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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Fri, 16 Dec 2016 17:39:43 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/16/t14819064644hrjr4w4utjcjwb.htm/, Retrieved Thu, 02 May 2024 19:56:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300437, Retrieved Thu, 02 May 2024 19:56:32 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [ARIMA Backward Selection] [] [2016-12-16 13:36:55] [683f400e1b95307fc738e729f07c4fce]
-    D  [ARIMA Backward Selection] [] [2016-12-16 14:17:56] [683f400e1b95307fc738e729f07c4fce]
- R  D    [ARIMA Backward Selection] [] [2016-12-16 14:51:40] [683f400e1b95307fc738e729f07c4fce]
- RM D        [(Partial) Autocorrelation Function] [] [2016-12-16 16:39:43] [404ac5ee4f7301873f6a96ef36861981] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300437&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=300437&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300437&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.324095	-2.2917	0.013085
2	-0.181776	-1.2853	0.102296
3	0.066643	0.4712	0.319761
4	-0.120246	-0.8503	0.199614
5	-0.039906	-0.2822	0.389487
6	0.025655	0.1814	0.428391
7	0.198726	1.4052	0.083071
8	-0.164575	-1.1637	0.12503
9	0.048343	0.3418	0.366954
10	0.070388	0.4977	0.310432
11	-0.108171	-0.7649	0.223968
12	0.026564	0.1878	0.425884
13	-0.046335	-0.3276	0.372277
14	0.113089	0.7997	0.213846
15	-0.010237	-0.0724	0.471291
16	-0.087925	-0.6217	0.268475
17	0.041023	0.2901	0.38648
18	-0.064475	-0.4559	0.325215
19	0.134275	0.9495	0.173475
20	-0.046862	-0.3314	0.370878
21	0.005603	0.0396	0.484278
22	0.033139	0.2343	0.407844
23	-0.158678	-1.122	0.133606
24	0.039927	0.2823	0.38943
25	-0.014989	-0.106	0.458007
26	0.156167	1.1043	0.137382
27	-0.006511	-0.046	0.481731
28	-0.080652	-0.5703	0.285515
29	-0.004646	-0.0328	0.486963
30	0.036774	0.26	0.397954
31	-0.067174	-0.475	0.31843
32	-0.035082	-0.2481	0.402549
33	0.122523	0.8664	0.195213
34	-0.082529	-0.5836	0.281066
35	0.045332	0.3205	0.374944
36	0.03567	0.2522	0.400949

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.324095 & -2.2917 & 0.013085 \tabularnewline
2 & -0.181776 & -1.2853 & 0.102296 \tabularnewline
3 & 0.066643 & 0.4712 & 0.319761 \tabularnewline
4 & -0.120246 & -0.8503 & 0.199614 \tabularnewline
5 & -0.039906 & -0.2822 & 0.389487 \tabularnewline
6 & 0.025655 & 0.1814 & 0.428391 \tabularnewline
7 & 0.198726 & 1.4052 & 0.083071 \tabularnewline
8 & -0.164575 & -1.1637 & 0.12503 \tabularnewline
9 & 0.048343 & 0.3418 & 0.366954 \tabularnewline
10 & 0.070388 & 0.4977 & 0.310432 \tabularnewline
11 & -0.108171 & -0.7649 & 0.223968 \tabularnewline
12 & 0.026564 & 0.1878 & 0.425884 \tabularnewline
13 & -0.046335 & -0.3276 & 0.372277 \tabularnewline
14 & 0.113089 & 0.7997 & 0.213846 \tabularnewline
15 & -0.010237 & -0.0724 & 0.471291 \tabularnewline
16 & -0.087925 & -0.6217 & 0.268475 \tabularnewline
17 & 0.041023 & 0.2901 & 0.38648 \tabularnewline
