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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 computationWed, 22 Jan 2020 09:56:51 +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/2020/Jan/22/t1579683589uni6uhdosao2x1m.htm/, Retrieved Sat, 20 Apr 2024 13:31:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319008, Retrieved Sat, 20 Apr 2024 13:31:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsspectoral analysis 1
Estimated Impact87

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] [Examen 22/01] [2020-01-22 08:56:51] [6318fcabf82ddcca686e14c1c17254d8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
62.4
67.4
76.1
67.4
74.5
72.6
60.5
66.1
76.5
76.8
77
71
74.8
73.7
80.5
71.8
76.9
79.9
65.9
69.5
75.1
79.6
75.2
68
72.8
71.5
78.5
76.8
75.3
76.7
69.7
67.8
77.5
82.5
75.3
70.9
76
73.7
79.7
77.8
73.3
78.3
71.9
67
82
83.7
74.8
80
74.3
76.8
89
81.9
76.8
88.9
75.8
75.5
89.1
88
85.9
89.3
82.9
81.2
90.5
86.4
81.8
91.3
73.4
76.6
91
87
89.7
90.7
86.5
86.6
98.8
84.4
91.4
95.7
78.5
81.7
94.3
98.5
95.4
91.7
92.8
90.5
102.2
91.8
95
102
88.9
89.6
97.9
108.6
100.8
95.1
101
100.9
102.5
105.4
98.4
105.3
96.5
88.1
107.9
107
92.5
95.7
85.2
85.5
94.7
86.2
88.8
93.4
83.4
82.9
96.7
96.2
92.8
92.8
90
95.4
108.3
96.3
95
109
92
92.3
107
105.5
105.4
103.9
99.2
102.2
121.5
102.3
110
105.9
91.9
100
111.7
104.9
103.3
101.8
100.8
104.2
116.5
97.9
100.7
107
96.3
96
104.5
107.4
102.4
94.9
98.8
96.8
108.2
103.8
102.3
107.2
102
92.6
105.2
113
105.6
101.6
101.7
102.7
109
105.5
103.3
108.6
98.2
90
112.4
111.9
102.1
102.4
101.7
98.7
114
105.1
98.3
110
96.5
92.2
112
111.4
107.5
103.4
103.5
107.4
117.6
110.2
104.3
115.9
98.9
101.9
113.5
109.5
110
114.2
106.9
109.2
124.2
104.7
111.9
119
102.9
106.3

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319008&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=319008&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319008&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 time1 seconds
R ServerBig Analytics Cloud Computing Center






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.80950111.78650
20.74218210.80630
30.81364711.84690
40.74318510.82090
50.76673611.16380
60.81217111.82540
70.70973810.33390
80.6841839.96190
90.70112210.20850
100.6073018.84240
110.6689159.73950
120.77066211.2210
130.6256129.1090
140.5738198.35490
150.6170678.98460
160.5721548.33070
170.5973038.69690
180.6313369.19240
190.5474947.97160
200.5366367.81350
210.5405417.87040
220.4649566.76990
230.5326097.75490
240.6067778.83480
250.4942197.19590
260.4478126.52020
270.4788256.97180
280.460146.69970
290.4806136.99780
300.5033287.32860
310.4490656.53850
320.4278716.22990
330.4252326.19150
340.3764935.48180
350.4136416.02270
360.4852397.06520
370.4011335.84060
380.32824.77872e-06
390.3661055.33060
400.3514795.11760
410.3484875.0740
420.3767195.48510
430.3275394.7692e-06
440.2858014.16132.3e-05
450.2916714.24681.6e-05
460.2455633.57550.000216
470.2571063.74350.000117
480.3407774.96181e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.809501 & 11.7865 & 0 \tabularnewline
