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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, 14 Dec 2017 13:03:30 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/14/t15132530729a4npnobqhonc32.htm/, Retrieved Tue, 14 May 2024 15:38:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309473, Retrieved Tue, 14 May 2024 15:38:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2017-12-14 12:03:30] [76161aa76684ab75eda7753df0aa1ca0] [Current]
-         [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2017-12-14 12:03:30] [74be16979710d4c4e7c6647856088456]
- RMPD      [] [(Partial) Autocor...] [9999-12-31 23:59:59] [74be16979710d4c4e7c6647856088456]
- RMPD      [] [] [9999-12-31 23:59:59] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
63.2
68.6
77.7
68.1
75.1
73.3
60.5
65.9
77.7
77.1
77.7
71.3
76
75.3
81.7
72.5
77.4
81.1
65.1
68.7
75.6
79.7
75.3
67.7
73.2
72.2
79.3
77.5
75.6
77.4
69.2
67.1
77.9
82.7
75.7
70.1
76.4
74.3
80.5
78
73.5
78.8
71.2
66.2
82.7
83.8
75
80.4
74.6
77.7
89.8
82.4
77
89.6
75.7
75.1
89.9
88.8
86.5
90
84
82.7
91.7
87.5
82
92.2
73.1
75.6
91.6
87.5
90.1
91.3
87.6
88.4
100.7
85.3
92
96.8
77.9
80.9
95.3
99.3
96.1
92.5
93.7
92.1
103.6
92.5
95.7
103.4
89
89.1
98.7
109.4
101.1
95.4
101.4
102.1
103.6
106
98.4
106.6
95.8
87.2
108.5
107
92
94.9
84.4
85
94
84.5
88.2
92.1
81.1
81.2
96.1
95.3
92.1
91.7
90.3
96.1
108.7
95.9
95.1
109.4
91.2
91.4
107.4
105.6
105.3
103.7
99.5
103.2
123.1
102.2
110
106.2
91.3
99.3
111.8
104.4
102.4
101
100.6
104.5
117.4
97.4
99.5
106.4
95.2
94
104.1
105.8
101.1
93.5
97.9
96.8
108.4
103.5
101.3
107.4
100.7
91.1
105
112.8
105.6
101
101.9
103.5
109.5
105
102.9
108.5
96.9
88.4
112.4
111.3
101.6
101.2
101.8
98.8
114.4
104.5
97.6
109.1
94.5
90.4
111.8
110.5
106.8
101.8
103.7
107.4
117.5
109.6
102.8
115.5
97.8
100.2
112.9
108.7
109
113.9
106.9
109.6
124.5
104.2
110.8
118.7
102.1
105.1

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309473&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]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309473&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309473&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7846211.42420
20.70511310.26660
30.7896111.49690
40.71586610.42320
50.73443810.69360
60.78349411.40790
70.674389.81910
80.6512029.48160
90.6699519.75460
100.5641958.21480
110.6367449.27110
120.75895511.05060
130.5937088.64450
140.529137.70430
150.5856588.52730
160.5396477.85740
170.5591568.14140
180.5983278.71180
190.5094317.41740
200.5001927.28290
210.5088037.40830
220.421926.14320
230.4997667.27670
240.5951538.66560
250.4639886.75580
260.4070915.92730
270.4526526.59070
280.4323826.29560
290.4500976.55350
300.4791636.97670
310.419616.10960
320.4025.85320
330.4037275.87830
340.343855.00651e-06
350.3906535.6880
360.4813767.00890
370.3794235.52450
380.297244.32791.2e-05
390.3473285.05720
400.3304664.81171e-06
410.3249944.7322e-06
420.3582315.21590
430.3029894.41168e-06
440.2645523.85197.8e-05
450.2736813.98494.6e-05
460.2155143.13790.000972