18 & -0.064475 & -0.4559 & 0.325215 \tabularnewline
19 & 0.134275 & 0.9495 & 0.173475 \tabularnewline
20 & -0.046862 & -0.3314 & 0.370878 \tabularnewline
21 & 0.005603 & 0.0396 & 0.484278 \tabularnewline
22 & 0.033139 & 0.2343 & 0.407844 \tabularnewline
23 & -0.158678 & -1.122 & 0.133606 \tabularnewline
24 & 0.039927 & 0.2823 & 0.38943 \tabularnewline
25 & -0.014989 & -0.106 & 0.458007 \tabularnewline
26 & 0.156167 & 1.1043 & 0.137382 \tabularnewline
27 & -0.006511 & -0.046 & 0.481731 \tabularnewline
28 & -0.080652 & -0.5703 & 0.285515 \tabularnewline
29 & -0.004646 & -0.0328 & 0.486963 \tabularnewline
30 & 0.036774 & 0.26 & 0.397954 \tabularnewline
31 & -0.067174 & -0.475 & 0.31843 \tabularnewline
32 & -0.035082 & -0.2481 & 0.402549 \tabularnewline
33 & 0.122523 & 0.8664 & 0.195213 \tabularnewline
34 & -0.082529 & -0.5836 & 0.281066 \tabularnewline
35 & 0.045332 & 0.3205 & 0.374944 \tabularnewline
36 & 0.03567 & 0.2522 & 0.400949 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300437&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]-0.324095[/C][C]-2.2917[/C][C]0.013085[/C][/ROW]
[ROW][C]2[/C][C]-0.181776[/C][C]-1.2853[/C][C]0.102296[/C][/ROW]
[ROW][C]3[/C][C]0.066643[/C][C]0.4712[/C][C]0.319761[/C][/ROW]
[ROW][C]4[/C][C]-0.120246[/C][C]-0.8503[/C][C]0.199614[/C][/ROW]
[ROW][C]5[/C][C]-0.039906[/C][C]-0.2822[/C][C]0.389487[/C][/ROW]
[ROW][C]6[/C][C]0.025655[/C][C]0.1814[/C][C]0.428391[/C][/ROW]
[ROW][C]7[/C][C]0.198726[/C][C]1.4052[/C][C]0.083071[/C][/ROW]
[ROW][C]8[/C][C]-0.164575[/C][C]-1.1637[/C][C]0.12503[/C][/ROW]
[ROW][C]9[/C][C]0.048343[/C][C]0.3418[/C][C]0.366954[/C][/ROW]
[ROW][C]10[/C][C]0.070388[/C][C]0.4977[/C][C]0.310432[/C][/ROW]
[ROW][C]11[/C][C]-0.108171[/C][C]-0.7649[/C][C]0.223968[/C][/ROW]
[ROW][C]12[/C][C]0.026564[/C][C]0.1878[/C][C]0.425884[/C][/ROW]
[ROW][C]13[/C][C]-0.046335[/C][C]-0.3276[/C][C]0.372277[/C][/ROW]
[ROW][C]14[/C][C]0.113089[/C][C]0.7997[/C][C]0.213846[/C][/ROW]
[ROW][C]15[/C][C]-0.010237[/C][C]-0.0724[/C][C]0.471291[/C][/ROW]
[ROW][C]16[/C][C]-0.087925[/C][C]-0.6217[/C][C]0.268475[/C][/ROW]
[ROW][C]17[/C][C]0.041023[/C][C]0.2901[/C][C]0.38648[/C][/ROW]
[ROW][C]18[/C][C]-0.064475[/C][C]-0.4559[/C][C]0.325215[/C][/ROW]
[ROW][C]19[/C][C]0.134275[/C][C]0.9495[/C][C]0.173475[/C][/ROW]
[ROW][C]20[/C][C]-0.046862[/C][C]-0.3314[/C][C]0.370878[/C][/ROW]
[ROW][C]21[/C][C]0.005603[/C][C]0.0396[/C][C]0.484278[/C][/ROW]
[ROW][C]22[/C][C]0.033139[/C][C]0.2343[/C][C]0.407844[/C][/ROW]
[ROW][C]23[/C][C]-0.158678[/C][C]-1.122[/C][C]0.133606[/C][/ROW]
[ROW][C]24[/C][C]0.039927[/C][C]0.2823[/C][C]0.38943[/C][/ROW]
[ROW][C]25[/C][C]-0.014989[/C][C]-0.106[/C][C]0.458007[/C][/ROW]
[ROW][C]26[/C][C]0.156167[/C][C]1.1043[/C][C]0.137382[/C][/ROW]
[ROW][C]27[/C][C]-0.006511[/C][C]-0.046[/C][C]0.481731[/C][/ROW]
[ROW][C]28[/C][C]-0.080652[/C][C]-0.5703[/C][C]0.285515[/C][/ROW]
[ROW][C]29[/C][C]-0.004646[/C][C]-0.0328[/C][C]0.486963[/C][/ROW]
[ROW][C]30[/C][C]0.036774[/C][C]0.26[/C][C]0.397954[/C][/ROW]
