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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, 19 Dec 2009 08:27:46 -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/19/t1261236493xvnc5s3ksd8oxqr.htm/, Retrieved Mon, 12 May 2025 13:17:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69638, Retrieved Mon, 12 May 2025 13:17:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:26:39] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [Model 1 (d = 1, D...] [2009-11-24 17:46:32] [ee7c2e7343f5b1451e62c5c16ec521f1]
- R PD            [(Partial) Autocorrelation Function] [] [2009-12-19 15:27:46] [d5175f34d1f80375edd7cbd8232724fe] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1920
2218
3032
2375
2446
2916
2434
2540
2349
2310
2189
2660
2194
2419
2742
2137
2710
2173
2363
2126
1905
2121
1983
1734
2074
2049
2406
2558
2251
2059
2397
1747
1707
2319
1631
1627
1791
2034
1997
2169
2028
2253
2218
1855
2187
1852
1570
1851
1954
1828
2251
2277
2085
2282
2266
1878
2267
2069
1746
2299
2360
2214
2825
2355
2333
3016
2155
2172
2150
2533
2058
2160
2260
2498
2695
2799
2947
2930
2318
2540
2570
2669
2450
2842
3440
2678
2981
2260
2844
2546
2456
2295
2379
2479
2057
2280
2351
2276
2548
2311
2201
2725
2408
2139
1898
2537
2069
2063
2526
2440
2191
2797
2074
2628
2287
2146
2430
2141
1827
2082
1788

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=69638&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=69638&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69638&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
1-0.502888-5.50890
2-0.02897-0.31740.375764
30.249512.73330.00361
4-0.156472-1.71410.04455
5-0.049559-0.54290.294106
60.0641730.7030.241717
7-0.133477-1.46220.073155
8-0.006707-0.07350.470777
90.1690931.85230.033218
10-0.169482-1.85660.032911
110.0244220.26750.39476
120.2212522.42370.008428
13-0.17821-1.95220.026622
140.0380920.41730.338611
150.127951.40160.081804
16-0.172329-1.88780.030736
170.0989881.08440.14019
18-0.117575-1.2880.100117
190.0394670.43230.333136
20-0.100612-1.10220.136301
210.1287481.41040.080509
22-0.111894-1.22570.111348
230.0719320.7880.216134
240.0551350.6040.2735
250.0301450.33020.370904
26-0.016482-0.18060.428512
27-0.018208-0.19950.42112
280.0350080.38350.351018
29-0.049901-0.54660.292821
30-0.037766-0.41370.339912
31-0.07928-0.86850.193437
320.1133771.2420.108332
33-0.023564-0.25810.398375
34-0.034967-0.3830.351181
35-0.010658-0.11680.453627
360.1389961.52260.065242

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.502888 & -5.5089 & 0 \tabularnewline
2 & -0.02897 & -0.3174 & 0.375764 \tabularnewline
3 & 0.24951 & 2.7333 & 0.00361 \tabularnewline
4 & -0.156472 & -1.7141 & 0.04455 \tabularnewline
5 & -0.049559 & -0.5429 & 0.294106 \tabularnewline
6 & 0.064173 & 0.703 & 0.241717 \tabularnewline
7 & -0.133477 & -1.4622 & 0.073155 \tabularnewline