470.236143.43820.000352
480.3363674.89761e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.78462 & 11.4242 & 0 \tabularnewline
2 & 0.705113 & 10.2666 & 0 \tabularnewline
3 & 0.78961 & 11.4969 & 0 \tabularnewline
4 & 0.715866 & 10.4232 & 0 \tabularnewline
5 & 0.734438 & 10.6936 & 0 \tabularnewline
6 & 0.783494 & 11.4079 & 0 \tabularnewline
7 & 0.67438 & 9.8191 & 0 \tabularnewline
8 & 0.651202 & 9.4816 & 0 \tabularnewline
9 & 0.669951 & 9.7546 & 0 \tabularnewline
10 & 0.564195 & 8.2148 & 0 \tabularnewline
11 & 0.636744 & 9.2711 & 0 \tabularnewline
12 & 0.758955 & 11.0506 & 0 \tabularnewline
13 & 0.593708 & 8.6445 & 0 \tabularnewline
14 & 0.52913 & 7.7043 & 0 \tabularnewline
15 & 0.585658 & 8.5273 & 0 \tabularnewline
16 & 0.539647 & 7.8574 & 0 \tabularnewline
17 & 0.559156 & 8.1414 & 0 \tabularnewline
18 & 0.598327 & 8.7118 & 0 \tabularnewline
19 & 0.509431 & 7.4174 & 0 \tabularnewline
20 & 0.500192 & 7.2829 & 0 \tabularnewline
21 & 0.508803 & 7.4083 & 0 \tabularnewline
22 & 0.42192 & 6.1432 & 0 \tabularnewline
23 & 0.499766 & 7.2767 & 0 \tabularnewline
24 & 0.595153 & 8.6656 & 0 \tabularnewline
25 & 0.463988 & 6.7558 & 0 \tabularnewline
26 & 0.407091 & 5.9273 & 0 \tabularnewline
27 & 0.452652 & 6.5907 & 0 \tabularnewline
28 & 0.432382 & 6.2956 & 0 \tabularnewline
29 & 0.450097 & 6.5535 & 0 \tabularnewline
30 & 0.479163 & 6.9767 & 0 \tabularnewline
31 & 0.41961 & 6.1096 & 0 \tabularnewline
32 & 0.402 & 5.8532 & 0 \tabularnewline
33 & 0.403727 & 5.8783 & 0 \tabularnewline
34 & 0.34385 & 5.0065 & 1e-06 \tabularnewline
35 & 0.390653 & 5.688 & 0 \tabularnewline
36 & 0.481376 & 7.0089 & 0 \tabularnewline
37 & 0.379423 & 5.5245 & 0 \tabularnewline
38 & 0.29724 & 4.3279 & 1.2e-05 \tabularnewline
39 & 0.347328 & 5.0572 & 0 \tabularnewline
40 & 0.330466 & 4.8117 & 1e-06 \tabularnewline
41 & 0.324994 & 4.732 & 2e-06 \tabularnewline
42 & 0.358231 & 5.2159 & 0 \tabularnewline
43 & 0.302989 & 4.4116 & 8e-06 \tabularnewline
44 & 0.264552 & 3.8519 & 7.8e-05 \tabularnewline
45 & 0.273681 & 3.9849 & 4.6e-05 \tabularnewline
46 & 0.215514 & 3.1379 & 0.000972 \tabularnewline
47 & 0.23614 & 3.4382 & 0.000352 \tabularnewline
48 & 0.336367 & 4.8976 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309473&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]0.78462[/C][C]11.4242[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.705113[/C][C]10.2666[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.78961[/C][C]11.4969[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.715866[/C][C]10.4232[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.734438[/C][C]10.6936[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.783494[/C][C]11.4079[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.67438[/C][C]9.8191[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.651202[/C][C]9.4816[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.669951[/C][C]9.7546[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.564195[/C][C]8.2148[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.636