[ROW][C]31[/C][C]-0.067174[/C][C]-0.475[/C][C]0.31843[/C][/ROW]
[ROW][C]32[/C][C]-0.035082[/C][C]-0.2481[/C][C]0.402549[/C][/ROW]
[ROW][C]33[/C][C]0.122523[/C][C]0.8664[/C][C]0.195213[/C][/ROW]
[ROW][C]34[/C][C]-0.082529[/C][C]-0.5836[/C][C]0.281066[/C][/ROW]
[ROW][C]35[/C][C]0.045332[/C][C]0.3205[/C][C]0.374944[/C][/ROW]
[ROW][C]36[/C][C]0.03567[/C][C]0.2522[/C][C]0.400949[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300437&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300437&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.324095	-2.2917	0.013085
2	-0.181776	-1.2853	0.102296
3	0.066643	0.4712	0.319761
4	-0.120246	-0.8503	0.199614
5	-0.039906	-0.2822	0.389487
6	0.025655	0.1814	0.428391
7	0.198726	1.4052	0.083071
8	-0.164575	-1.1637	0.12503
9	0.048343	0.3418	0.366954
10	0.070388	0.4977	0.310432
11	-0.108171	-0.7649	0.223968
12	0.026564	0.1878	0.425884
13	-0.046335	-0.3276	0.372277
14	0.113089	0.7997	0.213846
15	-0.010237	-0.0724	0.471291
16	-0.087925	-0.6217	0.268475
17	0.041023	0.2901	0.38648
18	-0.064475	-0.4559	0.325215
19	0.134275	0.9495	0.173475
20	-0.046862	-0.3314	0.370878
21	0.005603	0.0396	0.484278
22	0.033139	0.2343	0.407844
23	-0.158678	-1.122	0.133606
24	0.039927	0.2823	0.38943
25	-0.014989	-0.106	0.458007
26	0.156167	1.1043	0.137382
27	-0.006511	-0.046	0.481731
28	-0.080652	-0.5703	0.285515
29	-0.004646	-0.0328	0.486963
30	0.036774	0.26	0.397954
31	-0.067174	-0.475	0.31843
32	-0.035082	-0.2481	0.402549
33	0.122523	0.8664	0.195213
34	-0.082529	-0.5836	0.281066
35	0.045332	0.3205	0.374944
36	0.03567	0.2522	0.400949

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.324095	-2.2917	0.013085
2	-0.320475	-2.2661	0.013903
3	-0.143222	-1.0127	0.158031
4	-0.259964	-1.8382	0.035987
5	-0.275405	-1.9474	0.028556
6	-0.294748	-2.0842	0.021137
7	-0.020024	-0.1416	0.443987
8	-0.219698	-1.5535	0.063306
9	-0.112052	-0.7923	0.215956
10	-0.052105	-0.3684	0.35705
11	-0.065952	-0.4664	0.321494
12	-0.031781	-0.2247	0.411554
13	-0.122063	-0.8631	0.196098
14	0.037218	0.2632	0.396749
15	0.094216	0.6662	0.25417
16	-0.023348	-0.1651	0.434767
17	-0.007744	-0.0548	0.478276
18	-0.069922	-0.4944	0.311585
19	0.12279	0.8683	0.194701
20	0.064642	0.4571	0.324794
21	0.069382	0.4906	0.312926
22	0.145486	1.0287	0.154275
23	0.001972	0.0139	0.494465
24	-0.045596	-0.3224	0.374242
25	-0.139953	-0.9896	0.163563
26	0.030888	0.2184	0.413999
27	0.073906	0.5226	0.301783
28	-0.039747	-0.2811	0.389915
29	-0.121639	-0.8601	0.196915
30	0.110108	0.7786	0.219947
31	-0.000991	-0.007	0.497219
32	-0.059635	-0.4217	0.337533
33	-0.030486	-0.2156	0.4151
34	-0.090249	-0.6382	0.263143
35	0.03437	0.243	0.404487
36	-0.067988	-0.4807	0.316397

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.324095 & -2.2917 & 0.013085 \tabularnewline
2 & -0.320475 & -2.2661 & 0.013903 \tabularnewline
3 & -0.143222 & -1.0127 & 0.158031 \tabularnewline
4 & -0.259964 & -1.8382 & 0.035987 \tabularnewline
5 & -0.275405 & -1.9474 & 0.028556 \tabularnewline
