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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 computationFri, 23 Dec 2016 08:43:55 +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/2016/Dec/23/t14824790691lpqk2z9xz3tvak.htm/, Retrieved Wed, 08 May 2024 00:44:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302755, Retrieved Wed, 08 May 2024 00:44:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

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...] [2016-12-23 07:43:55] [55eb8f21ed24cda91766c505eb72bb6f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3949.9
4010.65
4381.8
4238.25
4178.1
4702.25
3944.1
4208.5
4743.45
4948.25
4735.45
4843.15
4757.75
5227.15
5739.65
4981.45
5020.05
5149.15
4513.35
4762.55
4990.45
4963.35
5010
4983.3
4924.7
5175.25
5470.3
4969.4
5020.5
5519.2
4510.75
4934.45
5430.65
5254.7
4897.8
5305.7
5055.7
5409
5683
5125.55
4965.2
5373.3
4556.1
4714.25
5513.85
5258.45
5111.4
5422.25
4753.3
5455.5
5909.15
5524.4
5477.8
5907.75
5072.55
5171
5871.4
5812.45
5692.2
5838.1
5438.2
6041.05
6335.6
5891.8
5909.65
6449.75
5312.25
5828.1
6466.15
6328.35
6131.8
6734.2
6037.25
6412.4
6785.55
6386
6045.25
6597.25
5355.9
5773.35
6539.6
6149.2
6373.45
6504.7
5451.25
6119.9
6954.95
6139.7
6383.25
6643.7
5547.75
5974
6583.6
6571.55
5736.5
6027.2
5302.65
5825.85
5910.6
5733.65
5914.3
6128.25
5680.5
5926.3
6270.5
6263
6064.55
5706.6
5365
5884.2
6504.4
6174.3
6123.65
6698.95
5256.55
5838.2

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=302755&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=302755&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302755&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
1-0.38429-4.12113.6e-05
2-0.312815-3.35460.000539
30.4224784.53067e-06
4-0.237419-2.5460.006109
5-0.284381-3.04970.001422
60.6180736.62810
7-0.269525-2.89030.002301
8-0.212853-2.28260.012146
90.4005144.2951.8e-05
10-0.32443-3.47910.000356
11-0.243641-2.61280.005091
120.7185567.70570
13-0.288268-3.09130.00125
14-0.272058-2.91750.002122
150.3807234.08284.1e-05
16-0.235904-2.52980.006383
17-0.251915-2.70150.003974
180.6088256.52890
19-0.315866-3.38730.000483
20-0.123574-1.32520.093868
210.3438893.68780.000173
22-0.294154-3.15450.001026
23-0.253652-2.72010.00377
240.6940377.44270
25-0.279965-3.00230.001644
26-0.262798-2.81820.002844
270.3557713.81520.00011
28-0.204437-2.19230.015185
29-0.240887-2.58320.005521
300.5332685.71870
31-0.257312-2.75940.00337
32-0.138831-1.48880.069639
330.3312273.5520.000278
34-0.306658-3.28850.000668
35-0.191605-2.05470.021085
360.5907046.33460
37-0.265051-2.84240.00265
38-0.166756-1.78830.038183
390.2936633.14920.001043
40-0.196255-2.10460.018752
41-0.173536-1.8610.032652
420.4391664.70953e-06
43-0.240391-2.57790.005602
44-0.067594-0.72490.235004
450.2400072.57380.005665
46-0.236104-2.53190.006346
47-0.168907-1.81130.03635
480.4748015.09171e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.38429 & -4.1211 & 3.6e-05 \tabularnewline
2 & -0.312815 & -3.3546 & 0.000539 \tabularnewline
3 & 0.422478 & 4.5306 & 7e-06 \tabularnewline