2 & 0.742182 & 10.8063 & 0 \tabularnewline
3 & 0.813647 & 11.8469 & 0 \tabularnewline
4 & 0.743185 & 10.8209 & 0 \tabularnewline
5 & 0.766736 & 11.1638 & 0 \tabularnewline
6 & 0.812171 & 11.8254 & 0 \tabularnewline
7 & 0.709738 & 10.3339 & 0 \tabularnewline
8 & 0.684183 & 9.9619 & 0 \tabularnewline
9 & 0.701122 & 10.2085 & 0 \tabularnewline
10 & 0.607301 & 8.8424 & 0 \tabularnewline
11 & 0.668915 & 9.7395 & 0 \tabularnewline
12 & 0.770662 & 11.221 & 0 \tabularnewline
13 & 0.625612 & 9.109 & 0 \tabularnewline
14 & 0.573819 & 8.3549 & 0 \tabularnewline
15 & 0.617067 & 8.9846 & 0 \tabularnewline
16 & 0.572154 & 8.3307 & 0 \tabularnewline
17 & 0.597303 & 8.6969 & 0 \tabularnewline
18 & 0.631336 & 9.1924 & 0 \tabularnewline
19 & 0.547494 & 7.9716 & 0 \tabularnewline
20 & 0.536636 & 7.8135 & 0 \tabularnewline
21 & 0.540541 & 7.8704 & 0 \tabularnewline
22 & 0.464956 & 6.7699 & 0 \tabularnewline
23 & 0.532609 & 7.7549 & 0 \tabularnewline
24 & 0.606777 & 8.8348 & 0 \tabularnewline
25 & 0.494219 & 7.1959 & 0 \tabularnewline
26 & 0.447812 & 6.5202 & 0 \tabularnewline
27 & 0.478825 & 6.9718 & 0 \tabularnewline
28 & 0.46014 & 6.6997 & 0 \tabularnewline
29 & 0.480613 & 6.9978 & 0 \tabularnewline
30 & 0.503328 & 7.3286 & 0 \tabularnewline
31 & 0.449065 & 6.5385 & 0 \tabularnewline
32 & 0.427871 & 6.2299 & 0 \tabularnewline
33 & 0.425232 & 6.1915 & 0 \tabularnewline
34 & 0.376493 & 5.4818 & 0 \tabularnewline
35 & 0.413641 & 6.0227 & 0 \tabularnewline
36 & 0.485239 & 7.0652 & 0 \tabularnewline
37 & 0.401133 & 5.8406 & 0 \tabularnewline
38 & 0.3282 & 4.7787 & 2e-06 \tabularnewline
39 & 0.366105 & 5.3306 & 0 \tabularnewline
40 & 0.351479 & 5.1176 & 0 \tabularnewline
41 & 0.348487 & 5.074 & 0 \tabularnewline
42 & 0.376719 & 5.4851 & 0 \tabularnewline
43 & 0.327539 & 4.769 & 2e-06 \tabularnewline
44 & 0.285801 & 4.1613 & 2.3e-05 \tabularnewline
45 & 0.291671 & 4.2468 & 1.6e-05 \tabularnewline
46 & 0.245563 & 3.5755 & 0.000216 \tabularnewline
47 & 0.257106 & 3.7435 & 0.000117 \tabularnewline
48 & 0.340777 & 4.9618 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319008&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]0.809501[/C][C]11.7865[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.742182[/C][C]10.8063[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.813647[/C][C]11.8469[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.743185[/C][C]10.8209[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.766736[/C][C]11.1638[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.812171[/C][C]11.8254[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.709738[/C][C]10.3339[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.684183[/C][C]9.9619[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.701122[/C][C]10.2085[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.607301[/C][C]8.8424[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.668915[/C][C]9.7395[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.770662[/C][C]11