FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 24 Jan 2018 09:41:18 +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/2018/Jan/24/t1516783285lw4l40n4u5pokmk.htm/, Retrieved Mon, 06 May 2024 09:18:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=311789, Retrieved Mon, 06 May 2024 09:18:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact26

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] [] [2018-01-24 08:41:18] [d6df998cc895915cf377cf60df3b806a] [Current]
Feedback Forum

Post a new message

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 time3 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 time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=311789&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]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=311789&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=311789&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 time3 seconds
R ServerBig Analytics Cloud Computing Center






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.504455-7.11620
2-0.085947-1.21240.113393
30.3553795.01321e-06
4-0.307128-4.33261.2e-05
50.1207891.70390.044976
60.1609982.27120.012104
7-0.236584-3.33740.000505
80.0847821.1960.116559
90.0467330.65920.255249
10-0.094406-1.33180.092232
110.1689842.38380.009037
12-0.205385-2.89730.002093
13-0.004991-0.07040.471968
140.0806661.13790.128257
15-0.032775-0.46240.322167
16-0.073659-1.03910.150013
170.0585470.82590.204922
180.0402850.56830.285239
19-0.169843-2.39590.008752
200.1193961.68430.046848
210.0444980.62770.265452
22-0.262951-3.70940.000135
230.3264854.60564e-06
24-0.148524-2.09520.01871
25-0.159267-2.24670.012877
260.2934844.14012.6e-05
27-0.192694-2.71830.003571
280.0084410.11910.45267
290.1393951.96640.025321
30-0.167623-2.36460.009506
310.0574790.81080.209211
320.1219411.72020.043476
33-0.163102-2.30080.011219
340.1029621.45250.073975
350.002950.04160.483422
36-0.162993-2.29930.011263
370.2257823.18510.00084
38-0.099845-1.40850.080274
39-0.062461-0.88110.189657
400.1118311.57760.058126
410.0191970.27080.39341
42-0.121433-1.7130.044133
430.0900251.270.102792
440.107681.5190.065174
45-0.256403-3.6170.000189
460.2522243.55810.000234
47-0.010761-0.15180.439747
48-0.21118-2.97910.001626

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.504455 & -7.1162 & 0 \tabularnewline
2 & -0.085947 & -1.2124 & 0.113393 \tabularnewline
3 & 0.355379 & 5.0132 & 1e-06 \tabularnewline
4 & -0.307128 & -4.3326 & 1.2e-05 \tabularnewline
5 & 0.120789 & 1.7039 & 0.044976 \tabularnewline
6 & 0.160998 & 2.2712 & 0.012104 \tabularnewline
7 & -0.236584 & -3.3374 & 0.000505 \tabularnewline
8 & 0.084782 & 1.196 & 0.116559 \tabularnewline
9 & 0.046733 & 0.6592 & 0.255249 \tabularnewline
10 & -0.094406 & -1.3318 & 0.092232 \tabularnewline
11 & 0.168984 & 2.3838 & 0.009037 \tabularnewline
12 & -0.205385 & -2.8973 & 0.002093 \tabularnewline
13 & -0.004991 & -0.0704 & 0.471968 \tabularnewline