4 & -0.237419 & -2.546 & 0.006109 \tabularnewline
5 & -0.284381 & -3.0497 & 0.001422 \tabularnewline
6 & 0.618073 & 6.6281 & 0 \tabularnewline
7 & -0.269525 & -2.8903 & 0.002301 \tabularnewline
8 & -0.212853 & -2.2826 & 0.012146 \tabularnewline
9 & 0.400514 & 4.295 & 1.8e-05 \tabularnewline
10 & -0.32443 & -3.4791 & 0.000356 \tabularnewline
11 & -0.243641 & -2.6128 & 0.005091 \tabularnewline
12 & 0.718556 & 7.7057 & 0 \tabularnewline
13 & -0.288268 & -3.0913 & 0.00125 \tabularnewline
14 & -0.272058 & -2.9175 & 0.002122 \tabularnewline
15 & 0.380723 & 4.0828 & 4.1e-05 \tabularnewline
16 & -0.235904 & -2.5298 & 0.006383 \tabularnewline
17 & -0.251915 & -2.7015 & 0.003974 \tabularnewline
18 & 0.608825 & 6.5289 & 0 \tabularnewline
19 & -0.315866 & -3.3873 & 0.000483 \tabularnewline
20 & -0.123574 & -1.3252 & 0.093868 \tabularnewline
21 & 0.343889 & 3.6878 & 0.000173 \tabularnewline
22 & -0.294154 & -3.1545 & 0.001026 \tabularnewline
23 & -0.253652 & -2.7201 & 0.00377 \tabularnewline
24 & 0.694037 & 7.4427 & 0 \tabularnewline
25 & -0.279965 & -3.0023 & 0.001644 \tabularnewline
26 & -0.262798 & -2.8182 & 0.002844 \tabularnewline
27 & 0.355771 & 3.8152 & 0.00011 \tabularnewline
28 & -0.204437 & -2.1923 & 0.015185 \tabularnewline
29 & -0.240887 & -2.5832 & 0.005521 \tabularnewline
30 & 0.533268 & 5.7187 & 0 \tabularnewline
31 & -0.257312 & -2.7594 & 0.00337 \tabularnewline
32 & -0.138831 & -1.4888 & 0.069639 \tabularnewline
33 & 0.331227 & 3.552 & 0.000278 \tabularnewline
34 & -0.306658 & -3.2885 & 0.000668 \tabularnewline
35 & -0.191605 & -2.0547 & 0.021085 \tabularnewline
36 & 0.590704 & 6.3346 & 0 \tabularnewline
37 & -0.265051 & -2.8424 & 0.00265 \tabularnewline
38 & -0.166756 & -1.7883 & 0.038183 \tabularnewline
39 & 0.293663 & 3.1492 & 0.001043 \tabularnewline
40 & -0.196255 & -2.1046 & 0.018752 \tabularnewline
41 & -0.173536 & -1.861 & 0.032652 \tabularnewline
42 & 0.439166 & 4.7095 & 3e-06 \tabularnewline
43 & -0.240391 & -2.5779 & 0.005602 \tabularnewline
44 & -0.067594 & -0.7249 & 0.235004 \tabularnewline
45 & 0.240007 & 2.5738 & 0.005665 \tabularnewline
46 & -0.236104 & -2.5319 & 0.006346 \tabularnewline
47 & -0.168907 & -1.8113 & 0.03635 \tabularnewline
48 & 0.474801 & 5.0917 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302755&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]-0.38429[/C][C]-4.1211[/C][C]3.6e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.312815[/C][C]-3.3546[/C][C]0.000539[/C][/ROW]
[ROW][C]3[/C][C]0.422478[/C][C]4.5306[/C][C]7e-06[/C][/ROW]
[ROW][C]4[/C][C]-0.237419[/C][C]-2.546[/C][C]0.006109[/C][/ROW]
[ROW][C]5[/C][C]-0.284381[/C][C]-3.0497[/C][C]0.001422[/C][/ROW]
[ROW][C]6[/C][C]0.618073[/C][C]6.6281[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.269525[/C][C]-2.8903[/C][C]0.002301[/C][/ROW]
[ROW][C]8[/C][C]-0.212853[/C][C]-2.2826[/C][C]0.012146[/C][/ROW]
[ROW][C]9[/C][C]0.400514[/C][C]4.295[/C][C]1.8e-05[/C][/ROW]
[ROW][C]10[/C][C]-0.32443[/C][C]-3.4791[/C][C]0.000356[/C][/ROW]
[ROW][C]11[/C][C]-0.243641[/C][C]-2.6128[/C][C]0.005091[/C][/ROW]