8 & -0.006707 & -0.0735 & 0.470777 \tabularnewline
9 & 0.169093 & 1.8523 & 0.033218 \tabularnewline
10 & -0.169482 & -1.8566 & 0.032911 \tabularnewline
11 & 0.024422 & 0.2675 & 0.39476 \tabularnewline
12 & 0.221252 & 2.4237 & 0.008428 \tabularnewline
13 & -0.17821 & -1.9522 & 0.026622 \tabularnewline
14 & 0.038092 & 0.4173 & 0.338611 \tabularnewline
15 & 0.12795 & 1.4016 & 0.081804 \tabularnewline
16 & -0.172329 & -1.8878 & 0.030736 \tabularnewline
17 & 0.098988 & 1.0844 & 0.14019 \tabularnewline
18 & -0.117575 & -1.288 & 0.100117 \tabularnewline
19 & 0.039467 & 0.4323 & 0.333136 \tabularnewline
20 & -0.100612 & -1.1022 & 0.136301 \tabularnewline
21 & 0.128748 & 1.4104 & 0.080509 \tabularnewline
22 & -0.111894 & -1.2257 & 0.111348 \tabularnewline
23 & 0.071932 & 0.788 & 0.216134 \tabularnewline
24 & 0.055135 & 0.604 & 0.2735 \tabularnewline
25 & 0.030145 & 0.3302 & 0.370904 \tabularnewline
26 & -0.016482 & -0.1806 & 0.428512 \tabularnewline
27 & -0.018208 & -0.1995 & 0.42112 \tabularnewline
28 & 0.035008 & 0.3835 & 0.351018 \tabularnewline
29 & -0.049901 & -0.5466 & 0.292821 \tabularnewline
30 & -0.037766 & -0.4137 & 0.339912 \tabularnewline
31 & -0.07928 & -0.8685 & 0.193437 \tabularnewline
32 & 0.113377 & 1.242 & 0.108332 \tabularnewline
33 & -0.023564 & -0.2581 & 0.398375 \tabularnewline
34 & -0.034967 & -0.383 & 0.351181 \tabularnewline
35 & -0.010658 & -0.1168 & 0.453627 \tabularnewline
36 & 0.138996 & 1.5226 & 0.065242 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69638&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]-0.502888[/C][C]-5.5089[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.02897[/C][C]-0.3174[/C][C]0.375764[/C][/ROW]
[ROW][C]3[/C][C]0.24951[/C][C]2.7333[/C][C]0.00361[/C][/ROW]
[ROW][C]4[/C][C]-0.156472[/C][C]-1.7141[/C][C]0.04455[/C][/ROW]
[ROW][C]5[/C][C]-0.049559[/C][C]-0.5429[/C][C]0.294106[/C][/ROW]
[ROW][C]6[/C][C]0.064173[/C][C]0.703[/C][C]0.241717[/C][/ROW]
[ROW][C]7[/C][C]-0.133477[/C][C]-1.4622[/C][C]0.073155[/C][/ROW]
[ROW][C]8[/C][C]-0.006707[/C][C]-0.0735[/C][C]0.470777[/C][/ROW]
[ROW][C]9[/C][C]0.169093[/C][C]1.8523[/C][C]0.033218[/C][/ROW]
[ROW][C]10[/C][C]-0.169482[/C][C]-1.8566[/C][C]0.032911[/C][/ROW]
[ROW][C]11[/C][C]0.024422[/C][C]0.2675[/C][C]0.39476[/C][/ROW]
[ROW][C]12[/C][C]0.221252[/C][C]2.4237[/C][C]0.008428[/C][/ROW]
[ROW][C]13[/C][C]-0.17821[/C][C]-1.9522[/C][C]0.026622[/C][/ROW]
[ROW][C]14[/C][C]0.038092[/C][C]0.4173[/C][C]0.338611[/C][/ROW]
[ROW][C]15[/C][C]0.12795[/C][C]1.4016[/C][C]0.081804[/C][/ROW]
[ROW][C]16[/C][C]-0.172329[/C][C]-1.8878[/C][C]0.030736[/C][/ROW]
[ROW][C]17[/C][C]0.098988[/C][C]1.0844[/C][C]0.14019[/C][/ROW]
[ROW][C]18[/C][C]-0.117575[/C][C]-1.288[/C][C]0.100117[/C][/ROW]
[ROW][C]19[/C][C]0.039467[/C][C]0.4323[/C][C]0.333136[/C][/ROW]
[ROW][C]20[/C][C]-0.100612[/C][C]-1.1022[/C][C]0.136301[/C][/ROW]
