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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 computationThu, 25 Nov 2010 16:59:27 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/25/t1290704266yj12kaunmy971hf.htm/, Retrieved Fri, 19 Apr 2024 16:22:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=101239, Retrieved Fri, 19 Apr 2024 16:22:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
-    D          [(Partial) Autocorrelation Function] [Methode 1 (D=0, d=0)] [2009-11-27 12:01:23] [76ab39dc7a55316678260825bd5ad46c]
-    D            [(Partial) Autocorrelation Function] [methode 1 (d=0 D= 0)] [2009-11-27 20:21:42] [4b453aa14d54730625f8d3de5f1f6d82]
-    D              [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:04:55] [7773f496f69461f4a67891f0ef752622]
-   PD                [(Partial) Autocorrelation Function] [Appelen Jonagold ...] [2009-12-17 16:56:03] [7773f496f69461f4a67891f0ef752622]
-   P                   [(Partial) Autocorrelation Function] [Appelen Jonagold ...] [2009-12-19 09:43:35] [7773f496f69461f4a67891f0ef752622]
-   PD                      [(Partial) Autocorrelation Function] [WS8 4] [2010-11-25 16:59:27] [c1f1b5e209adb4577289f490325e36f2] [Current]
-    D                        [(Partial) Autocorrelation Function] [WS8 6] [2010-11-25 18:04:29] [717f3d787904f94c39256c5c1fc72d4c]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
 1.3031
 1.3241
 1.2961
 1.2865
 1.2305
 1.2101
 1.2125
 1.2350
 1.2014
 1.1992
 1.1791
 1.1832
 1.2159
 1.1922
 1.2114
 1.2614
 1.2812
 1.2786
 1.2772
 1.2815
 1.2679
 1.2765
 1.3247
 1.3191
 1.3029
 1.3234
 1.3354
 1.3651
 1.3453
 1.3534
 1.3706
 1.3638
 1.4268
 1.4485
 1.4635
 1.4587
 1.4876
 1.5189
 1.5783
 1.5633
 1.5554
 1.5757
 1.5593
 1.4660
 1.4065
 1.2759
 1.2705
 1.3954
 1.2793
 1.2694
 1.3282
 1.3230
 1.4135
 1.4042
 1.4253
 1.4322
 1.4632
 1.4713
 1.5016
 1.4318

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101239&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101239&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101239&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0103120.07920.468569
2-0.02522-0.19370.423532
30.1646121.26440.105527
4-0.07536-0.57890.282446
50.1426921.0960.138758
60.0318850.24490.403688
7-0.33584-2.57960.006201
8-0.113863-0.87460.192669
9-0.068943-0.52960.299202
10-0.091364-0.70180.242788
110.0134890.10360.458916
12-0.219313-1.68460.048677
13-0.153105-1.1760.122155
140.1210030.92940.178223
150.116760.89680.186722
160.0292990.2250.41136
170.0280830.21570.41498
18-0.01639-0.12590.450123
19-0.031704-0.24350.404223
200.1570381.20620.116271
21-0.063181-0.48530.314629
220.0001850.00140.499436
23-0.085253-0.65480.257559
240.0002860.00220.499126
250.1069830.82180.207263
26-0.018354-0.1410.444182
27-0.090608-0.6960.24459
28-0.087058-0.66870.253146
29-0.081978-0.62970.265667
30-0.070313-0.54010.295586
310.0323910.24880.402189
320.0029950.0230.490862
33-0.088474-0.67960.249713