[ROW][C]12[/C][C]0.718556[/C][C]7.7057[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.288268[/C][C]-3.0913[/C][C]0.00125[/C][/ROW]
[ROW][C]14[/C][C]-0.272058[/C][C]-2.9175[/C][C]0.002122[/C][/ROW]
[ROW][C]15[/C][C]0.380723[/C][C]4.0828[/C][C]4.1e-05[/C][/ROW]
[ROW][C]16[/C][C]-0.235904[/C][C]-2.5298[/C][C]0.006383[/C][/ROW]
[ROW][C]17[/C][C]-0.251915[/C][C]-2.7015[/C][C]0.003974[/C][/ROW]
[ROW][C]18[/C][C]0.608825[/C][C]6.5289[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]-0.315866[/C][C]-3.3873[/C][C]0.000483[/C][/ROW]
[ROW][C]20[/C][C]-0.123574[/C][C]-1.3252[/C][C]0.093868[/C][/ROW]
[ROW][C]21[/C][C]0.343889[/C][C]3.6878[/C][C]0.000173[/C][/ROW]
[ROW][C]22[/C][C]-0.294154[/C][C]-3.1545[/C][C]0.001026[/C][/ROW]
[ROW][C]23[/C][C]-0.253652[/C][C]-2.7201[/C][C]0.00377[/C][/ROW]
[ROW][C]24[/C][C]0.694037[/C][C]7.4427[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]-0.279965[/C][C]-3.0023[/C][C]0.001644[/C][/ROW]
[ROW][C]26[/C][C]-0.262798[/C][C]-2.8182[/C][C]0.002844[/C][/ROW]
[ROW][C]27[/C][C]0.355771[/C][C]3.8152[/C][C]0.00011[/C][/ROW]
[ROW][C]28[/C][C]-0.204437[/C][C]-2.1923[/C][C]0.015185[/C][/ROW]
[ROW][C]29[/C][C]-0.240887[/C][C]-2.5832[/C][C]0.005521[/C][/ROW]
[ROW][C]30[/C][C]0.533268[/C][C]5.7187[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]-0.257312[/C][C]-2.7594[/C][C]0.00337[/C][/ROW]
[ROW][C]32[/C][C]-0.138831[/C][C]-1.4888[/C][C]0.069639[/C][/ROW]
[ROW][C]33[/C][C]0.331227[/C][C]3.552[/C][C]0.000278[/C][/ROW]
[ROW][C]34[/C][C]-0.306658[/C][C]-3.2885[/C][C]0.000668[/C][/ROW]
[ROW][C]35[/C][C]-0.191605[/C][C]-2.0547[/C][C]0.021085[/C][/ROW]
[ROW][C]36[/C][C]0.590704[/C][C]6.3346[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]-0.265051[/C][C]-2.8424[/C][C]0.00265[/C][/ROW]
[ROW][C]38[/C][C]-0.166756[/C][C]-1.7883[/C][C]0.038183[/C][/ROW]
[ROW][C]39[/C][C]0.293663[/C][C]3.1492[/C][C]0.001043[/C][/ROW]
[ROW][C]40[/C][C]-0.196255[/C][C]-2.1046[/C][C]0.018752[/C][/ROW]
[ROW][C]41[/C][C]-0.173536[/C][C]-1.861[/C][C]0.032652[/C][/ROW]
[ROW][C]42[/C][C]0.439166[/C][C]4.7095[/C][C]3e-06[/C][/ROW]
[ROW][C]43[/C][C]-0.240391[/C][C]-2.5779[/C][C]0.005602[/C][/ROW]
[ROW][C]44[/C][C]-0.067594[/C][C]-0.7249[/C][C]0.235004[/C][/ROW]
[ROW][C]45[/C][C]0.240007[/C][C]2.5738[/C][C]0.005665[/C][/ROW]
[ROW][C]46[/C][C]-0.236104[/C][C]-2.5319[/C][C]0.006346[/C][/ROW]
[ROW][C]47[/C][C]-0.168907[/C][C]-1.8113[/C][C]0.03635[/C][/ROW]
[ROW][C]48[/C][C]0.474801[/C][C]5.0917[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302755&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302755&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
1-0.38429-4.12113.6e-05
2-0.312815-3.35460.000539
30.4224784.53067e-06
4-0.237419-2.5460.006109
5-0.284381-3.04970.001422
60.6180736.62810
7-0.269525-2.89030.002301
8-0.212853-2.28260.012146
90.4005144.2951.8e-05
10-0.32443-3.47910.000356
11-0.243641-2.61280.005091
120.7185567.70570
13-0.288268-3.09130.00125
14-0.272058-2.91750.002122
150.3807234.08284.1e-05
16-0.235904-2.52980.006383
17-0.251915-2.70150.003974
180.6088256.52890
19-0.315866-3.38730.000483