744[/C][C]9.2711[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.758955[/C][C]11.0506[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.593708[/C][C]8.6445[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.52913[/C][C]7.7043[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.585658[/C][C]8.5273[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.539647[/C][C]7.8574[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.559156[/C][C]8.1414[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.598327[/C][C]8.7118[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.509431[/C][C]7.4174[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.500192[/C][C]7.2829[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.508803[/C][C]7.4083[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.42192[/C][C]6.1432[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.499766[/C][C]7.2767[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.595153[/C][C]8.6656[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.463988[/C][C]6.7558[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.407091[/C][C]5.9273[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.452652[/C][C]6.5907[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]0.432382[/C][C]6.2956[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]0.450097[/C][C]6.5535[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]0.479163[/C][C]6.9767[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]0.41961[/C][C]6.1096[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]0.402[/C][C]5.8532[/C][C]0[/C][/ROW]
[ROW][C]33[/C][C]0.403727[/C][C]5.8783[/C][C]0[/C][/ROW]
[ROW][C]34[/C][C]0.34385[/C][C]5.0065[/C][C]1e-06[/C][/ROW]
[ROW][C]35[/C][C]0.390653[/C][C]5.688[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0.481376[/C][C]7.0089[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.379423[/C][C]5.5245[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]0.29724[/C][C]4.3279[/C][C]1.2e-05[/C][/ROW]
[ROW][C]39[/C][C]0.347328[/C][C]5.0572[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]0.330466[/C][C]4.8117[/C][C]1e-06[/C][/ROW]
[ROW][C]41[/C][C]0.324994[/C][C]4.732[/C][C]2e-06[/C][/ROW]
[ROW][C]42[/C][C]0.358231[/C][C]5.2159[/C][C]0[/C][/ROW]
[ROW][C]43[/C][C]0.302989[/C][C]4.4116[/C][C]8e-06[/C][/ROW]
[ROW][C]44[/C][C]0.264552[/C][C]3.8519[/C][C]7.8e-05[/C][/ROW]
[ROW][C]45[/C][C]0.273681[/C][C]3.9849[/C][C]4.6e-05[/C][/ROW]
[ROW][C]46[/C][C]0.215514[/C][C]3.1379[/C][C]0.000972[/C][/ROW]
[ROW][C]47[/C][C]0.23614[/C][C]3.4382[/C][C]0.000352[/C][/ROW]
[ROW][C]48[/C][C]0.336367[/C][C]4.8976[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309473&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309473&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
10.7846211.42420
20.70511310.26660
30.7896111.49690
40.71586610.42320
50.73443810.69360
60.78349411.40790
70.674389.81910
80.6512029.48160
90.6699519.75460
100.5641958.21480
110.6367449.27110
120.75895511.05060
130.5937088.64450
140.529137.70430