34-0.073928-0.56790.286144
350.159191.22280.113141
360.0071610.0550.478159

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.010312 & 0.0792 & 0.468569 \tabularnewline
2 & -0.02522 & -0.1937 & 0.423532 \tabularnewline
3 & 0.164612 & 1.2644 & 0.105527 \tabularnewline
4 & -0.07536 & -0.5789 & 0.282446 \tabularnewline
5 & 0.142692 & 1.096 & 0.138758 \tabularnewline
6 & 0.031885 & 0.2449 & 0.403688 \tabularnewline
7 & -0.33584 & -2.5796 & 0.006201 \tabularnewline
8 & -0.113863 & -0.8746 & 0.192669 \tabularnewline
9 & -0.068943 & -0.5296 & 0.299202 \tabularnewline
10 & -0.091364 & -0.7018 & 0.242788 \tabularnewline
11 & 0.013489 & 0.1036 & 0.458916 \tabularnewline
12 & -0.219313 & -1.6846 & 0.048677 \tabularnewline
13 & -0.153105 & -1.176 & 0.122155 \tabularnewline
14 & 0.121003 & 0.9294 & 0.178223 \tabularnewline
15 & 0.11676 & 0.8968 & 0.186722 \tabularnewline
16 & 0.029299 & 0.225 & 0.41136 \tabularnewline
17 & 0.028083 & 0.2157 & 0.41498 \tabularnewline
18 & -0.01639 & -0.1259 & 0.450123 \tabularnewline
19 & -0.031704 & -0.2435 & 0.404223 \tabularnewline
20 & 0.157038 & 1.2062 & 0.116271 \tabularnewline
21 & -0.063181 & -0.4853 & 0.314629 \tabularnewline
22 & 0.000185 & 0.0014 & 0.499436 \tabularnewline
23 & -0.085253 & -0.6548 & 0.257559 \tabularnewline
24 & 0.000286 & 0.0022 & 0.499126 \tabularnewline
25 & 0.106983 & 0.8218 & 0.207263 \tabularnewline
26 & -0.018354 & -0.141 & 0.444182 \tabularnewline
27 & -0.090608 & -0.696 & 0.24459 \tabularnewline
28 & -0.087058 & -0.6687 & 0.253146 \tabularnewline
29 & -0.081978 & -0.6297 & 0.265667 \tabularnewline
30 & -0.070313 & -0.5401 & 0.295586 \tabularnewline
31 & 0.032391 & 0.2488 & 0.402189 \tabularnewline
32 & 0.002995 & 0.023 & 0.490862 \tabularnewline
33 & -0.088474 & -0.6796 & 0.249713 \tabularnewline
34 & -0.073928 & -0.5679 & 0.286144 \tabularnewline
35 & 0.15919 & 1.2228 & 0.113141 \tabularnewline
36 & 0.007161 & 0.055 & 0.478159 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101239&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]0.010312[/C][C]0.0792[/C][C]0.468569[/C][/ROW]
[ROW][C]2[/C][C]-0.02522[/C][C]-0.1937[/C][C]0.423532[/C][/ROW]
[ROW][C]3[/C][C]0.164612[/C][C]1.2644[/C][C]0.105527[/C][/ROW]
[ROW][C]4[/C][C]-0.07536[/C][C]-0.5789[/C][C]0.282446[/C][/ROW]
[ROW][C]5[/C][C]0.142692[/C][C]1.096[/C][C]0.138758[/C][/ROW]
[ROW][C]6[/C][C]0.031885[/C][C]0.2449[/C][C]0.403688[/C][/ROW]
[ROW][C]7[/C][C]-0.33584[/C][C]-2.5796[/C][C]0.006201[/C][/ROW]
[ROW][C]8[/C][C]-0.113863[/C][C]-0.8746[/C][C]0.192669[/C][/ROW]
[ROW][C]9[/C][C]-0.068943[/C][C]-0.5296[/C][C]0.299202[/C][/ROW]
[ROW][C]10[/C][C]-0.091364[/C][C]-0.7018[/C][C]0.242788[/C][/ROW]
[ROW][C]11[/C][C]0.013489[/C][C]0.1036[/C][C]0.458916[/C][/ROW]
[ROW][C]12[/C][C]-0.219313[/C][C]-1.6846[/C][C]0.048677[/C][/ROW]
[ROW][C]13[/C][C]-0.153105[/C][C]-1.176[/C][C]0.122155[/C][/ROW]
[ROW][C]14[/C][C]0.121003[/C][C]0.9294[/C][C]0.178223[/C][/ROW]
[ROW][C]15[/C][C]0.11676[/C][C]0.8968[/C][C]0.186722[/C][/ROW]
