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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 10 Dec 2008 01:02:44 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/10/t12288961866uwo8p2ekuy9r8a.htm/, Retrieved Sun, 19 May 2024 06:44:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31872, Retrieved Sun, 19 May 2024 06:44:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact219

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [(Partial) Autocorrelation Function] [] [2008-12-10 08:02:44] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-14 16:04:23 [Steven Vanhooreweghe] [reply] 
hier kan je zien dat er een inderdaad een lange termijn trend aanwezig is. Je zult dus niet-seizoenaal moeten differentieren. Dat komt overeen met het VRM (d=1)

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
19.644
18.483
18.079
19.178
18.391
18.441
18.584
20.108
20.148
19.394
17.745
17.696
17.032
16.438
15.683
15.594
15.713
15.937
16.171
15.928
16.348
15.579
15.305
15.648
14.954
15.137
15.839
16.05
15.168
17.064
16.005
14.886
14.931
14.544
13.812
13.031
12.574
11.964
11.451
11.346
11.353
10.702
10.646
10.556
10.463
10.407
10.625
10.872
10.805
10.653
10.574
10.431
10.383
10.296
10.872
10.635
10.297
10.57
10.662
10.709
10.413
10.846
10.371
9.924
9.828
9.897
9.721
10.171
10.738
10.812
10.511
10.244
10.368
10.457
10.186
10.166
10.827
10.997
10.94
10.756
10.893
10.236
9.96
10.018
10.063
10.002
9.728
10.002
10.177
9.948
9.394
9.308
9.155
9.103
9.732
9.984

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31872&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31872&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31872&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9593479.39960
20.9251269.06430
30.8934578.75410
40.8507868.3360
50.810197.93820
60.773957.58310
70.7399567.25010
80.6958766.81820
90.6510356.37880
100.6067245.94470
110.5732375.61660
120.5369215.26070
130.5046714.94472e-06
140.4766744.67045e-06
150.4551374.45941.1e-05
160.4367214.2792.2e-05
170.41964.11124.1e-05
180.4023263.9427.7e-05
190.3806593.72970.000162

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.959347 & 9.3996 & 0 \tabularnewline
2 & 0.925126 & 9.0643 & 0 \tabularnewline
3 & 0.893457 & 8.7541 & 0 \tabularnewline
4 & 0.850786 & 8.336 & 0 \tabularnewline
5 & 0.81019 & 7.9382 & 0 \tabularnewline
6 & 0.77395 & 7.5831 & 0 \tabularnewline
7 & 0.739956 & 7.2501 & 0 \tabularnewline
8 & 0.695876 & 6.8182 & 0 \tabularnewline
9 & 0.651035 & 6.3788 & 0 \tabularnewline
10 & 0.606724 & 5.9447 & 0 \tabularnewline
11 & 0.573237 & 5.6166 & 0 \tabularnewline
12 & 0.536921 & 5.2607 & 0 \tabularnewline
13 & 0.504671 & 4.9447 & 2e-06 \tabularnewline
14 & 0.476674 & 4.6704 & 5e-06 \tabularnewline
15 & 0.455137 & 4.4594 & 1.1e-05 \tabularnewline
16 & 0.436721 & 4.279 & 2.2e-05 \tabularnewline
17 & 0.4196 & 4.1112 & 4.1e-05 \tabularnewline
18 & 0.402326 & 3.942 & 7.7e-05 \tabularnewline
19 & 0.380659 & 3.7297 & 0.000162 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31872&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]0.959347[/C][C]9.3996[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.925126[/C][C]9.0643[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.893457[/C][C]8.7541[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.850786[/C][C]8.336[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.81019[/C][C]7.9382[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.77395[/C][C]7.5831[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.739956[/C][C]7.2501[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.695876[/C][C]6.8182[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.651035[/C][C]6.3788[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.606724[/C][C]5.9447[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.573237[/C][C]5.6166[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.536921[/C][C]5.2607[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.504671[/C][C]4.9447[/C][C]2e-06[/C][/ROW]
[ROW][C]14[/C][C]0.476674[/C][C]4.6704[/C][C]5e-06[/C][/ROW]
[ROW][C]15[/C][C]0.455137[/C][C]4.4594[/C][C]1.1e-05[/C][/ROW]
[ROW][C]16[/C][C]0.436721[/C][C]4.279[/C][C]2.2e-05[/C][/ROW]
[ROW][C]17[/C][C]0.4196[/C][C]4.1112[/C][C]4.1e-05[/C][/ROW]
[ROW][C]18[/C][C]0.402326[/C][C]3.942[/C][C]7.7e-05[/C][/ROW]
[ROW][C]19[/C][C]0.380659[/C][C]3.7297[/C][C]0.000162[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31872&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31872&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
10.9593479.39960
20.9251269.06430
30.8934578.75410
40.8507868.3360
50.810197.93820
60.773957.58310
70.7399567.25010
80.6958766.81820
90.6510356.37880
100.6067245.94470
110.5732375.61660
120.5369215.26070
130.5046714.94472e-06
140.4766744.67045e-06
150.4551374.45941.1e-05
160.4367214.2792.2e-05
170.41964.11124.1e-05
180.4023263.9427.7e-05
190.3806593.72970.000162