14 & 0.080666 & 1.1379 & 0.128257 \tabularnewline
15 & -0.032775 & -0.4624 & 0.322167 \tabularnewline
16 & -0.073659 & -1.0391 & 0.150013 \tabularnewline
17 & 0.058547 & 0.8259 & 0.204922 \tabularnewline
18 & 0.040285 & 0.5683 & 0.285239 \tabularnewline
19 & -0.169843 & -2.3959 & 0.008752 \tabularnewline
20 & 0.119396 & 1.6843 & 0.046848 \tabularnewline
21 & 0.044498 & 0.6277 & 0.265452 \tabularnewline
22 & -0.262951 & -3.7094 & 0.000135 \tabularnewline
23 & 0.326485 & 4.6056 & 4e-06 \tabularnewline
24 & -0.148524 & -2.0952 & 0.01871 \tabularnewline
25 & -0.159267 & -2.2467 & 0.012877 \tabularnewline
26 & 0.293484 & 4.1401 & 2.6e-05 \tabularnewline
27 & -0.192694 & -2.7183 & 0.003571 \tabularnewline
28 & 0.008441 & 0.1191 & 0.45267 \tabularnewline
29 & 0.139395 & 1.9664 & 0.025321 \tabularnewline
30 & -0.167623 & -2.3646 & 0.009506 \tabularnewline
31 & 0.057479 & 0.8108 & 0.209211 \tabularnewline
32 & 0.121941 & 1.7202 & 0.043476 \tabularnewline
33 & -0.163102 & -2.3008 & 0.011219 \tabularnewline
34 & 0.102962 & 1.4525 & 0.073975 \tabularnewline
35 & 0.00295 & 0.0416 & 0.483422 \tabularnewline
36 & -0.162993 & -2.2993 & 0.011263 \tabularnewline
37 & 0.225782 & 3.1851 & 0.00084 \tabularnewline
38 & -0.099845 & -1.4085 & 0.080274 \tabularnewline
39 & -0.062461 & -0.8811 & 0.189657 \tabularnewline
40 & 0.111831 & 1.5776 & 0.058126 \tabularnewline
41 & 0.019197 & 0.2708 & 0.39341 \tabularnewline
42 & -0.121433 & -1.713 & 0.044133 \tabularnewline
43 & 0.090025 & 1.27 & 0.102792 \tabularnewline
44 & 0.10768 & 1.519 & 0.065174 \tabularnewline
45 & -0.256403 & -3.617 & 0.000189 \tabularnewline
46 & 0.252224 & 3.5581 & 0.000234 \tabularnewline
47 & -0.010761 & -0.1518 & 0.439747 \tabularnewline
48 & -0.21118 & -2.9791 & 0.001626 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=311789&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]-0.504455[/C][C]-7.1162[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.085947[/C][C]-1.2124[/C][C]0.113393[/C][/ROW]
[ROW][C]3[/C][C]0.355379[/C][C]5.0132[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]-0.307128[/C][C]-4.3326[/C][C]1.2e-05[/C][/ROW]
[ROW][C]5[/C][C]0.120789[/C][C]1.7039[/C][C]0.044976[/C][/ROW]
[ROW][C]6[/C][C]0.160998[/C][C]2.2712[/C][C]0.012104[/C][/ROW]
[ROW][C]7[/C][C]-0.236584[/C][C]-3.3374[/C][C]0.000505[/C][/ROW]
[ROW][C]8[/C][C]0.084782[/C][C]1.196[/C][C]0.116559[/C][/ROW]
[ROW][C]9[/C][C]0.046733[/C][C]0.6592[/C][C]0.255249[/C][/ROW]
[ROW][C]10[/C][C]-0.094406[/C][C]-1.3318[/C][C]0.092232[/C][/ROW]
[ROW][C]11[/C][C]0.168984[/C][C]2.3838[/C][C]0.009037[/C][/ROW]
[ROW][C]12[/C][C]-0.205385[/C][C]-2.8973[/C][C]0.002093[/C][/ROW]
[ROW][C]13[/C][C]-0.004991[/C][C]-0.0704[/C][C]0.471968[/C][/ROW]
[ROW][C]14[/C][C]0.080666[/C][C]1.1379[/C][C]0.128257[/C][/ROW]
[ROW][C]15[/C][C]-0.032775[/C][C]-0.4624[/C][C]0.322167[/C][/ROW]
[ROW][C]16[/C][C]-0.073659[/C][C]-1.0391[/C][C]0.150013[/C][/ROW]
[ROW][C]17[/C][C]0.058547[/C][C]0.8259[/C][C]0.204922[/C][/ROW]
