618 & 0.8623 & 0.195704 \tabularnewline
15 & -0.036555 & -0.3102 & 0.37866 \tabularnewline
16 & -0.052325 & -0.444 & 0.329189 \tabularnewline
17 & 0.005621 & 0.0477 & 0.481045 \tabularnewline
18 & 0.201966 & 1.7137 & 0.045439 \tabularnewline
19 & -0.202182 & -1.7156 & 0.045271 \tabularnewline
20 & 0.050503 & 0.4285 & 0.334773 \tabularnewline
21 & 0.120381 & 1.0215 & 0.155227 \tabularnewline
22 & -0.282548 & -2.3975 & 0.009552 \tabularnewline
23 & 0.390417 & 3.3128 & 0.000724 \tabularnewline
24 & -0.291247 & -2.4713 & 0.007914 \tabularnewline
25 & 0.012695 & 0.1077 & 0.457258 \tabularnewline
26 & 0.174643 & 1.4819 & 0.071366 \tabularnewline
27 & -0.084666 & -0.7184 & 0.237413 \tabularnewline
28 & -0.094631 & -0.803 & 0.212318 \tabularnewline
29 & 0.146876 & 1.2463 & 0.10835 \tabularnewline
30 & -0.12545 & -1.0645 & 0.145335 \tabularnewline
31 & 0.023154 & 0.1965 & 0.4224 \tabularnewline
32 & 0.139123 & 1.1805 & 0.120844 \tabularnewline
33 & -0.216775 & -1.8394 & 0.03499 \tabularnewline
34 & 0.07256 & 0.6157 & 0.270021 \tabularnewline
35 & 0.087515 & 0.7426 & 0.230072 \tabularnewline
36 & -0.112162 & -0.9517 & 0.172209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28533&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]-0.563466[/C][C]-4.7812[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]0.046071[/C][C]0.3909[/C][C]0.348505[/C][/ROW]
[ROW][C]3[/C][C]0.188928[/C][C]1.6031[/C][C]0.056645[/C][/ROW]
[ROW][C]4[/C][C]-0.158924[/C][C]-1.3485[/C][C]0.09086[/C][/ROW]
[ROW][C]5[/C][C]0.065992[/C][C]0.56[/C][C]0.288623[/C][/ROW]
[ROW][C]6[/C][C]0.067557[/C][C]0.5732[/C][C]0.284133[/C][/ROW]
[ROW][C]7[/C][C]-0.096562[/C][C]-0.8194[/C][C]0.207644[/C][/ROW]
[ROW][C]8[/C][C]-0.136722[/C][C]-1.1601[/C][C]0.124915[/C][/ROW]
[ROW][C]9[/C][C]0.316909[/C][C]2.6891[/C][C]0.004449[/C][/ROW]
[ROW][C]10[/C][C]-0.212021[/C][C]-1.7991[/C][C]0.0381[/C][/ROW]
[ROW][C]11[/C][C]-0.014064[/C][C]-0.1193[/C][C]0.452669[/C][/ROW]
[ROW][C]12[/C][C]0.060473[/C][C]0.5131[/C][C]0.304716[/C][/ROW]
[ROW][C]13[/C][C]-0.060293[/C][C]-0.5116[/C][C]0.305247[/C][/ROW]
[ROW][C]14[/C][C]0.101618[/C][C]0.8623[/C][C]0.195704[/C][/ROW]
[ROW][C]15[/C][C]-0.036555[/C][C]-0.3102[/C][C]0.37866[/C][/ROW]
[ROW][C]16[/C][C]-0.052325[/C][C]-0.444[/C][C]0.329189[/C][/ROW]
[ROW][C]17[/C][C]0.005621[/C][C]0.0477[/C][C]0.481045[/C][/ROW]
[ROW][C]18[/C][C]0.201966[/C][C]1.7137[/C][C]0.045439[/C][/ROW]
[ROW][C]19[/C][C]-0.202182[/C][C]-1.7156[/C][C]0.045271[/C][/ROW]
[ROW][C]20[/C][C]0.050503[/C][C]0.4285[/C][C]0.334773[/C][/ROW]
[ROW][C]21[/C][C]0.120381[/C][C]1.0215[/C][C]0.155227[/C][/ROW]
[ROW][C]22[/C][C]-0.282548[/C][C]-2.3975[/C][C]0.009552[/C][/ROW]
[ROW][C]23[/C][C]0.390417[/C][C]3.3128[/C][C]0.000724[/C][/ROW]
[ROW][C]24[/C][C]-0.291247[/C][C]-2.4713[/C][C]0.007914[/C][/ROW]