[ROW][C]21[/C][C]0.128748[/C][C]1.4104[/C][C]0.080509[/C][/ROW]
[ROW][C]22[/C][C]-0.111894[/C][C]-1.2257[/C][C]0.111348[/C][/ROW]
[ROW][C]23[/C][C]0.071932[/C][C]0.788[/C][C]0.216134[/C][/ROW]
[ROW][C]24[/C][C]0.055135[/C][C]0.604[/C][C]0.2735[/C][/ROW]
[ROW][C]25[/C][C]0.030145[/C][C]0.3302[/C][C]0.370904[/C][/ROW]
[ROW][C]26[/C][C]-0.016482[/C][C]-0.1806[/C][C]0.428512[/C][/ROW]
[ROW][C]27[/C][C]-0.018208[/C][C]-0.1995[/C][C]0.42112[/C][/ROW]
[ROW][C]28[/C][C]0.035008[/C][C]0.3835[/C][C]0.351018[/C][/ROW]
[ROW][C]29[/C][C]-0.049901[/C][C]-0.5466[/C][C]0.292821[/C][/ROW]
[ROW][C]30[/C][C]-0.037766[/C][C]-0.4137[/C][C]0.339912[/C][/ROW]
[ROW][C]31[/C][C]-0.07928[/C][C]-0.8685[/C][C]0.193437[/C][/ROW]
[ROW][C]32[/C][C]0.113377[/C][C]1.242[/C][C]0.108332[/C][/ROW]
[ROW][C]33[/C][C]-0.023564[/C][C]-0.2581[/C][C]0.398375[/C][/ROW]
[ROW][C]34[/C][C]-0.034967[/C][C]-0.383[/C][C]0.351181[/C][/ROW]
[ROW][C]35[/C][C]-0.010658[/C][C]-0.1168[/C][C]0.453627[/C][/ROW]
[ROW][C]36[/C][C]0.138996[/C][C]1.5226[/C][C]0.065242[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69638&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69638&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
1-0.502888-5.50890
2-0.02897-0.31740.375764
30.249512.73330.00361
4-0.156472-1.71410.04455
5-0.049559-0.54290.294106
60.0641730.7030.241717
7-0.133477-1.46220.073155
8-0.006707-0.07350.470777
90.1690931.85230.033218
10-0.169482-1.85660.032911
110.0244220.26750.39476
120.2212522.42370.008428
13-0.17821-1.95220.026622
140.0380920.41730.338611
150.127951.40160.081804
16-0.172329-1.88780.030736
170.0989881.08440.14019
18-0.117575-1.2880.100117
190.0394670.43230.333136
20-0.100612-1.10220.136301
210.1287481.41040.080509
22-0.111894-1.22570.111348
230.0719320.7880.216134
240.0551350.6040.2735
250.0301450.33020.370904
26-0.016482-0.18060.428512
27-0.018208-0.19950.42112
280.0350080.38350.351018
29-0.049901-0.54660.292821
30-0.037766-0.41370.339912
31-0.07928-0.86850.193437
320.1133771.2420.108332
33-0.023564-0.25810.398375
34-0.034967-0.3830.351181
35-0.010658-0.11680.453627
360.1389961.52260.065242






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.502888-5.50890
2-0.377279-4.13293.3e-05
30.0619830.6790.249226
40.0501230.54910.291991
5-0.074675-0.8180.207482
6-0.115318-1.26320.104475
7-0.234196-2.56550.005767
8-0.249507-2.73320.003611
90.0484280.53050.298371
100.01580.17310.431438
11-0.076185-0.83460.202812
120.1183871.29690.098583
130.0581830.63740.262553
140.012970.14210.443626
150.0937491.0270.153249
160.0105460.11550.45411
170.084120.92150.179322
18-0.147952-1.62070.05385
19-0.012628-0.13830.445104
20-0.191254-2.09510.019133
21-0.021101-0.23120.408795
22-0.052818-0.57860.281973
230.0144970.15880.437044
24-0.032616-0.35730.360753
250.1518561.66350.049411
260.0950691.04140.149885
27-0.009411-0.10310.459033