150.5856588.52730
160.5396477.85740
170.5591568.14140
180.5983278.71180
190.5094317.41740
200.5001927.28290
210.5088037.40830
220.421926.14320
230.4997667.27670
240.5951538.66560
250.4639886.75580
260.4070915.92730
270.4526526.59070
280.4323826.29560
290.4500976.55350
300.4791636.97670
310.419616.10960
320.4025.85320
330.4037275.87830
340.343855.00651e-06
350.3906535.6880
360.4813767.00890
370.3794235.52450
380.297244.32791.2e-05
390.3473285.05720
400.3304664.81171e-06
410.3249944.7322e-06
420.3582315.21590
430.3029894.41168e-06
440.2645523.85197.8e-05
450.2736813.98494.6e-05
460.2155143.13790.000972
470.236143.43820.000352
480.3363674.89761e-06






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7846211.42420
20.2328093.38980.000417
30.5020047.30930
4-0.044592-0.64930.258433
50.346915.05110
60.131581.91580.028366
7-0.114821-1.67180.048017
8-0.040703-0.59260.277025
9-0.094674-1.37850.084756
10-0.262168-3.81728.9e-05
110.2848834.1482.4e-05
120.4383736.38280
13-0.210716-3.06810.001218
14-0.229134-3.33620.000501
15-0.100808-1.46780.071822
160.0834361.21480.112889
17-0.058397-0.85030.198066
180.072011.04850.147806
190.0650620.94730.172276
200.054330.79110.214897
21-0.02869-0.41770.338282
22-0.033254-0.48420.314375
230.0497590.72450.234777
240.0861661.25460.105503
25-0.02244-0.32670.372097
26-0.101092-1.47190.071262
27-0.028502-0.4150.339284
280.0705661.02750.152689
29-0.03314-0.48250.314968
300.0171630.24990.401456
310.1001291.45790.073175
32-0.050178-0.73060.232914
33-0.028824-0.41970.337571
34-0.004784-0.06970.472265
35-0.10477-1.52550.064316
360.0764941.11380.133321
370.0205020.29850.382803
38-0.09046-1.31710.094612
390.0010390.01510.49397
40-0.032719-0.47640.317144
41-0.042548-0.61950.268124
42-0.019064-0.27760.390803
430.0338690.49310.311213
44-0.053189-0.77440.219767
450.0077590.1130.45508
46-0.014937-0.21750.414018
47-0.06179-0.89970.184657
480.0751871.09470.137435

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.78462 & 11.4242 & 0 \tabularnewline
2 & 0.232809 & 3.3898 & 0.000417 \tabularnewline
3 & 0.502004 & 7.3093 & 0 \tabularnewline
4 & -0.044592 & -0.6493 & 0.258433 \tabularnewline
5 & 0.34691 & 5.0511 & 0 \tabularnewline
6 & 0.13158 & 1.9158 & 0.028366 \tabularnewline
7 & -0.114821 & -1.6718 & 0.048017 \tabularnewline
8 & -0.040703 & -0.5926 & 0.277025 \tabularnewline
9 & -0.094674 & -1.3785 & 0.084756 \tabularnewline
10 & -0.262168 & -3.8172 & 8.9e-05 \tabularnewline
11 & 0.284883 & 4.148 & 2.4e-05 \tabularnewline
12 & 0.438373 & 6.3828 & 0 \tabularnewline
13 & -0.210716 & -3.0681 & 0.001218 \tabularnewline
14 & -0.229134 & -3.3362 & 0.000501 \tabularnewline
15 & -0.100808 & -1.4678 & 0.071822 \tabularnewline
16 & 0.083436 & 1.2148 & 0.112889 \tabularnewline
17 & -0.058397 & -0.8503 & 0.198066 \tabularnewline
18 & 0.07201 & 1.0485 & 0.147806 \tabularnewline
19 & 0.065062 & 0.9473 & 0.172276 \tabularnewline
20 & 0.05433 & 0.7911 & 0.214897 \tabularnewline
21 & -0.02869 & -0.4177 & 0.338282 \tabularnewline
22 & -0.033254 & -0.4842 & 0.314375 \tabularnewline