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9593479.39960
20.0600070.58790.278975
30.0205470.20130.420439
4-0.149966-1.46940.072502
5-0.016744-0.16410.435016
60.0276820.27120.393398
70.0354550.34740.364531
8-0.144931-1.420.079419
9-0.068101-0.66730.253106
10-0.039292-0.3850.350552
110.154621.5150.066535
12-0.028838-0.28260.389064
130.0173780.17030.43258
14-0.021204-0.20780.417929
150.1092581.07050.143539
160.0540920.530.298672
170.019240.18850.425435
18-0.088229-0.86450.194745
19-0.08232-0.80660.210954

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.959347 & 9.3996 & 0 \tabularnewline
2 & 0.060007 & 0.5879 & 0.278975 \tabularnewline
3 & 0.020547 & 0.2013 & 0.420439 \tabularnewline
4 & -0.149966 & -1.4694 & 0.072502 \tabularnewline
5 & -0.016744 & -0.1641 & 0.435016 \tabularnewline
6 & 0.027682 & 0.2712 & 0.393398 \tabularnewline
7 & 0.035455 & 0.3474 & 0.364531 \tabularnewline
8 & -0.144931 & -1.42 & 0.079419 \tabularnewline
9 & -0.068101 & -0.6673 & 0.253106 \tabularnewline
10 & -0.039292 & -0.385 & 0.350552 \tabularnewline
11 & 0.15462 & 1.515 & 0.066535 \tabularnewline
12 & -0.028838 & -0.2826 & 0.389064 \tabularnewline
13 & 0.017378 & 0.1703 & 0.43258 \tabularnewline
14 & -0.021204 & -0.2078 & 0.417929 \tabularnewline
15 & 0.109258 & 1.0705 & 0.143539 \tabularnewline
16 & 0.054092 & 0.53 & 0.298672 \tabularnewline
17 & 0.01924 & 0.1885 & 0.425435 \tabularnewline
18 & -0.088229 & -0.8645 & 0.194745 \tabularnewline
19 & -0.08232 & -0.8066 & 0.210954 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31872&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]0.959347[/C][C]9.3996[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.060007[/C][C]0.5879[/C][C]0.278975[/C][/ROW]
[ROW][C]3[/C][C]0.020547[/C][C]0.2013[/C][C]0.420439[/C][/ROW]
[ROW][C]4[/C][C]-0.149966[/C][C]-1.4694[/C][C]0.072502[/C][/ROW]
[ROW][C]5[/C][C]-0.016744[/C][C]-0.1641[/C][C]0.435016[/C][/ROW]
[ROW][C]6[/C][C]0.027682[/C][C]0.2712[/C][C]0.393398[/C][/ROW]
[ROW][C]7[/C][C]0.035455[/C][C]0.3474[/C][C]0.364531[/C][/ROW]
[ROW][C]8[/C][C]-0.144931[/C][C]-1.42[/C][C]0.079419[/C][/ROW]
[ROW][C]9[/C][C]-0.068101[/C][C]-0.6673[/C][C]0.253106[/C][/ROW]
[ROW][C]10[/C][C]-0.039292[/C][C]-0.385[/C][C]0.350552[/C][/ROW]
[ROW][C]11[/C][C]0.15462[/C][C]1.515[/C][C]0.066535[/C][/ROW]
[ROW][C]12[/C][C]-0.028838[/C][C]-0.2826[/C][C]0.389064[/C][/ROW]
[ROW][C]13[/C][C]0.017378[/C][C]0.1703[/C][C]0.43258[/C][/ROW]
[ROW][C]14[/C][C]-0.021204[/C][C]-0.2078[/C][C]0.417929[/C][/ROW]
[ROW][C]15[/C][C]0.109258[/C][C]1.0705[/C][C]0.143539[/C][/ROW]
[ROW][C]16[/C][C]0.054092[/C][C]0.53[/C][C]0.298672[/C][/ROW]
[ROW][C]17[/C][C]0.01924[/C][C]0.1885[/C][C]0.425435[/C][/ROW]
[ROW][C]18[/C][C]-0.088229[/C][C]-0.8645[/C][C]0.194745[/C][/ROW]
[ROW][C]19[/C][C]-0.08232[/C][C]-0.8066[/C][C]0.210954[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31872&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31872&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
10.9593479.39960
20.0600070.58790.278975
30.0205470.20130.420439
4-0.149966-1.46940.072502
5-0.016744-0.16410.435016
60.0276820.27120.393398
70.0354550.34740.364531
8-0.144931-1.420.079419
9-0.068101-0.66730.253106
10-0.039292-0.3850.350552
110.154621.5150.066535
12-0.028838-0.28260.389064
130.0173780.17030.43258
14-0.021204-0.20780.417929
150.1092581.07050.143539
160.0540920.530.298672
170.019240.18850.425435
18-0.088229-0.86450.194745
19-0.08232-0.80660.210954


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),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,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),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')