280.0030120.0330.486865
290.0099780.10930.456571
30-0.006363-0.06970.472272
31-0.170539-1.86820.032089
320.0315570.34570.36509
330.0939061.02870.152848
340.0442710.4850.314294
35-0.112934-1.23710.109227
36-0.031023-0.33980.367287

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.502888 & -5.5089 & 0 \tabularnewline
2 & -0.377279 & -4.1329 & 3.3e-05 \tabularnewline
3 & 0.061983 & 0.679 & 0.249226 \tabularnewline
4 & 0.050123 & 0.5491 & 0.291991 \tabularnewline
5 & -0.074675 & -0.818 & 0.207482 \tabularnewline
6 & -0.115318 & -1.2632 & 0.104475 \tabularnewline
7 & -0.234196 & -2.5655 & 0.005767 \tabularnewline
8 & -0.249507 & -2.7332 & 0.003611 \tabularnewline
9 & 0.048428 & 0.5305 & 0.298371 \tabularnewline
10 & 0.0158 & 0.1731 & 0.431438 \tabularnewline
11 & -0.076185 & -0.8346 & 0.202812 \tabularnewline
12 & 0.118387 & 1.2969 & 0.098583 \tabularnewline
13 & 0.058183 & 0.6374 & 0.262553 \tabularnewline
14 & 0.01297 & 0.1421 & 0.443626 \tabularnewline
15 & 0.093749 & 1.027 & 0.153249 \tabularnewline
16 & 0.010546 & 0.1155 & 0.45411 \tabularnewline
17 & 0.08412 & 0.9215 & 0.179322 \tabularnewline
18 & -0.147952 & -1.6207 & 0.05385 \tabularnewline
19 & -0.012628 & -0.1383 & 0.445104 \tabularnewline
20 & -0.191254 & -2.0951 & 0.019133 \tabularnewline
21 & -0.021101 & -0.2312 & 0.408795 \tabularnewline
22 & -0.052818 & -0.5786 & 0.281973 \tabularnewline
23 & 0.014497 & 0.1588 & 0.437044 \tabularnewline
24 & -0.032616 & -0.3573 & 0.360753 \tabularnewline
25 & 0.151856 & 1.6635 & 0.049411 \tabularnewline
26 & 0.095069 & 1.0414 & 0.149885 \tabularnewline
27 & -0.009411 & -0.1031 & 0.459033 \tabularnewline
28 & 0.003012 & 0.033 & 0.486865 \tabularnewline
29 & 0.009978 & 0.1093 & 0.456571 \tabularnewline
30 & -0.006363 & -0.0697 & 0.472272 \tabularnewline
31 & -0.170539 & -1.8682 & 0.032089 \tabularnewline
32 & 0.031557 & 0.3457 & 0.36509 \tabularnewline
33 & 0.093906 & 1.0287 & 0.152848 \tabularnewline
34 & 0.044271 & 0.485 & 0.314294 \tabularnewline
35 & -0.112934 & -1.2371 & 0.109227 \tabularnewline
36 & -0.031023 & -0.3398 & 0.367287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69638&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]-0.502888[/C][C]-5.5089[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.377279[/C][C]-4.1329[/C][C]3.3e-05[/C][/ROW]
[ROW][C]3[/C][C]0.061983[/C][C]0.679[/C][C]0.249226[/C][/ROW]
[ROW][C]4[/C][C]0.050123[/C][C]0.5491[/C][C]0.291991[/C][/ROW]
[ROW][C]5[/C][C]-0.074675[/C][C]-0.818[/C][C]0.207482[/C][/ROW]
[ROW][C]6[/C][C]-0.115318[/C][C]-1.2632[/C][C]0.104475[/C][/ROW]
[ROW][C]7[/C][C]-0.234196[/C][C]-2.5655[/C][C]0.005767[/C][/ROW]
[ROW][C]8[/C][C]-0.249507[/C][C]-2.7332[/C][C]0.003611[/C][/ROW]
[ROW][C]9[/C][C]0.048428[/C][C]0.5305[/C][C]0.298371[/C][/ROW]
[ROW][C]10[/C][C]0.0158[/C][C]0.1731[/C][C]0.431438[/C][/ROW]