20-0.123574-1.32520.093868
210.3438893.68780.000173
22-0.294154-3.15450.001026
23-0.253652-2.72010.00377
240.6940377.44270
25-0.279965-3.00230.001644
26-0.262798-2.81820.002844
270.3557713.81520.00011
28-0.204437-2.19230.015185
29-0.240887-2.58320.005521
300.5332685.71870
31-0.257312-2.75940.00337
32-0.138831-1.48880.069639
330.3312273.5520.000278
34-0.306658-3.28850.000668
35-0.191605-2.05470.021085
360.5907046.33460
37-0.265051-2.84240.00265
38-0.166756-1.78830.038183
390.2936633.14920.001043
40-0.196255-2.10460.018752
41-0.173536-1.8610.032652
420.4391664.70953e-06
43-0.240391-2.57790.005602
44-0.067594-0.72490.235004
450.2400072.57380.005665
46-0.236104-2.53190.006346
47-0.168907-1.81130.03635
480.4748015.09171e-06






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.38429-4.12113.6e-05
2-0.540282-5.79390
30.0491990.52760.299397
4-0.231818-2.4860.007178
5-0.464395-4.98011e-06
60.2195052.35390.010136
7-0.054332-0.58260.280637
80.0214340.22990.409306
90.1025011.09920.136989
10-0.22764-2.44120.008082
11-0.340251-3.64880.000199
120.3072693.29510.000654
130.1963572.10570.018703
140.0695060.74540.228784
15-0.05876-0.63010.264928
16-0.026994-0.28950.386367
17-0.090858-0.97430.165966
180.1454871.56020.060733
19-0.119791-1.28460.100754
200.0940591.00870.157624
210.0033350.03580.485768
220.0610790.6550.256887
23-0.187334-2.00890.023443
240.1485331.59280.056971
250.1325381.42130.078966
260.0022340.0240.490465
27-0.106038-1.13710.128924
280.0409180.43880.330815
29-0.010675-0.11450.454531
30-0.033164-0.35560.361378
31-0.08846-0.94860.172399
32-0.02895-0.31050.378388
33-0.028197-0.30240.381455
34-0.110772-1.18790.11866
35-0.061934-0.66420.253957
36-0.092596-0.9930.161403
37-0.051852-0.55610.289627
380.0721960.77420.220196
390.0030710.03290.486893
400.0179320.19230.423924
410.1432071.53570.063677
42-0.066696-0.71520.237957
430.0145580.15610.438109
440.0389350.41750.338534
45-0.064149-0.68790.246445
460.05810.62310.26724
470.0146020.15660.43792
48-0.095862-1.0280.153053

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.38429 & -4.1211 & 3.6e-05 \tabularnewline
2 & -0.540282 & -5.7939 & 0 \tabularnewline
3 & 0.049199 & 0.5276 & 0.299397 \tabularnewline
4 & -0.231818 & -2.486 & 0.007178 \tabularnewline
5 & -0.464395 & -4.9801 & 1e-06 \tabularnewline
6 & 0.219505 & 2.3539 & 0.010136 \tabularnewline
7 & -0.054332 & -0.5826 & 0.280637 \tabularnewline
8 & 0.021434 & 0.2299 & 0.409306 \tabularnewline
9 & 0.102501 & 1.0992 & 0.136989 \tabularnewline
10 & -0.22764 & -2.4412 & 0.008082 \tabularnewline
11 & -0.340251 & -3.6488 & 0.000199 \tabularnewline
12 & 0.307269 & 3.2951 & 0.000654 \tabularnewline
13 & 0.196357 & 2.1057 & 0.018703 \tabularnewline
14 & 0.069506 & 0.7454 & 0.228784 \tabularnewline
15 & -0.05876 & -0.6301 & 0.264928 \tabularnewline
16 & -0.026994 & -0.2895 & 0.386367 \tabularnewline
17 & -0.090858 & -0.9743 & 0.165966 \tabularnewline
18 & 0.145487 & 1.5602 & 0.060733 \tabularnewline
19 & -0.119791 & -1.2846 & 0.100754 \tabularnewline
20 & 0.094059 & 1.0087 & 0.157624 \tabularnewline