6 & -0.294748 & -2.0842 & 0.021137 \tabularnewline
7 & -0.020024 & -0.1416 & 0.443987 \tabularnewline
8 & -0.219698 & -1.5535 & 0.063306 \tabularnewline
9 & -0.112052 & -0.7923 & 0.215956 \tabularnewline
10 & -0.052105 & -0.3684 & 0.35705 \tabularnewline
11 & -0.065952 & -0.4664 & 0.321494 \tabularnewline
12 & -0.031781 & -0.2247 & 0.411554 \tabularnewline
13 & -0.122063 & -0.8631 & 0.196098 \tabularnewline
14 & 0.037218 & 0.2632 & 0.396749 \tabularnewline
15 & 0.094216 & 0.6662 & 0.25417 \tabularnewline
16 & -0.023348 & -0.1651 & 0.434767 \tabularnewline
17 & -0.007744 & -0.0548 & 0.478276 \tabularnewline
18 & -0.069922 & -0.4944 & 0.311585 \tabularnewline
19 & 0.12279 & 0.8683 & 0.194701 \tabularnewline
20 & 0.064642 & 0.4571 & 0.324794 \tabularnewline
21 & 0.069382 & 0.4906 & 0.312926 \tabularnewline
22 & 0.145486 & 1.0287 & 0.154275 \tabularnewline
23 & 0.001972 & 0.0139 & 0.494465 \tabularnewline
24 & -0.045596 & -0.3224 & 0.374242 \tabularnewline
25 & -0.139953 & -0.9896 & 0.163563 \tabularnewline
26 & 0.030888 & 0.2184 & 0.413999 \tabularnewline
27 & 0.073906 & 0.5226 & 0.301783 \tabularnewline
28 & -0.039747 & -0.2811 & 0.389915 \tabularnewline
29 & -0.121639 & -0.8601 & 0.196915 \tabularnewline
30 & 0.110108 & 0.7786 & 0.219947 \tabularnewline
31 & -0.000991 & -0.007 & 0.497219 \tabularnewline
32 & -0.059635 & -0.4217 & 0.337533 \tabularnewline
33 & -0.030486 & -0.2156 & 0.4151 \tabularnewline
34 & -0.090249 & -0.6382 & 0.263143 \tabularnewline
35 & 0.03437 & 0.243 & 0.404487 \tabularnewline
36 & -0.067988 & -0.4807 & 0.316397 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300437&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]-0.324095[/C][C]-2.2917[/C][C]0.013085[/C][/ROW]
[ROW][C]2[/C][C]-0.320475[/C][C]-2.2661[/C][C]0.013903[/C][/ROW]
[ROW][C]3[/C][C]-0.143222[/C][C]-1.0127[/C][C]0.158031[/C][/ROW]
[ROW][C]4[/C][C]-0.259964[/C][C]-1.8382[/C][C]0.035987[/C][/ROW]
[ROW][C]5[/C][C]-0.275405[/C][C]-1.9474[/C][C]0.028556[/C][/ROW]
[ROW][C]6[/C][C]-0.294748[/C][C]-2.0842[/C][C]0.021137[/C][/ROW]
[ROW][C]7[/C][C]-0.020024[/C][C]-0.1416[/C][C]0.443987[/C][/ROW]
[ROW][C]8[/C][C]-0.219698[/C][C]-1.5535[/C][C]0.063306[/C][/ROW]
[ROW][C]9[/C][C]-0.112052[/C][C]-0.7923[/C][C]0.215956[/C][/ROW]
[ROW][C]10[/C][C]-0.052105[/C][C]-0.3684[/C][C]0.35705[/C][/ROW]
[ROW][C]11[/C][C]-0.065952[/C][C]-0.4664[/C][C]0.321494[/C][/ROW]
[ROW][C]12[/C][C]-0.031781[/C][C]-0.2247[/C][C]0.411554[/C][/ROW]
[ROW][C]13[/C][C]-0.122063[/C][C]-0.8631[/C][C]0.196098[/C][/ROW]
[ROW][C]14[/C][C]0.037218[/C][C]0.2632[/C][C]0.396749[/C][/ROW]
[ROW][C]15[/C][C]0.094216[/C][C]0.6662[/C][C]0.25417[/C][/ROW]
[ROW][C]16[/C][C]-0.023348[/C][C]-0.1651[/C][C]0.434767[/C][/ROW]
[ROW][C]17[/C][C]-0.007744[/C][C]-0.0548[/C][C]0.478276[/C][/ROW]
[ROW][C]18[/C][C]-0.069922[/C][C]-0.4944[/C][C]0.311585[/C][/ROW]
[ROW][C]19[/C][C]0.12279[/C][C]0.8683[/C][C]0.194701[/C][/ROW]
[ROW][C]20[/C][C]0.064642[/C][C]0.4571[/C][C]0.324794[/C][/ROW]
[ROW][C]21[/C][C]0.069382[/C][C]0.4906[/C][C]0.312926[/C][/ROW]