.221[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.625612[/C][C]9.109[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.573819[/C][C]8.3549[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.617067[/C][C]8.9846[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.572154[/C][C]8.3307[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.597303[/C][C]8.6969[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.631336[/C][C]9.1924[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.547494[/C][C]7.9716[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.536636[/C][C]7.8135[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.540541[/C][C]7.8704[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.464956[/C][C]6.7699[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.532609[/C][C]7.7549[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.606777[/C][C]8.8348[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.494219[/C][C]7.1959[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.447812[/C][C]6.5202[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.478825[/C][C]6.9718[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]0.46014[/C][C]6.6997[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]0.480613[/C][C]6.9978[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]0.503328[/C][C]7.3286[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]0.449065[/C][C]6.5385[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]0.427871[/C][C]6.2299[/C][C]0[/C][/ROW]
[ROW][C]33[/C][C]0.425232[/C][C]6.1915[/C][C]0[/C][/ROW]
[ROW][C]34[/C][C]0.376493[/C][C]5.4818[/C][C]0[/C][/ROW]
[ROW][C]35[/C][C]0.413641[/C][C]6.0227[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0.485239[/C][C]7.0652[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.401133[/C][C]5.8406[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]0.3282[/C][C]4.7787[/C][C]2e-06[/C][/ROW]
[ROW][C]39[/C][C]0.366105[/C][C]5.3306[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]0.351479[/C][C]5.1176[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]0.348487[/C][C]5.074[/C][C]0[/C][/ROW]
[ROW][C]42[/C][C]0.376719[/C][C]5.4851[/C][C]0[/C][/ROW]
[ROW][C]43[/C][C]0.327539[/C][C]4.769[/C][C]2e-06[/C][/ROW]
[ROW][C]44[/C][C]0.285801[/C][C]4.1613[/C][C]2.3e-05[/C][/ROW]
[ROW][C]45[/C][C]0.291671[/C][C]4.2468[/C][C]1.6e-05[/C][/ROW]
[ROW][C]46[/C][C]0.245563[/C][C]3.5755[/C][C]0.000216[/C][/ROW]
[ROW][C]47[/C][C]0.257106[/C][C]3.7435[/C][C]0.000117[/C][/ROW]
[ROW][C]48[/C][C]0.340777[/C][C]4.9618[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319008&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319008&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
10.80950111.78650
20.74218210.80630
30.81364711.84690
40.74318510.82090
50.76673611.16380
60.81217111.82540
70.70973810.33390
80.6841839.96190
90.70112210.20850
100.6073018.84240
110.6689159.73950
120.77066211.2210
130.6256129.1090
140.5738198.35490
150.6170678.98460
160.5721548.33070
170.5973038.69690
180.6313369.19240