21 & 0.003335 & 0.0358 & 0.485768 \tabularnewline
22 & 0.061079 & 0.655 & 0.256887 \tabularnewline
23 & -0.187334 & -2.0089 & 0.023443 \tabularnewline
24 & 0.148533 & 1.5928 & 0.056971 \tabularnewline
25 & 0.132538 & 1.4213 & 0.078966 \tabularnewline
26 & 0.002234 & 0.024 & 0.490465 \tabularnewline
27 & -0.106038 & -1.1371 & 0.128924 \tabularnewline
28 & 0.040918 & 0.4388 & 0.330815 \tabularnewline
29 & -0.010675 & -0.1145 & 0.454531 \tabularnewline
30 & -0.033164 & -0.3556 & 0.361378 \tabularnewline
31 & -0.08846 & -0.9486 & 0.172399 \tabularnewline
32 & -0.02895 & -0.3105 & 0.378388 \tabularnewline
33 & -0.028197 & -0.3024 & 0.381455 \tabularnewline
34 & -0.110772 & -1.1879 & 0.11866 \tabularnewline
35 & -0.061934 & -0.6642 & 0.253957 \tabularnewline
36 & -0.092596 & -0.993 & 0.161403 \tabularnewline
37 & -0.051852 & -0.5561 & 0.289627 \tabularnewline
38 & 0.072196 & 0.7742 & 0.220196 \tabularnewline
39 & 0.003071 & 0.0329 & 0.486893 \tabularnewline
40 & 0.017932 & 0.1923 & 0.423924 \tabularnewline
41 & 0.143207 & 1.5357 & 0.063677 \tabularnewline
42 & -0.066696 & -0.7152 & 0.237957 \tabularnewline
43 & 0.014558 & 0.1561 & 0.438109 \tabularnewline
44 & 0.038935 & 0.4175 & 0.338534 \tabularnewline
45 & -0.064149 & -0.6879 & 0.246445 \tabularnewline
46 & 0.0581 & 0.6231 & 0.26724 \tabularnewline
47 & 0.014602 & 0.1566 & 0.43792 \tabularnewline
48 & -0.095862 & -1.028 & 0.153053 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302755&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]-0.38429[/C][C]-4.1211[/C][C]3.6e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.540282[/C][C]-5.7939[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.049199[/C][C]0.5276[/C][C]0.299397[/C][/ROW]
[ROW][C]4[/C][C]-0.231818[/C][C]-2.486[/C][C]0.007178[/C][/ROW]
[ROW][C]5[/C][C]-0.464395[/C][C]-4.9801[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.219505[/C][C]2.3539[/C][C]0.010136[/C][/ROW]
[ROW][C]7[/C][C]-0.054332[/C][C]-0.5826[/C][C]0.280637[/C][/ROW]
[ROW][C]8[/C][C]0.021434[/C][C]0.2299[/C][C]0.409306[/C][/ROW]
[ROW][C]9[/C][C]0.102501[/C][C]1.0992[/C][C]0.136989[/C][/ROW]
[ROW][C]10[/C][C]-0.22764[/C][C]-2.4412[/C][C]0.008082[/C][/ROW]
[ROW][C]11[/C][C]-0.340251[/C][C]-3.6488[/C][C]0.000199[/C][/ROW]
[ROW][C]12[/C][C]0.307269[/C][C]3.2951[/C][C]0.000654[/C][/ROW]
[ROW][C]13[/C][C]0.196357[/C][C]2.1057[/C][C]0.018703[/C][/ROW]
[ROW][C]14[/C][C]0.069506[/C][C]0.7454[/C][C]0.228784[/C][/ROW]
[ROW][C]15[/C][C]-0.05876[/C][C]-0.6301[/C][C]0.264928[/C][/ROW]
[ROW][C]16[/C][C]-0.026994[/C][C]-0.2895[/C][C]0.386367[/C][/ROW]
[ROW][C]17[/C][C]-0.090858[/C][C]-0.9743[/C][C]0.165966[/C][/ROW]
[ROW][C]18[/C][C]0.145487[/C][C]1.5602[/C][C]0.060733[/C][/ROW]
[ROW][C]19[/C][C]-0.119791[/C][C]-1.2846[/C][C]0.100754[/C][/ROW]
[ROW][C]20[/C][C]0.094059[/C][C]1.0087[/C][C]0.157624[/C][/ROW]
[ROW][C]21[/C][C]0.003335[/C][C]0.0358[/C][C]0.485768[/C][/ROW]
[ROW][C]22[/C][C]0.061079[/C][C]0.655[/C][C]0.256887[/C][/ROW]
[ROW][C]23[/C][C]-0.187334[/C][C]-2.0089[/C][C]0.023443[/C][/ROW]
[ROW][C]24[/C][C]0.148533[/C][C]1.5928[/C][C]0.056971[/C][/ROW]