[ROW][C]18[/C][C]0.040285[/C][C]0.5683[/C][C]0.285239[/C][/ROW]
[ROW][C]19[/C][C]-0.169843[/C][C]-2.3959[/C][C]0.008752[/C][/ROW]
[ROW][C]20[/C][C]0.119396[/C][C]1.6843[/C][C]0.046848[/C][/ROW]
[ROW][C]21[/C][C]0.044498[/C][C]0.6277[/C][C]0.265452[/C][/ROW]
[ROW][C]22[/C][C]-0.262951[/C][C]-3.7094[/C][C]0.000135[/C][/ROW]
[ROW][C]23[/C][C]0.326485[/C][C]4.6056[/C][C]4e-06[/C][/ROW]
[ROW][C]24[/C][C]-0.148524[/C][C]-2.0952[/C][C]0.01871[/C][/ROW]
[ROW][C]25[/C][C]-0.159267[/C][C]-2.2467[/C][C]0.012877[/C][/ROW]
[ROW][C]26[/C][C]0.293484[/C][C]4.1401[/C][C]2.6e-05[/C][/ROW]
[ROW][C]27[/C][C]-0.192694[/C][C]-2.7183[/C][C]0.003571[/C][/ROW]
[ROW][C]28[/C][C]0.008441[/C][C]0.1191[/C][C]0.45267[/C][/ROW]
[ROW][C]29[/C][C]0.139395[/C][C]1.9664[/C][C]0.025321[/C][/ROW]
[ROW][C]30[/C][C]-0.167623[/C][C]-2.3646[/C][C]0.009506[/C][/ROW]
[ROW][C]31[/C][C]0.057479[/C][C]0.8108[/C][C]0.209211[/C][/ROW]
[ROW][C]32[/C][C]0.121941[/C][C]1.7202[/C][C]0.043476[/C][/ROW]
[ROW][C]33[/C][C]-0.163102[/C][C]-2.3008[/C][C]0.011219[/C][/ROW]
[ROW][C]34[/C][C]0.102962[/C][C]1.4525[/C][C]0.073975[/C][/ROW]
[ROW][C]35[/C][C]0.00295[/C][C]0.0416[/C][C]0.483422[/C][/ROW]
[ROW][C]36[/C][C]-0.162993[/C][C]-2.2993[/C][C]0.011263[/C][/ROW]
[ROW][C]37[/C][C]0.225782[/C][C]3.1851[/C][C]0.00084[/C][/ROW]
[ROW][C]38[/C][C]-0.099845[/C][C]-1.4085[/C][C]0.080274[/C][/ROW]
[ROW][C]39[/C][C]-0.062461[/C][C]-0.8811[/C][C]0.189657[/C][/ROW]
[ROW][C]40[/C][C]0.111831[/C][C]1.5776[/C][C]0.058126[/C][/ROW]
[ROW][C]41[/C][C]0.019197[/C][C]0.2708[/C][C]0.39341[/C][/ROW]
[ROW][C]42[/C][C]-0.121433[/C][C]-1.713[/C][C]0.044133[/C][/ROW]
[ROW][C]43[/C][C]0.090025[/C][C]1.27[/C][C]0.102792[/C][/ROW]
[ROW][C]44[/C][C]0.10768[/C][C]1.519[/C][C]0.065174[/C][/ROW]
[ROW][C]45[/C][C]-0.256403[/C][C]-3.617[/C][C]0.000189[/C][/ROW]
[ROW][C]46[/C][C]0.252224[/C][C]3.5581[/C][C]0.000234[/C][/ROW]
[ROW][C]47[/C][C]-0.010761[/C][C]-0.1518[/C][C]0.439747[/C][/ROW]
[ROW][C]48[/C][C]-0.21118[/C][C]-2.9791[/C][C]0.001626[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=311789&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=311789&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
1-0.504455-7.11620
2-0.085947-1.21240.113393
30.3553795.01321e-06
4-0.307128-4.33261.2e-05
50.1207891.70390.044976
60.1609982.27120.012104
7-0.236584-3.33740.000505
80.0847821.1960.116559
90.0467330.65920.255249
10-0.094406-1.33180.092232
110.1689842.38380.009037
12-0.205385-2.89730.002093
13-0.004991-0.07040.471968
140.0806661.13790.128257
15-0.032775-0.46240.322167
16-0.073659-1.03910.150013
170.0585470.82590.204922
180.0402850.56830.285239
19-0.169843-2.39590.008752
200.1193961.68430.046848
210.0444980.62770.265452
22-0.262951-3.70940.000135
230.3264854.60564e-06
24-0.148524-2.09520.01871
25-0.159267-2.24670.012877
260.2934844.14012.6e-05
27-0.192694-2.71830.003571
280.0084410.11910.45267
290.1393951.96640.025321
30-0.167623-2.36460.009506
310.0574790.81080.209211