[ROW][C]25[/C][C]0.012695[/C][C]0.1077[/C][C]0.457258[/C][/ROW]
[ROW][C]26[/C][C]0.174643[/C][C]1.4819[/C][C]0.071366[/C][/ROW]
[ROW][C]27[/C][C]-0.084666[/C][C]-0.7184[/C][C]0.237413[/C][/ROW]
[ROW][C]28[/C][C]-0.094631[/C][C]-0.803[/C][C]0.212318[/C][/ROW]
[ROW][C]29[/C][C]0.146876[/C][C]1.2463[/C][C]0.10835[/C][/ROW]
[ROW][C]30[/C][C]-0.12545[/C][C]-1.0645[/C][C]0.145335[/C][/ROW]
[ROW][C]31[/C][C]0.023154[/C][C]0.1965[/C][C]0.4224[/C][/ROW]
[ROW][C]32[/C][C]0.139123[/C][C]1.1805[/C][C]0.120844[/C][/ROW]
[ROW][C]33[/C][C]-0.216775[/C][C]-1.8394[/C][C]0.03499[/C][/ROW]
[ROW][C]34[/C][C]0.07256[/C][C]0.6157[/C][C]0.270021[/C][/ROW]
[ROW][C]35[/C][C]0.087515[/C][C]0.7426[/C][C]0.230072[/C][/ROW]
[ROW][C]36[/C][C]-0.112162[/C][C]-0.9517[/C][C]0.172209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28533&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28533&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
1-0.563466-4.78124e-06
20.0460710.39090.348505
30.1889281.60310.056645
4-0.158924-1.34850.09086
50.0659920.560.288623
60.0675570.57320.284133
7-0.096562-0.81940.207644
8-0.136722-1.16010.124915
90.3169092.68910.004449
10-0.212021-1.79910.0381
11-0.014064-0.11930.452669
120.0604730.51310.304716
13-0.060293-0.51160.305247
140.1016180.86230.195704
15-0.036555-0.31020.37866
16-0.052325-0.4440.329189
170.0056210.04770.481045
180.2019661.71370.045439
19-0.202182-1.71560.045271
200.0505030.42850.334773
210.1203811.02150.155227
22-0.282548-2.39750.009552
230.3904173.31280.000724
24-0.291247-2.47130.007914
250.0126950.10770.457258
260.1746431.48190.071366
27-0.084666-0.71840.237413
28-0.094631-0.8030.212318
290.1468761.24630.10835
30-0.12545-1.06450.145335
310.0231540.19650.4224
320.1391231.18050.120844
33-0.216775-1.83940.03499
340.072560.61570.270021
350.0875150.74260.230072
36-0.112162-0.95170.172209






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.563466-4.78124e-06
2-0.397685-3.37450.000597
30.0019640.01670.493376
40.0157950.1340.446878
50.0397750.33750.36836
60.1256511.06620.144951
70.0593990.5040.307895
8-0.316614-2.68660.004479
90.0240570.20410.419414
100.0845640.71750.23768
11-0.004984-0.04230.483193
12-0.139517-1.18380.120185
13-0.076014-0.6450.260488
140.1127360.95660.170987
150.0825570.70050.24293
16-0.017647-0.14970.440694
17-0.027923-0.23690.406691
180.233541.98170.025668
190.0680170.57710.282823
20-0.075548-0.6410.261764
210.1431021.21430.114308
22-0.166609-1.41370.080876
230.1145690.97220.167115
24-0.06897-0.58520.280113
25-0.012687-0.10770.457286
260.1564571.32760.094256
270.0969650.82280.206677
28-0.124176-1.05370.14778
290.0343970.29190.385615
30-0.087573-0.74310.229924
310.0397640.33740.368394
32-0.040147-0.34070.367176
33-0.058588-0.49710.310304
34-0.036108-0.30640.380097
35-0.017728-0.15040.440422
36-0.141196-1.19810.117406