23 & 0.049759 & 0.7245 & 0.234777 \tabularnewline
24 & 0.086166 & 1.2546 & 0.105503 \tabularnewline
25 & -0.02244 & -0.3267 & 0.372097 \tabularnewline
26 & -0.101092 & -1.4719 & 0.071262 \tabularnewline
27 & -0.028502 & -0.415 & 0.339284 \tabularnewline
28 & 0.070566 & 1.0275 & 0.152689 \tabularnewline
29 & -0.03314 & -0.4825 & 0.314968 \tabularnewline
30 & 0.017163 & 0.2499 & 0.401456 \tabularnewline
31 & 0.100129 & 1.4579 & 0.073175 \tabularnewline
32 & -0.050178 & -0.7306 & 0.232914 \tabularnewline
33 & -0.028824 & -0.4197 & 0.337571 \tabularnewline
34 & -0.004784 & -0.0697 & 0.472265 \tabularnewline
35 & -0.10477 & -1.5255 & 0.064316 \tabularnewline
36 & 0.076494 & 1.1138 & 0.133321 \tabularnewline
37 & 0.020502 & 0.2985 & 0.382803 \tabularnewline
38 & -0.09046 & -1.3171 & 0.094612 \tabularnewline
39 & 0.001039 & 0.0151 & 0.49397 \tabularnewline
40 & -0.032719 & -0.4764 & 0.317144 \tabularnewline
41 & -0.042548 & -0.6195 & 0.268124 \tabularnewline
42 & -0.019064 & -0.2776 & 0.390803 \tabularnewline
43 & 0.033869 & 0.4931 & 0.311213 \tabularnewline
44 & -0.053189 & -0.7744 & 0.219767 \tabularnewline
45 & 0.007759 & 0.113 & 0.45508 \tabularnewline
46 & -0.014937 & -0.2175 & 0.414018 \tabularnewline
47 & -0.06179 & -0.8997 & 0.184657 \tabularnewline
48 & 0.075187 & 1.0947 & 0.137435 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309473&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]0.78462[/C][C]11.4242[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.232809[/C][C]3.3898[/C][C]0.000417[/C][/ROW]
[ROW][C]3[/C][C]0.502004[/C][C]7.3093[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]-0.044592[/C][C]-0.6493[/C][C]0.258433[/C][/ROW]
[ROW][C]5[/C][C]0.34691[/C][C]5.0511[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.13158[/C][C]1.9158[/C][C]0.028366[/C][/ROW]
[ROW][C]7[/C][C]-0.114821[/C][C]-1.6718[/C][C]0.048017[/C][/ROW]
[ROW][C]8[/C][C]-0.040703[/C][C]-0.5926[/C][C]0.277025[/C][/ROW]
[ROW][C]9[/C][C]-0.094674[/C][C]-1.3785[/C][C]0.084756[/C][/ROW]
[ROW][C]10[/C][C]-0.262168[/C][C]-3.8172[/C][C]8.9e-05[/C][/ROW]
[ROW][C]11[/C][C]0.284883[/C][C]4.148[/C][C]2.4e-05[/C][/ROW]
[ROW][C]12[/C][C]0.438373[/C][C]6.3828[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.210716[/C][C]-3.0681[/C][C]0.001218[/C][/ROW]
[ROW][C]14[/C][C]-0.229134[/C][C]-3.3362[/C][C]0.000501[/C][/ROW]
[ROW][C]15[/C][C]-0.100808[/C][C]-1.4678[/C][C]0.071822[/C][/ROW]
[ROW][C]16[/C][C]0.083436[/C][C]1.2148[/C][C]0.112889[/C][/ROW]
[ROW][C]17[/C][C]-0.058397[/C][C]-0.8503[/C][C]0.198066[/C][/ROW]
[ROW][C]18[/C][C]0.07201[/C][C]1.0485[/C][C]0.147806[/C][/ROW]
[ROW][C]19[/C][C]0.065062[/C][C]0.9473[/C][C]0.172276[/C][/ROW]
[ROW][C]20[/C][C]0.05433[/C][C]0.7911[/C][C]0.214897[/C][/ROW]
[ROW][C]21[/C][C]-0.02869[/C][C]-0.4177[/C][C]0.338282[/C][/ROW]
[ROW][C]22[/C][C]-0.033254[/C][C]-0.4842[/C][C]0.314375[/C][/ROW]
[ROW][C]23[/C][C]0.049759[/C][C]0.7245[/C][C]0.234777[/C][/ROW]
[ROW][C]24[/C][C]0.086166[/C][C]1.2546[/C][C]0.105503[/C][/ROW]