320.1219411.72020.043476
33-0.163102-2.30080.011219
340.1029621.45250.073975
350.002950.04160.483422
36-0.162993-2.29930.011263
370.2257823.18510.00084
38-0.099845-1.40850.080274
39-0.062461-0.88110.189657
400.1118311.57760.058126
410.0191970.27080.39341
42-0.121433-1.7130.044133
430.0900251.270.102792
440.107681.5190.065174
45-0.256403-3.6170.000189
460.2522243.55810.000234
47-0.010761-0.15180.439747
48-0.21118-2.97910.001626






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.504455-7.11620
2-0.45662-6.44140
30.1048691.47940.070313
4-0.073224-1.0330.15144
50.0425440.60020.274543
60.1880222.65240.004319
70.0675870.95340.170765
8-0.049025-0.69160.245005
9-0.072585-1.02390.153556
10-0.035865-0.50590.306728
110.1507312.12630.017354
12-0.12235-1.7260.042953
13-0.184076-2.59670.005057
14-0.209477-2.9550.001752
150.0100080.14120.443934
16-0.13131-1.85240.032728
17-0.081979-1.15650.12444
180.1673852.36130.00959
19-0.027634-0.38980.348539
20-0.116047-1.6370.051601
210.004930.06950.472315
22-0.205149-2.8940.002114
230.1642282.31670.010768
24-0.017491-0.24670.402684
25-0.151989-2.14410.01662
26-0.083178-1.17340.121025
27-0.035749-0.50430.307306
28-0.032921-0.46440.321432
29-0.072162-1.0180.154965
300.0643670.9080.182487
31-8.8e-05-0.00120.499506
32-0.007053-0.09950.46042
33-0.008236-0.11620.453812
34-0.0881-1.24280.107702
350.0606670.85580.196566
36-0.194256-2.74030.003348
37-0.058363-0.82330.205657
38-0.083191-1.17360.120987
39-0.022872-0.32270.373649
40-0.031655-0.44650.327845
410.10621.49810.067842
420.0802241.13170.129562
43-0.046002-0.64890.258562
440.1580012.22890.01347
45-0.01435-0.20240.419892
460.063780.89970.184677
470.156542.20830.014184
48-0.105069-1.48220.069937

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.504455 & -7.1162 & 0 \tabularnewline
2 & -0.45662 & -6.4414 & 0 \tabularnewline
3 & 0.104869 & 1.4794 & 0.070313 \tabularnewline
4 & -0.073224 & -1.033 & 0.15144 \tabularnewline
5 & 0.042544 & 0.6002 & 0.274543 \tabularnewline
6 & 0.188022 & 2.6524 & 0.004319 \tabularnewline
7 & 0.067587 & 0.9534 & 0.170765 \tabularnewline
8 & -0.049025 & -0.6916 & 0.245005 \tabularnewline
9 & -0.072585 & -1.0239 & 0.153556 \tabularnewline
10 & -0.035865 & -0.5059 & 0.306728 \tabularnewline
11 & 0.150731 & 2.1263 & 0.017354 \tabularnewline
12 & -0.12235 & -1.726 & 0.042953 \tabularnewline
13 & -0.184076 & -2.5967 & 0.005057 \tabularnewline
14 & -0.209477 & -2.955 & 0.001752 \tabularnewline
15 & 0.010008 & 0.1412 & 0.443934 \tabularnewline
16 & -0.13131 & -1.8524 & 0.032728 \tabularnewline
17 & -0.081979 & -1.1565 & 0.12444 \tabularnewline
18 & 0.167385 & 2.3613 & 0.00959 \tabularnewline
19 & -0.027634 & -0.3898 & 0.348539 \tabularnewline
20 & -0.116047 & -1.637 & 0.051601 \tabularnewline
21 & 0.00493 & 0.0695 & 0.472315 \tabularnewline
22 & -0.205149 & -2.894 & 0.002114 \tabularnewline
23 & 0.164228 & 2.3167 & 0.010768 \tabularnewline
24 & -0.017491 & -0.2467 & 0.402684 \tabularnewline