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.563466 & -4.7812 & 4e-06 \tabularnewline
2 & -0.397685 & -3.3745 & 0.000597 \tabularnewline
3 & 0.001964 & 0.0167 & 0.493376 \tabularnewline
4 & 0.015795 & 0.134 & 0.446878 \tabularnewline
5 & 0.039775 & 0.3375 & 0.36836 \tabularnewline
6 & 0.125651 & 1.0662 & 0.144951 \tabularnewline
7 & 0.059399 & 0.504 & 0.307895 \tabularnewline
8 & -0.316614 & -2.6866 & 0.004479 \tabularnewline
9 & 0.024057 & 0.2041 & 0.419414 \tabularnewline
10 & 0.084564 & 0.7175 & 0.23768 \tabularnewline
11 & -0.004984 & -0.0423 & 0.483193 \tabularnewline
12 & -0.139517 & -1.1838 & 0.120185 \tabularnewline
13 & -0.076014 & -0.645 & 0.260488 \tabularnewline
14 & 0.112736 & 0.9566 & 0.170987 \tabularnewline
15 & 0.082557 & 0.7005 & 0.24293 \tabularnewline
16 & -0.017647 & -0.1497 & 0.440694 \tabularnewline
17 & -0.027923 & -0.2369 & 0.406691 \tabularnewline
18 & 0.23354 & 1.9817 & 0.025668 \tabularnewline
19 & 0.068017 & 0.5771 & 0.282823 \tabularnewline
20 & -0.075548 & -0.641 & 0.261764 \tabularnewline
21 & 0.143102 & 1.2143 & 0.114308 \tabularnewline
22 & -0.166609 & -1.4137 & 0.080876 \tabularnewline
23 & 0.114569 & 0.9722 & 0.167115 \tabularnewline
24 & -0.06897 & -0.5852 & 0.280113 \tabularnewline
25 & -0.012687 & -0.1077 & 0.457286 \tabularnewline
26 & 0.156457 & 1.3276 & 0.094256 \tabularnewline
27 & 0.096965 & 0.8228 & 0.206677 \tabularnewline
28 & -0.124176 & -1.0537 & 0.14778 \tabularnewline
29 & 0.034397 & 0.2919 & 0.385615 \tabularnewline
30 & -0.087573 & -0.7431 & 0.229924 \tabularnewline
31 & 0.039764 & 0.3374 & 0.368394 \tabularnewline
32 & -0.040147 & -0.3407 & 0.367176 \tabularnewline
33 & -0.058588 & -0.4971 & 0.310304 \tabularnewline
34 & -0.036108 & -0.3064 & 0.380097 \tabularnewline
35 & -0.017728 & -0.1504 & 0.440422 \tabularnewline
36 & -0.141196 & -1.1981 & 0.117406 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28533&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]-0.563466[/C][C]-4.7812[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.397685[/C][C]-3.3745[/C][C]0.000597[/C][/ROW]
[ROW][C]3[/C][C]0.001964[/C][C]0.0167[/C][C]0.493376[/C][/ROW]
[ROW][C]4[/C][C]0.015795[/C][C]0.134[/C][C]0.446878[/C][/ROW]
[ROW][C]5[/C][C]0.039775[/C][C]0.3375[/C][C]0.36836[/C][/ROW]
[ROW][C]6[/C][C]0.125651[/C][C]1.0662[/C][C]0.144951[/C][/ROW]
[ROW][C]7[/C][C]0.059399[/C][C]0.504[/C][C]0.307895[/C][/ROW]
[ROW][C]8[/C][C]-0.316614[/C][C]-2.6866[/C][C]0.004479[/C][/ROW]
[ROW][C]9[/C][C]0.024057[/C][C]0.2041[/C][C]0.419414[/C][/ROW]
[ROW][C]10[/C][C]0.084564[/C][C]0.7175[/C][C]0.23768[/C][/ROW]
[ROW][C]11[/C][C]-0.004984[/C][C]-0.0423[/C][C]0.483193[/C][/ROW]
[ROW][C]12[/C][C]-0.139517[/C][C]-1.1838[/C][C]0.120185[/C][/ROW]
[ROW][C]13[/C][C]-0.076014[/C][C]-0.645[/C][C]0.260488[/C][/ROW]