[ROW][C]25[/C][C]0.132538[/C][C]1.4213[/C][C]0.078966[/C][/ROW]
[ROW][C]26[/C][C]0.002234[/C][C]0.024[/C][C]0.490465[/C][/ROW]
[ROW][C]27[/C][C]-0.106038[/C][C]-1.1371[/C][C]0.128924[/C][/ROW]
[ROW][C]28[/C][C]0.040918[/C][C]0.4388[/C][C]0.330815[/C][/ROW]
[ROW][C]29[/C][C]-0.010675[/C][C]-0.1145[/C][C]0.454531[/C][/ROW]
[ROW][C]30[/C][C]-0.033164[/C][C]-0.3556[/C][C]0.361378[/C][/ROW]
[ROW][C]31[/C][C]-0.08846[/C][C]-0.9486[/C][C]0.172399[/C][/ROW]
[ROW][C]32[/C][C]-0.02895[/C][C]-0.3105[/C][C]0.378388[/C][/ROW]
[ROW][C]33[/C][C]-0.028197[/C][C]-0.3024[/C][C]0.381455[/C][/ROW]
[ROW][C]34[/C][C]-0.110772[/C][C]-1.1879[/C][C]0.11866[/C][/ROW]
[ROW][C]35[/C][C]-0.061934[/C][C]-0.6642[/C][C]0.253957[/C][/ROW]
[ROW][C]36[/C][C]-0.092596[/C][C]-0.993[/C][C]0.161403[/C][/ROW]
[ROW][C]37[/C][C]-0.051852[/C][C]-0.5561[/C][C]0.289627[/C][/ROW]
[ROW][C]38[/C][C]0.072196[/C][C]0.7742[/C][C]0.220196[/C][/ROW]
[ROW][C]39[/C][C]0.003071[/C][C]0.0329[/C][C]0.486893[/C][/ROW]
[ROW][C]40[/C][C]0.017932[/C][C]0.1923[/C][C]0.423924[/C][/ROW]
[ROW][C]41[/C][C]0.143207[/C][C]1.5357[/C][C]0.063677[/C][/ROW]
[ROW][C]42[/C][C]-0.066696[/C][C]-0.7152[/C][C]0.237957[/C][/ROW]
[ROW][C]43[/C][C]0.014558[/C][C]0.1561[/C][C]0.438109[/C][/ROW]
[ROW][C]44[/C][C]0.038935[/C][C]0.4175[/C][C]0.338534[/C][/ROW]
[ROW][C]45[/C][C]-0.064149[/C][C]-0.6879[/C][C]0.246445[/C][/ROW]
[ROW][C]46[/C][C]0.0581[/C][C]0.6231[/C][C]0.26724[/C][/ROW]
[ROW][C]47[/C][C]0.014602[/C][C]0.1566[/C][C]0.43792[/C][/ROW]
[ROW][C]48[/C][C]-0.095862[/C][C]-1.028[/C][C]0.153053[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302755&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302755&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
1-0.38429-4.12113.6e-05
2-0.540282-5.79390
30.0491990.52760.299397
4-0.231818-2.4860.007178
5-0.464395-4.98011e-06
60.2195052.35390.010136
7-0.054332-0.58260.280637
80.0214340.22990.409306
90.1025011.09920.136989
10-0.22764-2.44120.008082
11-0.340251-3.64880.000199
120.3072693.29510.000654
130.1963572.10570.018703
140.0695060.74540.228784
15-0.05876-0.63010.264928
16-0.026994-0.28950.386367
17-0.090858-0.97430.165966
180.1454871.56020.060733
19-0.119791-1.28460.100754
200.0940591.00870.157624
210.0033350.03580.485768
220.0610790.6550.256887
23-0.187334-2.00890.023443
240.1485331.59280.056971
250.1325381.42130.078966
260.0022340.0240.490465
27-0.106038-1.13710.128924
280.0409180.43880.330815
29-0.010675-0.11450.454531
30-0.033164-0.35560.361378
31-0.08846-0.94860.172399
32-0.02895-0.31050.378388
33-0.028197-0.30240.381455
34-0.110772-1.18790.11866
35-0.061934-0.66420.253957
36-0.092596-0.9930.161403
37-0.051852-0.55610.289627
380.0721960.77420.220196
390.0030710.03290.486893
400.0179320.19230.423924
410.1432071.53570.063677
42-0.066696-0.71520.237957
430.0145580.15610.438109
440.0389350.41750.338534
45-0.064149-0.68790.246445
460.05810.62310.26724
470.0146020.15660.43792
48-0.095862-1.0280.153053


Figures (Output of Computation)

Input Parameters & R Code

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