25 & -0.151989 & -2.1441 & 0.01662 \tabularnewline
26 & -0.083178 & -1.1734 & 0.121025 \tabularnewline
27 & -0.035749 & -0.5043 & 0.307306 \tabularnewline
28 & -0.032921 & -0.4644 & 0.321432 \tabularnewline
29 & -0.072162 & -1.018 & 0.154965 \tabularnewline
30 & 0.064367 & 0.908 & 0.182487 \tabularnewline
31 & -8.8e-05 & -0.0012 & 0.499506 \tabularnewline
32 & -0.007053 & -0.0995 & 0.46042 \tabularnewline
33 & -0.008236 & -0.1162 & 0.453812 \tabularnewline
34 & -0.0881 & -1.2428 & 0.107702 \tabularnewline
35 & 0.060667 & 0.8558 & 0.196566 \tabularnewline
36 & -0.194256 & -2.7403 & 0.003348 \tabularnewline
37 & -0.058363 & -0.8233 & 0.205657 \tabularnewline
38 & -0.083191 & -1.1736 & 0.120987 \tabularnewline
39 & -0.022872 & -0.3227 & 0.373649 \tabularnewline
40 & -0.031655 & -0.4465 & 0.327845 \tabularnewline
41 & 0.1062 & 1.4981 & 0.067842 \tabularnewline
42 & 0.080224 & 1.1317 & 0.129562 \tabularnewline
43 & -0.046002 & -0.6489 & 0.258562 \tabularnewline
44 & 0.158001 & 2.2289 & 0.01347 \tabularnewline
45 & -0.01435 & -0.2024 & 0.419892 \tabularnewline
46 & 0.06378 & 0.8997 & 0.184677 \tabularnewline
47 & 0.15654 & 2.2083 & 0.014184 \tabularnewline
48 & -0.105069 & -1.4822 & 0.069937 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=311789&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]-0.504455[/C][C]-7.1162[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.45662[/C][C]-6.4414[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.104869[/C][C]1.4794[/C][C]0.070313[/C][/ROW]
[ROW][C]4[/C][C]-0.073224[/C][C]-1.033[/C][C]0.15144[/C][/ROW]
[ROW][C]5[/C][C]0.042544[/C][C]0.6002[/C][C]0.274543[/C][/ROW]
[ROW][C]6[/C][C]0.188022[/C][C]2.6524[/C][C]0.004319[/C][/ROW]
[ROW][C]7[/C][C]0.067587[/C][C]0.9534[/C][C]0.170765[/C][/ROW]
[ROW][C]8[/C][C]-0.049025[/C][C]-0.6916[/C][C]0.245005[/C][/ROW]
[ROW][C]9[/C][C]-0.072585[/C][C]-1.0239[/C][C]0.153556[/C][/ROW]
[ROW][C]10[/C][C]-0.035865[/C][C]-0.5059[/C][C]0.306728[/C][/ROW]
[ROW][C]11[/C][C]0.150731[/C][C]2.1263[/C][C]0.017354[/C][/ROW]
[ROW][C]12[/C][C]-0.12235[/C][C]-1.726[/C][C]0.042953[/C][/ROW]
[ROW][C]13[/C][C]-0.184076[/C][C]-2.5967[/C][C]0.005057[/C][/ROW]
[ROW][C]14[/C][C]-0.209477[/C][C]-2.955[/C][C]0.001752[/C][/ROW]
[ROW][C]15[/C][C]0.010008[/C][C]0.1412[/C][C]0.443934[/C][/ROW]
[ROW][C]16[/C][C]-0.13131[/C][C]-1.8524[/C][C]0.032728[/C][/ROW]
[ROW][C]17[/C][C]-0.081979[/C][C]-1.1565[/C][C]0.12444[/C][/ROW]
[ROW][C]18[/C][C]0.167385[/C][C]2.3613[/C][C]0.00959[/C][/ROW]
[ROW][C]19[/C][C]-0.027634[/C][C]-0.3898[/C][C]0.348539[/C][/ROW]
[ROW][C]20[/C][C]-0.116047[/C][C]-1.637[/C][C]0.051601[/C][/ROW]
[ROW][C]21[/C][C]0.00493[/C][C]0.0695[/C][C]0.472315[/C][/ROW]
[ROW][C]22[/C][C]-0.205149[/C][C]-2.894[/C][C]0.002114[/C][/ROW]
[ROW][C]23[/C][C]0.164228[/C][C]2.3167[/C][C]0.010768[/C][/ROW]
[ROW][C]24[/C][C]-0.017491[/C][C]-0.2467[/C][C]0.402684[/C][/ROW]
[ROW][C]25[/C][C]-0.151989[/C][C]-2.1441[/C][C]0.01662[/C][/ROW]
[ROW][C]26[/C][C]-0.083178[/C][C]-1.1734[/C][C]0.121025[/C][/ROW]