[ROW][C]14[/C][C]0.112736[/C][C]0.9566[/C][C]0.170987[/C][/ROW]
[ROW][C]15[/C][C]0.082557[/C][C]0.7005[/C][C]0.24293[/C][/ROW]
[ROW][C]16[/C][C]-0.017647[/C][C]-0.1497[/C][C]0.440694[/C][/ROW]
[ROW][C]17[/C][C]-0.027923[/C][C]-0.2369[/C][C]0.406691[/C][/ROW]
[ROW][C]18[/C][C]0.23354[/C][C]1.9817[/C][C]0.025668[/C][/ROW]
[ROW][C]19[/C][C]0.068017[/C][C]0.5771[/C][C]0.282823[/C][/ROW]
[ROW][C]20[/C][C]-0.075548[/C][C]-0.641[/C][C]0.261764[/C][/ROW]
[ROW][C]21[/C][C]0.143102[/C][C]1.2143[/C][C]0.114308[/C][/ROW]
[ROW][C]22[/C][C]-0.166609[/C][C]-1.4137[/C][C]0.080876[/C][/ROW]
[ROW][C]23[/C][C]0.114569[/C][C]0.9722[/C][C]0.167115[/C][/ROW]
[ROW][C]24[/C][C]-0.06897[/C][C]-0.5852[/C][C]0.280113[/C][/ROW]
[ROW][C]25[/C][C]-0.012687[/C][C]-0.1077[/C][C]0.457286[/C][/ROW]
[ROW][C]26[/C][C]0.156457[/C][C]1.3276[/C][C]0.094256[/C][/ROW]
[ROW][C]27[/C][C]0.096965[/C][C]0.8228[/C][C]0.206677[/C][/ROW]
[ROW][C]28[/C][C]-0.124176[/C][C]-1.0537[/C][C]0.14778[/C][/ROW]
[ROW][C]29[/C][C]0.034397[/C][C]0.2919[/C][C]0.385615[/C][/ROW]
[ROW][C]30[/C][C]-0.087573[/C][C]-0.7431[/C][C]0.229924[/C][/ROW]
[ROW][C]31[/C][C]0.039764[/C][C]0.3374[/C][C]0.368394[/C][/ROW]
[ROW][C]32[/C][C]-0.040147[/C][C]-0.3407[/C][C]0.367176[/C][/ROW]
[ROW][C]33[/C][C]-0.058588[/C][C]-0.4971[/C][C]0.310304[/C][/ROW]
[ROW][C]34[/C][C]-0.036108[/C][C]-0.3064[/C][C]0.380097[/C][/ROW]
[ROW][C]35[/C][C]-0.017728[/C][C]-0.1504[/C][C]0.440422[/C][/ROW]
[ROW][C]36[/C][C]-0.141196[/C][C]-1.1981[/C][C]0.117406[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28533&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28533&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
1-0.563466-4.78124e-06
2-0.397685-3.37450.000597
30.0019640.01670.493376
40.0157950.1340.446878
50.0397750.33750.36836
60.1256511.06620.144951
70.0593990.5040.307895
8-0.316614-2.68660.004479
90.0240570.20410.419414
100.0845640.71750.23768
11-0.004984-0.04230.483193
12-0.139517-1.18380.120185
13-0.076014-0.6450.260488
140.1127360.95660.170987
150.0825570.70050.24293
16-0.017647-0.14970.440694
17-0.027923-0.23690.406691
180.233541.98170.025668
190.0680170.57710.282823
20-0.075548-0.6410.261764
210.1431021.21430.114308
22-0.166609-1.41370.080876
230.1145690.97220.167115
24-0.06897-0.58520.280113
25-0.012687-0.10770.457286
260.1564571.32760.094256
270.0969650.82280.206677
28-0.124176-1.05370.14778
290.0343970.29190.385615
30-0.087573-0.74310.229924
310.0397640.33740.368394
32-0.040147-0.34070.367176
33-0.058588-0.49710.310304
34-0.036108-0.30640.380097
35-0.017728-0.15040.440422
36-0.141196-1.19810.117406


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Airline ; par2 = Box-Jenkins ; par3 = Airline Passengers ;
Parameters (R input):
par1 = 36 ; par2 = 1.0 ; par3 = 1 ; 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')