[ROW][C]16[/C][C]0.029299[/C][C]0.225[/C][C]0.41136[/C][/ROW]
[ROW][C]17[/C][C]0.028083[/C][C]0.2157[/C][C]0.41498[/C][/ROW]
[ROW][C]18[/C][C]-0.01639[/C][C]-0.1259[/C][C]0.450123[/C][/ROW]
[ROW][C]19[/C][C]-0.031704[/C][C]-0.2435[/C][C]0.404223[/C][/ROW]
[ROW][C]20[/C][C]0.157038[/C][C]1.2062[/C][C]0.116271[/C][/ROW]
[ROW][C]21[/C][C]-0.063181[/C][C]-0.4853[/C][C]0.314629[/C][/ROW]
[ROW][C]22[/C][C]0.000185[/C][C]0.0014[/C][C]0.499436[/C][/ROW]
[ROW][C]23[/C][C]-0.085253[/C][C]-0.6548[/C][C]0.257559[/C][/ROW]
[ROW][C]24[/C][C]0.000286[/C][C]0.0022[/C][C]0.499126[/C][/ROW]
[ROW][C]25[/C][C]0.106983[/C][C]0.8218[/C][C]0.207263[/C][/ROW]
[ROW][C]26[/C][C]-0.018354[/C][C]-0.141[/C][C]0.444182[/C][/ROW]
[ROW][C]27[/C][C]-0.090608[/C][C]-0.696[/C][C]0.24459[/C][/ROW]
[ROW][C]28[/C][C]-0.087058[/C][C]-0.6687[/C][C]0.253146[/C][/ROW]
[ROW][C]29[/C][C]-0.081978[/C][C]-0.6297[/C][C]0.265667[/C][/ROW]
[ROW][C]30[/C][C]-0.070313[/C][C]-0.5401[/C][C]0.295586[/C][/ROW]
[ROW][C]31[/C][C]0.032391[/C][C]0.2488[/C][C]0.402189[/C][/ROW]
[ROW][C]32[/C][C]0.002995[/C][C]0.023[/C][C]0.490862[/C][/ROW]
[ROW][C]33[/C][C]-0.088474[/C][C]-0.6796[/C][C]0.249713[/C][/ROW]
[ROW][C]34[/C][C]-0.073928[/C][C]-0.5679[/C][C]0.286144[/C][/ROW]
[ROW][C]35[/C][C]0.15919[/C][C]1.2228[/C][C]0.113141[/C][/ROW]
[ROW][C]36[/C][C]0.007161[/C][C]0.055[/C][C]0.478159[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101239&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101239&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
10.0103120.07920.468569
2-0.02522-0.19370.423532
30.1646121.26440.105527
4-0.07536-0.57890.282446
50.1426921.0960.138758
60.0318850.24490.403688
7-0.33584-2.57960.006201
8-0.113863-0.87460.192669
9-0.068943-0.52960.299202
10-0.091364-0.70180.242788
110.0134890.10360.458916
12-0.219313-1.68460.048677
13-0.153105-1.1760.122155
140.1210030.92940.178223
150.116760.89680.186722
160.0292990.2250.41136
170.0280830.21570.41498
18-0.01639-0.12590.450123
19-0.031704-0.24350.404223
200.1570381.20620.116271
21-0.063181-0.48530.314629
220.0001850.00140.499436
23-0.085253-0.65480.257559
240.0002860.00220.499126
250.1069830.82180.207263
26-0.018354-0.1410.444182
27-0.090608-0.6960.24459
28-0.087058-0.66870.253146
29-0.081978-0.62970.265667
30-0.070313-0.54010.295586
310.0323910.24880.402189
320.0029950.0230.490862
33-0.088474-0.67960.249713
34-0.073928-0.56790.286144
350.159191.22280.113141
360.0071610.0550.478159






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0103120.07920.468569
2-0.025329-0.19460.423206
30.1652641.26940.104639
4-0.082489-0.63360.264391
50.1602591.2310.111609
6-0.010949-0.08410.466631
7-0.3163-2.42950.00909
8-0.169722-1.30370.098707
9-0.08035-0.61720.269745
10-0.016749-0.12870.449036
110.0180040.13830.445242
12-0.139218-1.06940.144633
13-0.116396-0.89410.187462
140.026340.20230.42018
150.123120.94570.174078
160.0003730.00290.498863
17-0.007993-0.06140.475627
18-0.027437-0.21070.416905
19-0.19422-1.49180.070536