[ROW][C]27[/C][C]-0.035749[/C][C]-0.5043[/C][C]0.307306[/C][/ROW]
[ROW][C]28[/C][C]-0.032921[/C][C]-0.4644[/C][C]0.321432[/C][/ROW]
[ROW][C]29[/C][C]-0.072162[/C][C]-1.018[/C][C]0.154965[/C][/ROW]
[ROW][C]30[/C][C]0.064367[/C][C]0.908[/C][C]0.182487[/C][/ROW]
[ROW][C]31[/C][C]-8.8e-05[/C][C]-0.0012[/C][C]0.499506[/C][/ROW]
[ROW][C]32[/C][C]-0.007053[/C][C]-0.0995[/C][C]0.46042[/C][/ROW]
[ROW][C]33[/C][C]-0.008236[/C][C]-0.1162[/C][C]0.453812[/C][/ROW]
[ROW][C]34[/C][C]-0.0881[/C][C]-1.2428[/C][C]0.107702[/C][/ROW]
[ROW][C]35[/C][C]0.060667[/C][C]0.8558[/C][C]0.196566[/C][/ROW]
[ROW][C]36[/C][C]-0.194256[/C][C]-2.7403[/C][C]0.003348[/C][/ROW]
[ROW][C]37[/C][C]-0.058363[/C][C]-0.8233[/C][C]0.205657[/C][/ROW]
[ROW][C]38[/C][C]-0.083191[/C][C]-1.1736[/C][C]0.120987[/C][/ROW]
[ROW][C]39[/C][C]-0.022872[/C][C]-0.3227[/C][C]0.373649[/C][/ROW]
[ROW][C]40[/C][C]-0.031655[/C][C]-0.4465[/C][C]0.327845[/C][/ROW]
[ROW][C]41[/C][C]0.1062[/C][C]1.4981[/C][C]0.067842[/C][/ROW]
[ROW][C]42[/C][C]0.080224[/C][C]1.1317[/C][C]0.129562[/C][/ROW]
[ROW][C]43[/C][C]-0.046002[/C][C]-0.6489[/C][C]0.258562[/C][/ROW]
[ROW][C]44[/C][C]0.158001[/C][C]2.2289[/C][C]0.01347[/C][/ROW]
[ROW][C]45[/C][C]-0.01435[/C][C]-0.2024[/C][C]0.419892[/C][/ROW]
[ROW][C]46[/C][C]0.06378[/C][C]0.8997[/C][C]0.184677[/C][/ROW]
[ROW][C]47[/C][C]0.15654[/C][C]2.2083[/C][C]0.014184[/C][/ROW]
[ROW][C]48[/C][C]-0.105069[/C][C]-1.4822[/C][C]0.069937[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=311789&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=311789&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
1-0.504455-7.11620
2-0.45662-6.44140
30.1048691.47940.070313
4-0.073224-1.0330.15144
50.0425440.60020.274543
60.1880222.65240.004319
70.0675870.95340.170765
8-0.049025-0.69160.245005
9-0.072585-1.02390.153556
10-0.035865-0.50590.306728
110.1507312.12630.017354
12-0.12235-1.7260.042953
13-0.184076-2.59670.005057
14-0.209477-2.9550.001752
150.0100080.14120.443934
16-0.13131-1.85240.032728
17-0.081979-1.15650.12444
180.1673852.36130.00959
19-0.027634-0.38980.348539
20-0.116047-1.6370.051601
210.004930.06950.472315
22-0.205149-2.8940.002114
230.1642282.31670.010768
24-0.017491-0.24670.402684
25-0.151989-2.14410.01662
26-0.083178-1.17340.121025
27-0.035749-0.50430.307306
28-0.032921-0.46440.321432
29-0.072162-1.0180.154965
300.0643670.9080.182487
31-8.8e-05-0.00120.499506
32-0.007053-0.09950.46042
33-0.008236-0.11620.453812
34-0.0881-1.24280.107702
350.0606670.85580.196566
36-0.194256-2.74030.003348
37-0.058363-0.82330.205657
38-0.083191-1.17360.120987
39-0.022872-0.32270.373649
40-0.031655-0.44650.327845
410.10621.49810.067842
420.0802241.13170.129562
43-0.046002-0.64890.258562
440.1580012.22890.01347
45-0.01435-0.20240.419892
460.063780.89970.184677
470.156542.20830.014184
48-0.105069-1.48220.069937


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.99 ; 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')