190.5474947.97160
200.5366367.81350
210.5405417.87040
220.4649566.76990
230.5326097.75490
240.6067778.83480
250.4942197.19590
260.4478126.52020
270.4788256.97180
280.460146.69970
290.4806136.99780
300.5033287.32860
310.4490656.53850
320.4278716.22990
330.4252326.19150
340.3764935.48180
350.4136416.02270
360.4852397.06520
370.4011335.84060
380.32824.77872e-06
390.3661055.33060
400.3514795.11760
410.3484875.0740
420.3767195.48510
430.3275394.7692e-06
440.2858014.16132.3e-05
450.2916714.24681.6e-05
460.2455633.57550.000216
470.2571063.74350.000117
480.3407774.96181e-06






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.80950111.78650
20.2520693.67020.000153
30.4964027.22770
4-0.055444-0.80730.210204
50.3613795.26180
60.1429282.08110.019315
7-0.123052-1.79170.037307
8-0.080821-1.17680.120304
9-0.085211-1.24070.108045
10-0.268446-3.90866.2e-05
110.2699313.93035.7e-05
120.4183496.09130
13-0.188647-2.74670.003268
14-0.206703-3.00960.001466
15-0.081361-1.18460.118744
160.0903471.31550.094886
17-0.055473-0.80770.210083
180.0546660.79590.213477
190.0456880.66520.253312
200.0374980.5460.292826
21-0.049524-0.72110.235827
22-0.027974-0.40730.342097
230.0594290.86530.193928
240.0894851.30290.097008
25-0.012967-0.18880.425217
26-0.105219-1.5320.063506
27-0.021036-0.30630.379841
280.0790781.15140.125435
29-0.047453-0.69090.245186
300.0007990.01160.495365
310.0961371.39980.081521
32-0.066852-0.97340.165735
33-0.031626-0.46050.322819
34-0.000382-0.00560.497785
35-0.091128-1.32680.092994
360.086031.25260.105864
370.0305890.44540.328251
38-0.1021-1.48660.069303
390.0118590.17270.431539
40-0.034715-0.50550.306881
41-0.042109-0.61310.270229
42-0.030524-0.44440.328591
430.0376120.54760.292257
44-0.063831-0.92940.176869
450.0058560.08530.466067
46-0.011185-0.16290.435393
47-0.052128-0.7590.22435
480.0847041.23330.109412

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.809501 & 11.7865 & 0 \tabularnewline
2 & 0.252069 & 3.6702 & 0.000153 \tabularnewline
3 & 0.496402 & 7.2277 & 0 \tabularnewline
4 & -0.055444 & -0.8073 & 0.210204 \tabularnewline
5 & 0.361379 & 5.2618 & 0 \tabularnewline
6 & 0.142928 & 2.0811 & 0.019315 \tabularnewline
7 & -0.123052 & -1.7917 & 0.037307 \tabularnewline
8 & -0.080821 & -1.1768 & 0.120304 \tabularnewline
9 & -0.085211 & -1.2407 & 0.108045 \tabularnewline
10 & -0.268446 & -3.9086 & 6.2e-05 \tabularnewline
11 & 0.269931 & 3.9303 & 5.7e-05 \tabularnewline
12 & 0.418349 & 6.0913 & 0 \tabularnewline
13 & -0.188647 & -2.7467 & 0.003268 \tabularnewline
14 & -0.206703 & -3.0096 & 0.001466 \tabularnewline
15 & -0.081361 & -1.1846 & 0.118744 \tabularnewline
16 & 0.090347 & 1.3155 & 0.094886 \tabularnewline
17 & -0.055473 & -0.8077 & 0.210083 \tabularnewline
18 & 0.054666 & 0.7959 & 0.213477 \tabularnewline
19 & 0.045688 & 0.6652 & 0.253312 \tabularnewline
20 & 0.037498 & 0.546 & 0.292826 \tabularnewline
21 & -0.049524 & -0.7211 & 0.235827 \tabularnewline
22 & -0.027974 & -0.4073 & 0.342097 \tabularnewline
23 & 0.059429 & 0.8653 & 0.193928 \tabularnewline