[ROW][C]25[/C][C]-0.02244[/C][C]-0.3267[/C][C]0.372097[/C][/ROW]
[ROW][C]26[/C][C]-0.101092[/C][C]-1.4719[/C][C]0.071262[/C][/ROW]
[ROW][C]27[/C][C]-0.028502[/C][C]-0.415[/C][C]0.339284[/C][/ROW]
[ROW][C]28[/C][C]0.070566[/C][C]1.0275[/C][C]0.152689[/C][/ROW]
[ROW][C]29[/C][C]-0.03314[/C][C]-0.4825[/C][C]0.314968[/C][/ROW]
[ROW][C]30[/C][C]0.017163[/C][C]0.2499[/C][C]0.401456[/C][/ROW]
[ROW][C]31[/C][C]0.100129[/C][C]1.4579[/C][C]0.073175[/C][/ROW]
[ROW][C]32[/C][C]-0.050178[/C][C]-0.7306[/C][C]0.232914[/C][/ROW]
[ROW][C]33[/C][C]-0.028824[/C][C]-0.4197[/C][C]0.337571[/C][/ROW]
[ROW][C]34[/C][C]-0.004784[/C][C]-0.0697[/C][C]0.472265[/C][/ROW]
[ROW][C]35[/C][C]-0.10477[/C][C]-1.5255[/C][C]0.064316[/C][/ROW]
[ROW][C]36[/C][C]0.076494[/C][C]1.1138[/C][C]0.133321[/C][/ROW]
[ROW][C]37[/C][C]0.020502[/C][C]0.2985[/C][C]0.382803[/C][/ROW]
[ROW][C]38[/C][C]-0.09046[/C][C]-1.3171[/C][C]0.094612[/C][/ROW]
[ROW][C]39[/C][C]0.001039[/C][C]0.0151[/C][C]0.49397[/C][/ROW]
[ROW][C]40[/C][C]-0.032719[/C][C]-0.4764[/C][C]0.317144[/C][/ROW]
[ROW][C]41[/C][C]-0.042548[/C][C]-0.6195[/C][C]0.268124[/C][/ROW]
[ROW][C]42[/C][C]-0.019064[/C][C]-0.2776[/C][C]0.390803[/C][/ROW]
[ROW][C]43[/C][C]0.033869[/C][C]0.4931[/C][C]0.311213[/C][/ROW]
[ROW][C]44[/C][C]-0.053189[/C][C]-0.7744[/C][C]0.219767[/C][/ROW]
[ROW][C]45[/C][C]0.007759[/C][C]0.113[/C][C]0.45508[/C][/ROW]
[ROW][C]46[/C][C]-0.014937[/C][C]-0.2175[/C][C]0.414018[/C][/ROW]
[ROW][C]47[/C][C]-0.06179[/C][C]-0.8997[/C][C]0.184657[/C][/ROW]
[ROW][C]48[/C][C]0.075187[/C][C]1.0947[/C][C]0.137435[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309473&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309473&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
10.7846211.42420
20.2328093.38980.000417
30.5020047.30930
4-0.044592-0.64930.258433
50.346915.05110
60.131581.91580.028366
7-0.114821-1.67180.048017
8-0.040703-0.59260.277025
9-0.094674-1.37850.084756
10-0.262168-3.81728.9e-05
110.2848834.1482.4e-05
120.4383736.38280
13-0.210716-3.06810.001218
14-0.229134-3.33620.000501
15-0.100808-1.46780.071822
160.0834361.21480.112889
17-0.058397-0.85030.198066
180.072011.04850.147806
190.0650620.94730.172276
200.054330.79110.214897
21-0.02869-0.41770.338282
22-0.033254-0.48420.314375
230.0497590.72450.234777
240.0861661.25460.105503
25-0.02244-0.32670.372097
26-0.101092-1.47190.071262
27-0.028502-0.4150.339284
280.0705661.02750.152689
29-0.03314-0.48250.314968
300.0171630.24990.401456
310.1001291.45790.073175
32-0.050178-0.73060.232914
33-0.028824-0.41970.337571
34-0.004784-0.06970.472265
35-0.10477-1.52550.064316
360.0764941.11380.133321
370.0205020.29850.382803
38-0.09046-1.31710.094612
390.0010390.01510.49397
40-0.032719-0.47640.317144
41-0.042548-0.61950.268124
42-0.019064-0.27760.390803
430.0338690.49310.311213
44-0.053189-0.77440.219767
450.0077590.1130.45508
46-0.014937-0.21750.414018
47-0.06179-0.89970.184657
480.0751871.09470.137435


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (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')