[ROW][C]22[/C][C]0.145486[/C][C]1.0287[/C][C]0.154275[/C][/ROW]
[ROW][C]23[/C][C]0.001972[/C][C]0.0139[/C][C]0.494465[/C][/ROW]
[ROW][C]24[/C][C]-0.045596[/C][C]-0.3224[/C][C]0.374242[/C][/ROW]
[ROW][C]25[/C][C]-0.139953[/C][C]-0.9896[/C][C]0.163563[/C][/ROW]
[ROW][C]26[/C][C]0.030888[/C][C]0.2184[/C][C]0.413999[/C][/ROW]
[ROW][C]27[/C][C]0.073906[/C][C]0.5226[/C][C]0.301783[/C][/ROW]
[ROW][C]28[/C][C]-0.039747[/C][C]-0.2811[/C][C]0.389915[/C][/ROW]
[ROW][C]29[/C][C]-0.121639[/C][C]-0.8601[/C][C]0.196915[/C][/ROW]
[ROW][C]30[/C][C]0.110108[/C][C]0.7786[/C][C]0.219947[/C][/ROW]
[ROW][C]31[/C][C]-0.000991[/C][C]-0.007[/C][C]0.497219[/C][/ROW]
[ROW][C]32[/C][C]-0.059635[/C][C]-0.4217[/C][C]0.337533[/C][/ROW]
[ROW][C]33[/C][C]-0.030486[/C][C]-0.2156[/C][C]0.4151[/C][/ROW]
[ROW][C]34[/C][C]-0.090249[/C][C]-0.6382[/C][C]0.263143[/C][/ROW]
[ROW][C]35[/C][C]0.03437[/C][C]0.243[/C][C]0.404487[/C][/ROW]
[ROW][C]36[/C][C]-0.067988[/C][C]-0.4807[/C][C]0.316397[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300437&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300437&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.324095	-2.2917	0.013085
2	-0.320475	-2.2661	0.013903
3	-0.143222	-1.0127	0.158031
4	-0.259964	-1.8382	0.035987
5	-0.275405	-1.9474	0.028556
6	-0.294748	-2.0842	0.021137
7	-0.020024	-0.1416	0.443987
8	-0.219698	-1.5535	0.063306
9	-0.112052	-0.7923	0.215956
10	-0.052105	-0.3684	0.35705
11	-0.065952	-0.4664	0.321494
12	-0.031781	-0.2247	0.411554
13	-0.122063	-0.8631	0.196098
14	0.037218	0.2632	0.396749
15	0.094216	0.6662	0.25417
16	-0.023348	-0.1651	0.434767
17	-0.007744	-0.0548	0.478276
18	-0.069922	-0.4944	0.311585
19	0.12279	0.8683	0.194701
20	0.064642	0.4571	0.324794
21	0.069382	0.4906	0.312926
22	0.145486	1.0287	0.154275
23	0.001972	0.0139	0.494465
24	-0.045596	-0.3224	0.374242
25	-0.139953	-0.9896	0.163563
26	0.030888	0.2184	0.413999
27	0.073906	0.5226	0.301783
28	-0.039747	-0.2811	0.389915
29	-0.121639	-0.8601	0.196915
30	0.110108	0.7786	0.219947
31	-0.000991	-0.007	0.497219
32	-0.059635	-0.4217	0.337533
33	-0.030486	-0.2156	0.4151
34	-0.090249	-0.6382	0.263143
35	0.03437	0.243	0.404487
36	-0.067988	-0.4807	0.316397

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = FALSE ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 1 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 0 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;

R code (references can be found in the software module):

par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '0'
par2 <- '1'
par1 <- 'Default'
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 (par8 != '') par8 <- as.numeric(par8)
x <- na.omit(x)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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,'ACF(k)',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,'PACF(k)',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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code