[ROW][C]11[/C][C]-0.076185[/C][C]-0.8346[/C][C]0.202812[/C][/ROW]
[ROW][C]12[/C][C]0.118387[/C][C]1.2969[/C][C]0.098583[/C][/ROW]
[ROW][C]13[/C][C]0.058183[/C][C]0.6374[/C][C]0.262553[/C][/ROW]
[ROW][C]14[/C][C]0.01297[/C][C]0.1421[/C][C]0.443626[/C][/ROW]
[ROW][C]15[/C][C]0.093749[/C][C]1.027[/C][C]0.153249[/C][/ROW]
[ROW][C]16[/C][C]0.010546[/C][C]0.1155[/C][C]0.45411[/C][/ROW]
[ROW][C]17[/C][C]0.08412[/C][C]0.9215[/C][C]0.179322[/C][/ROW]
[ROW][C]18[/C][C]-0.147952[/C][C]-1.6207[/C][C]0.05385[/C][/ROW]
[ROW][C]19[/C][C]-0.012628[/C][C]-0.1383[/C][C]0.445104[/C][/ROW]
[ROW][C]20[/C][C]-0.191254[/C][C]-2.0951[/C][C]0.019133[/C][/ROW]
[ROW][C]21[/C][C]-0.021101[/C][C]-0.2312[/C][C]0.408795[/C][/ROW]
[ROW][C]22[/C][C]-0.052818[/C][C]-0.5786[/C][C]0.281973[/C][/ROW]
[ROW][C]23[/C][C]0.014497[/C][C]0.1588[/C][C]0.437044[/C][/ROW]
[ROW][C]24[/C][C]-0.032616[/C][C]-0.3573[/C][C]0.360753[/C][/ROW]
[ROW][C]25[/C][C]0.151856[/C][C]1.6635[/C][C]0.049411[/C][/ROW]
[ROW][C]26[/C][C]0.095069[/C][C]1.0414[/C][C]0.149885[/C][/ROW]
[ROW][C]27[/C][C]-0.009411[/C][C]-0.1031[/C][C]0.459033[/C][/ROW]
[ROW][C]28[/C][C]0.003012[/C][C]0.033[/C][C]0.486865[/C][/ROW]
[ROW][C]29[/C][C]0.009978[/C][C]0.1093[/C][C]0.456571[/C][/ROW]
[ROW][C]30[/C][C]-0.006363[/C][C]-0.0697[/C][C]0.472272[/C][/ROW]
[ROW][C]31[/C][C]-0.170539[/C][C]-1.8682[/C][C]0.032089[/C][/ROW]
[ROW][C]32[/C][C]0.031557[/C][C]0.3457[/C][C]0.36509[/C][/ROW]
[ROW][C]33[/C][C]0.093906[/C][C]1.0287[/C][C]0.152848[/C][/ROW]
[ROW][C]34[/C][C]0.044271[/C][C]0.485[/C][C]0.314294[/C][/ROW]
[ROW][C]35[/C][C]-0.112934[/C][C]-1.2371[/C][C]0.109227[/C][/ROW]
[ROW][C]36[/C][C]-0.031023[/C][C]-0.3398[/C][C]0.367287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69638&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69638&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
1-0.502888-5.50890
2-0.377279-4.13293.3e-05
30.0619830.6790.249226
40.0501230.54910.291991
5-0.074675-0.8180.207482
6-0.115318-1.26320.104475
7-0.234196-2.56550.005767
8-0.249507-2.73320.003611
90.0484280.53050.298371
100.01580.17310.431438
11-0.076185-0.83460.202812
120.1183871.29690.098583
130.0581830.63740.262553
140.012970.14210.443626
150.0937491.0270.153249
160.0105460.11550.45411
170.084120.92150.179322
18-0.147952-1.62070.05385
19-0.012628-0.13830.445104
20-0.191254-2.09510.019133
21-0.021101-0.23120.408795
22-0.052818-0.57860.281973
230.0144970.15880.437044
24-0.032616-0.35730.360753
250.1518561.66350.049411
260.0950691.04140.149885
27-0.009411-0.10310.459033
280.0030120.0330.486865
290.0099780.10930.456571
30-0.006363-0.06970.472272
31-0.170539-1.86820.032089
320.0315570.34570.36509
330.0939061.02870.152848
340.0442710.4850.314294
35-0.112934-1.23710.109227
36-0.031023-0.33980.367287


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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')