24 & 0.089485 & 1.3029 & 0.097008 \tabularnewline
25 & -0.012967 & -0.1888 & 0.425217 \tabularnewline
26 & -0.105219 & -1.532 & 0.063506 \tabularnewline
27 & -0.021036 & -0.3063 & 0.379841 \tabularnewline
28 & 0.079078 & 1.1514 & 0.125435 \tabularnewline
29 & -0.047453 & -0.6909 & 0.245186 \tabularnewline
30 & 0.000799 & 0.0116 & 0.495365 \tabularnewline
31 & 0.096137 & 1.3998 & 0.081521 \tabularnewline
32 & -0.066852 & -0.9734 & 0.165735 \tabularnewline
33 & -0.031626 & -0.4605 & 0.322819 \tabularnewline
34 & -0.000382 & -0.0056 & 0.497785 \tabularnewline
35 & -0.091128 & -1.3268 & 0.092994 \tabularnewline
36 & 0.08603 & 1.2526 & 0.105864 \tabularnewline
37 & 0.030589 & 0.4454 & 0.328251 \tabularnewline
38 & -0.1021 & -1.4866 & 0.069303 \tabularnewline
39 & 0.011859 & 0.1727 & 0.431539 \tabularnewline
40 & -0.034715 & -0.5055 & 0.306881 \tabularnewline
41 & -0.042109 & -0.6131 & 0.270229 \tabularnewline
42 & -0.030524 & -0.4444 & 0.328591 \tabularnewline
43 & 0.037612 & 0.5476 & 0.292257 \tabularnewline
44 & -0.063831 & -0.9294 & 0.176869 \tabularnewline
45 & 0.005856 & 0.0853 & 0.466067 \tabularnewline
46 & -0.011185 & -0.1629 & 0.435393 \tabularnewline
47 & -0.052128 & -0.759 & 0.22435 \tabularnewline
48 & 0.084704 & 1.2333 & 0.109412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319008&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]0.809501[/C][C]11.7865[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.252069[/C][C]3.6702[/C][C]0.000153[/C][/ROW]
[ROW][C]3[/C][C]0.496402[/C][C]7.2277[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]-0.055444[/C][C]-0.8073[/C][C]0.210204[/C][/ROW]
[ROW][C]5[/C][C]0.361379[/C][C]5.2618[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.142928[/C][C]2.0811[/C][C]0.019315[/C][/ROW]
[ROW][C]7[/C][C]-0.123052[/C][C]-1.7917[/C][C]0.037307[/C][/ROW]
[ROW][C]8[/C][C]-0.080821[/C][C]-1.1768[/C][C]0.120304[/C][/ROW]
[ROW][C]9[/C][C]-0.085211[/C][C]-1.2407[/C][C]0.108045[/C][/ROW]
[ROW][C]10[/C][C]-0.268446[/C][C]-3.9086[/C][C]6.2e-05[/C][/ROW]
[ROW][C]11[/C][C]0.269931[/C][C]3.9303[/C][C]5.7e-05[/C][/ROW]
[ROW][C]12[/C][C]0.418349[/C][C]6.0913[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.188647[/C][C]-2.7467[/C][C]0.003268[/C][/ROW]
[ROW][C]14[/C][C]-0.206703[/C][C]-3.0096[/C][C]0.001466[/C][/ROW]
[ROW][C]15[/C][C]-0.081361[/C][C]-1.1846[/C][C]0.118744[/C][/ROW]
[ROW][C]16[/C][C]0.090347[/C][C]1.3155[/C][C]0.094886[/C][/ROW]
[ROW][C]17[/C][C]-0.055473[/C][C]-0.8077[/C][C]0.210083[/C][/ROW]
[ROW][C]18[/C][C]0.054666[/C][C]0.7959[/C][C]0.213477[/C][/ROW]
[ROW][C]19[/C][C]0.045688[/C][C]0.6652[/C][C]0.253312[/C][/ROW]
[ROW][C]20[/C][C]0.037498[/C][C]0.546[/C][C]0.292826[/C][/ROW]
[ROW][C]21[/C][C]-0.049524[/C][C]-0.7211[/C][C]0.235827[/C][/ROW]
[ROW][C]22[/C][C]-0.027974[/C][C]-0.4073[/C][C]0.342097[/C][/ROW]
[ROW][C]23[/C][C]0.059429[/C][C]0.8653[/C][C]0.193928[/C][/ROW]
[ROW][C]24[/C][C]0.089485[/C][C]1.3029[/C][C]0.097008[/C][/ROW]
[ROW][C]25[/C][C]-0.012967[/C][C]-0.1888[/C][C]0.425217[/C][/ROW]