20-0.008999-0.06910.472563
21-0.096973-0.74490.229656
220.1062190.81590.208925
23-0.103272-0.79330.215405
240.0645380.49570.310964
250.0280020.21510.415221
26-0.016012-0.1230.451267
27-0.041495-0.31870.375529
28-0.136355-1.04740.149602
29-0.130052-0.99890.160949
30-0.2228-1.71140.046134
31-0.030774-0.23640.406977
320.08960.68820.247003
33-0.019515-0.14990.440678
34-0.101734-0.78140.218836
350.0972960.74730.228912
36-0.07473-0.5740.28407

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.010312 & 0.0792 & 0.468569 \tabularnewline
2 & -0.025329 & -0.1946 & 0.423206 \tabularnewline
3 & 0.165264 & 1.2694 & 0.104639 \tabularnewline
4 & -0.082489 & -0.6336 & 0.264391 \tabularnewline
5 & 0.160259 & 1.231 & 0.111609 \tabularnewline
6 & -0.010949 & -0.0841 & 0.466631 \tabularnewline
7 & -0.3163 & -2.4295 & 0.00909 \tabularnewline
8 & -0.169722 & -1.3037 & 0.098707 \tabularnewline
9 & -0.08035 & -0.6172 & 0.269745 \tabularnewline
10 & -0.016749 & -0.1287 & 0.449036 \tabularnewline
11 & 0.018004 & 0.1383 & 0.445242 \tabularnewline
12 & -0.139218 & -1.0694 & 0.144633 \tabularnewline
13 & -0.116396 & -0.8941 & 0.187462 \tabularnewline
14 & 0.02634 & 0.2023 & 0.42018 \tabularnewline
15 & 0.12312 & 0.9457 & 0.174078 \tabularnewline
16 & 0.000373 & 0.0029 & 0.498863 \tabularnewline
17 & -0.007993 & -0.0614 & 0.475627 \tabularnewline
18 & -0.027437 & -0.2107 & 0.416905 \tabularnewline
19 & -0.19422 & -1.4918 & 0.070536 \tabularnewline
20 & -0.008999 & -0.0691 & 0.472563 \tabularnewline
21 & -0.096973 & -0.7449 & 0.229656 \tabularnewline
22 & 0.106219 & 0.8159 & 0.208925 \tabularnewline
23 & -0.103272 & -0.7933 & 0.215405 \tabularnewline
24 & 0.064538 & 0.4957 & 0.310964 \tabularnewline
25 & 0.028002 & 0.2151 & 0.415221 \tabularnewline
26 & -0.016012 & -0.123 & 0.451267 \tabularnewline
27 & -0.041495 & -0.3187 & 0.375529 \tabularnewline
28 & -0.136355 & -1.0474 & 0.149602 \tabularnewline
29 & -0.130052 & -0.9989 & 0.160949 \tabularnewline
30 & -0.2228 & -1.7114 & 0.046134 \tabularnewline
31 & -0.030774 & -0.2364 & 0.406977 \tabularnewline
32 & 0.0896 & 0.6882 & 0.247003 \tabularnewline
33 & -0.019515 & -0.1499 & 0.440678 \tabularnewline
34 & -0.101734 & -0.7814 & 0.218836 \tabularnewline
35 & 0.097296 & 0.7473 & 0.228912 \tabularnewline
36 & -0.07473 & -0.574 & 0.28407 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101239&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]0.010312[/C][C]0.0792[/C][C]0.468569[/C][/ROW]
[ROW][C]2[/C][C]-0.025329[/C][C]-0.1946[/C][C]0.423206[/C][/ROW]
[ROW][C]3[/C][C]0.165264[/C][C]1.2694[/C][C]0.104639[/C][/ROW]
[ROW][C]4[/C][C]-0.082489[/C][C]-0.6336[/C][C]0.264391[/C][/ROW]
[ROW][C]5[/C][C]0.160259[/C][C]1.231[/C][C]0.111609[/C][/ROW]
[ROW][C]6[/C][C]-0.010949[/C][C]-0.0841[/C][C]0.466631[/C][/ROW]
[ROW][C]7[/C][C]-0.3163[/C][C]-2.4295[/C][C]0.00909[/C][/ROW]
[ROW][C]8[/C][C]-0.169722[/C][C]-1.3037[/C][C]0.098707[/C][/ROW]
[ROW][C]9[/C][C]-0.08035[/C][C]-0.6172[/C][C]0.269745[/C][/ROW]