[ROW][C]26[/C][C]-0.105219[/C][C]-1.532[/C][C]0.063506[/C][/ROW]
[ROW][C]27[/C][C]-0.021036[/C][C]-0.3063[/C][C]0.379841[/C][/ROW]
[ROW][C]28[/C][C]0.079078[/C][C]1.1514[/C][C]0.125435[/C][/ROW]
[ROW][C]29[/C][C]-0.047453[/C][C]-0.6909[/C][C]0.245186[/C][/ROW]
[ROW][C]30[/C][C]0.000799[/C][C]0.0116[/C][C]0.495365[/C][/ROW]
[ROW][C]31[/C][C]0.096137[/C][C]1.3998[/C][C]0.081521[/C][/ROW]
[ROW][C]32[/C][C]-0.066852[/C][C]-0.9734[/C][C]0.165735[/C][/ROW]
[ROW][C]33[/C][C]-0.031626[/C][C]-0.4605[/C][C]0.322819[/C][/ROW]
[ROW][C]34[/C][C]-0.000382[/C][C]-0.0056[/C][C]0.497785[/C][/ROW]
[ROW][C]35[/C][C]-0.091128[/C][C]-1.3268[/C][C]0.092994[/C][/ROW]
[ROW][C]36[/C][C]0.08603[/C][C]1.2526[/C][C]0.105864[/C][/ROW]
[ROW][C]37[/C][C]0.030589[/C][C]0.4454[/C][C]0.328251[/C][/ROW]
[ROW][C]38[/C][C]-0.1021[/C][C]-1.4866[/C][C]0.069303[/C][/ROW]
[ROW][C]39[/C][C]0.011859[/C][C]0.1727[/C][C]0.431539[/C][/ROW]
[ROW][C]40[/C][C]-0.034715[/C][C]-0.5055[/C][C]0.306881[/C][/ROW]
[ROW][C]41[/C][C]-0.042109[/C][C]-0.6131[/C][C]0.270229[/C][/ROW]
[ROW][C]42[/C][C]-0.030524[/C][C]-0.4444[/C][C]0.328591[/C][/ROW]
[ROW][C]43[/C][C]0.037612[/C][C]0.5476[/C][C]0.292257[/C][/ROW]
[ROW][C]44[/C][C]-0.063831[/C][C]-0.9294[/C][C]0.176869[/C][/ROW]
[ROW][C]45[/C][C]0.005856[/C][C]0.0853[/C][C]0.466067[/C][/ROW]
[ROW][C]46[/C][C]-0.011185[/C][C]-0.1629[/C][C]0.435393[/C][/ROW]
[ROW][C]47[/C][C]-0.052128[/C][C]-0.759[/C][C]0.22435[/C][/ROW]
[ROW][C]48[/C][C]0.084704[/C][C]1.2333[/C][C]0.109412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319008&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319008&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
10.80950111.78650
20.2520693.67020.000153
30.4964027.22770
4-0.055444-0.80730.210204
50.3613795.26180
60.1429282.08110.019315
7-0.123052-1.79170.037307
8-0.080821-1.17680.120304
9-0.085211-1.24070.108045
10-0.268446-3.90866.2e-05
110.2699313.93035.7e-05
120.4183496.09130
13-0.188647-2.74670.003268
14-0.206703-3.00960.001466
15-0.081361-1.18460.118744
160.0903471.31550.094886
17-0.055473-0.80770.210083
180.0546660.79590.213477
190.0456880.66520.253312
200.0374980.5460.292826
21-0.049524-0.72110.235827
22-0.027974-0.40730.342097
230.0594290.86530.193928
240.0894851.30290.097008
25-0.012967-0.18880.425217
26-0.105219-1.5320.063506
27-0.021036-0.30630.379841
280.0790781.15140.125435
29-0.047453-0.69090.245186
300.0007990.01160.495365
310.0961371.39980.081521
32-0.066852-0.97340.165735
33-0.031626-0.46050.322819
34-0.000382-0.00560.497785
35-0.091128-1.32680.092994
360.086031.25260.105864
370.0305890.44540.328251
38-0.1021-1.48660.069303
390.0118590.17270.431539
40-0.034715-0.50550.306881
41-0.042109-0.61310.270229
42-0.030524-0.44440.328591
430.0376120.54760.292257
44-0.063831-0.92940.176869
450.0058560.08530.466067
46-0.011185-0.16290.435393
47-0.052128-0.7590.22435
480.0847041.23330.109412


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = two.sided ; par2 = 0.97 ; par3 = 14 ;
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')