[ROW][C]10[/C][C]-0.016749[/C][C]-0.1287[/C][C]0.449036[/C][/ROW]
[ROW][C]11[/C][C]0.018004[/C][C]0.1383[/C][C]0.445242[/C][/ROW]
[ROW][C]12[/C][C]-0.139218[/C][C]-1.0694[/C][C]0.144633[/C][/ROW]
[ROW][C]13[/C][C]-0.116396[/C][C]-0.8941[/C][C]0.187462[/C][/ROW]
[ROW][C]14[/C][C]0.02634[/C][C]0.2023[/C][C]0.42018[/C][/ROW]
[ROW][C]15[/C][C]0.12312[/C][C]0.9457[/C][C]0.174078[/C][/ROW]
[ROW][C]16[/C][C]0.000373[/C][C]0.0029[/C][C]0.498863[/C][/ROW]
[ROW][C]17[/C][C]-0.007993[/C][C]-0.0614[/C][C]0.475627[/C][/ROW]
[ROW][C]18[/C][C]-0.027437[/C][C]-0.2107[/C][C]0.416905[/C][/ROW]
[ROW][C]19[/C][C]-0.19422[/C][C]-1.4918[/C][C]0.070536[/C][/ROW]
[ROW][C]20[/C][C]-0.008999[/C][C]-0.0691[/C][C]0.472563[/C][/ROW]
[ROW][C]21[/C][C]-0.096973[/C][C]-0.7449[/C][C]0.229656[/C][/ROW]
[ROW][C]22[/C][C]0.106219[/C][C]0.8159[/C][C]0.208925[/C][/ROW]
[ROW][C]23[/C][C]-0.103272[/C][C]-0.7933[/C][C]0.215405[/C][/ROW]
[ROW][C]24[/C][C]0.064538[/C][C]0.4957[/C][C]0.310964[/C][/ROW]
[ROW][C]25[/C][C]0.028002[/C][C]0.2151[/C][C]0.415221[/C][/ROW]
[ROW][C]26[/C][C]-0.016012[/C][C]-0.123[/C][C]0.451267[/C][/ROW]
[ROW][C]27[/C][C]-0.041495[/C][C]-0.3187[/C][C]0.375529[/C][/ROW]
[ROW][C]28[/C][C]-0.136355[/C][C]-1.0474[/C][C]0.149602[/C][/ROW]
[ROW][C]29[/C][C]-0.130052[/C][C]-0.9989[/C][C]0.160949[/C][/ROW]
[ROW][C]30[/C][C]-0.2228[/C][C]-1.7114[/C][C]0.046134[/C][/ROW]
[ROW][C]31[/C][C]-0.030774[/C][C]-0.2364[/C][C]0.406977[/C][/ROW]
[ROW][C]32[/C][C]0.0896[/C][C]0.6882[/C][C]0.247003[/C][/ROW]
[ROW][C]33[/C][C]-0.019515[/C][C]-0.1499[/C][C]0.440678[/C][/ROW]
[ROW][C]34[/C][C]-0.101734[/C][C]-0.7814[/C][C]0.218836[/C][/ROW]
[ROW][C]35[/C][C]0.097296[/C][C]0.7473[/C][C]0.228912[/C][/ROW]
[ROW][C]36[/C][C]-0.07473[/C][C]-0.574[/C][C]0.28407[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101239&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101239&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
10.0103120.07920.468569
2-0.025329-0.19460.423206
30.1652641.26940.104639
4-0.082489-0.63360.264391
50.1602591.2310.111609
6-0.010949-0.08410.466631
7-0.3163-2.42950.00909
8-0.169722-1.30370.098707
9-0.08035-0.61720.269745
10-0.016749-0.12870.449036
110.0180040.13830.445242
12-0.139218-1.06940.144633
13-0.116396-0.89410.187462
140.026340.20230.42018
150.123120.94570.174078
160.0003730.00290.498863
17-0.007993-0.06140.475627
18-0.027437-0.21070.416905
19-0.19422-1.49180.070536
20-0.008999-0.06910.472563
21-0.096973-0.74490.229656
220.1062190.81590.208925
23-0.103272-0.79330.215405
240.0645380.49570.310964
250.0280020.21510.415221
26-0.016012-0.1230.451267
27-0.041495-0.31870.375529
28-0.136355-1.04740.149602
29-0.130052-0.99890.160949
30-0.2228-1.71140.046134
31-0.030774-0.23640.406977
320.08960.68820.247003
33-0.019515-0.14990.440678
34-0.101734-0.78140.218836
350.0972960.74730.228912
36-0.07473-0.5740.28407


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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')