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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, 12 Dec 2007 09:57:56 -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/2007/Dec/12/t1197477780g71p761jixertd0.htm/, Retrieved Thu, 02 May 2024 22:35:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3247, Retrieved Thu, 02 May 2024 22:35:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact201

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 autocorr G29] [2007-12-12 16:57:56] [8e05505c645e933583b5ad9ab4281af9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
145,3
143,6
142,8
155,9
156,2
149,8
152,7
155,5
159,3
143
141,4
142,8
146,4
152,3
164,3
168
171,3
162,7
150,2
142,5
138,2
138
145,1
138,4
131,8
130,8
126,3
123
124
120,8
122,1
106,5
104,3
108,7
113,8
112,5
106,1
98,4
96
99,3
97,5
95,3
88
94,7
99,4
98,9
96,4
95,3
99,5
101,6
103,9
106,6
108,3
102
93,8
91,6
97,7
94,8
98
103,8
97,8
91,2
89,3
87,5
90,4
94,2
102,2
101,3
96
90,8
93,2
90,9
91,1
90,2
94,3
96
99
103,3
113,1
112,8
112,1
107,4
111
110,5
110,8
112,4
111,5
116,2
122,5
121,3
113,9
110,7
120,8
141,1
147,4
148
158,1
165
187
190,3
182,4
168,8
151,2
120,1
112,5
106,2
107,1
108,5
106,5
108,3
125,6
124
127,2
136,9
135,8
124,3
115,4
113,6
114,4
118,4
117
116,5
115,4
113,6
117,4
116,9
116,4
111,1
110,2
118,9
131,8
130,6
138,3
148,4
148,7
144,3
152,5
162,9
167,2
166,5
185,6

Tables (Output of Computation)





Summary of compuational 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 compuational 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=3247&T=0

[TABLE]
[ROW][C]Summary of compuational 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=3247&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3247&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 compuational 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
0111.35780
10.91388810.37980
20.7939139.01710
30.6702387.61240
40.5493476.23940
50.4344324.93421e-06
60.3180223.6120.000217
70.207322.35470.010023
80.1157641.31480.095451
90.0359880.40870.341704
10-0.026403-0.29990.617624
11-0.066662-0.75710.774824
12-0.078272-0.8890.812172
13-0.039809-0.45210.674038
140.0053760.06110.475703
150.0418370.47520.317733
160.0659430.7490.227621
170.0715030.81210.209111
180.0681840.77440.220048
190.0551420.62630.266116
200.012840.14580.44214

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 11.3578 & 0 \tabularnewline
1 & 0.913888 & 10.3798 & 0 \tabularnewline
2 & 0.793913 & 9.0171 & 0 \tabularnewline
3 & 0.670238 & 7.6124 & 0 \tabularnewline
4 & 0.549347 & 6.2394 & 0 \tabularnewline
5 & 0.434432 & 4.9342 & 1e-06 \tabularnewline
6 & 0.318022 & 3.612 & 0.000217 \tabularnewline
7 & 0.20732 & 2.3547 & 0.010023 \tabularnewline
8 & 0.115764 & 1.3148 & 0.095451 \tabularnewline
9 & 0.035988 & 0.4087 & 0.341704 \tabularnewline
10 & -0.026403 & -0.2999 & 0.617624 \tabularnewline
11 & -0.066662 & -0.7571 & 0.774824 \tabularnewline
12 & -0.078272 & -0.889 & 0.812172 \tabularnewline
13 & -0.039809 & -0.4521 & 0.674038 \tabularnewline
14 & 0.005376 & 0.0611 & 0.475703 \tabularnewline
15 & 0.041837 & 0.4752 & 0.317733 \tabularnewline
16 & 0.065943 & 0.749 & 0.227621 \tabularnewline
17 & 0.071503 & 0.8121 & 0.209111 \tabularnewline
18 & 0.068184 & 0.7744 & 0.220048 \tabularnewline
19 & 0.055142 & 0.6263 & 0.266116 \tabularnewline
20 & 0.01284 & 0.1458 & 0.44214 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3247&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]0[/C][C]1[/C][C]11.3578[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]0.913888[/C][C]10.3798[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.793913[/C][C]9.0171[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.670238[/C][C]7.6124[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.549347[/C][C]6.2394[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.434432[/C][C]4.9342[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.318022[/C][C]3.612[/C][C]0.000217[/C][/ROW]
[ROW][C]7[/C][C]0.20732[/C][C]2.3547[/C][C]0.010023[/C][/ROW]
[ROW][C]8[/C][C]0.115764[/C][C]1.3148[/C][C]0.095451[/C][/ROW]
[ROW][C]9[/C][C]0.035988[/C][C]0.4087[/C][C]0.341704[/C][/ROW]
[ROW][C]10[/C][C]-0.026403[/C][C]-0.2999[/C][C]0.617624[/C][/ROW]
[ROW][C]11[/C][C]-0.066662[/C][C]-0.7571[/C][C]0.774824[/C][/ROW]
[ROW][C]12[/C][C]-0.078272[/C][C]-0.889[/C][C]0.812172[/C][/ROW]
[ROW][C]13[/C][C]-0.039809[/C][C]-0.4521[/C][C]0.674038[/C][/ROW]
[ROW][C]14[/C][C]0.005376[/C][C]0.0611[/C][C]0.475703[/C][/ROW]
[ROW][C]15[/C][C]0.041837[/C][C]0.4752[/C][C]0.317733[/C][/ROW]
[ROW][C]16[/C][C]0.065943[/C][C]0.749[/C][C]0.227621[/C][/ROW]
[ROW][C]17[/C][C]0.071503[/C][C]0.8121[/C][C]0.209111[/C][/ROW]
[ROW][C]18[/C][C]0.068184[/C][C]0.7744[/C][C]0.220048[/C][/ROW]
[ROW][C]19[/C][C]0.055142[/C][C]0.6263[/C][C]0.266116[/C][/ROW]
[ROW][C]20[/C][C]0.01284[/C][C]0.1458[/C][C]0.44214[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3247&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3247&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
0111.35780
10.91388810.37980
20.7939139.01710
30.6702387.61240
40.5493476.23940
50.4344324.93421e-06
60.3180223.6120.000217
70.207322.35470.010023
80.1157641.31480.095451
90.0359880.40870.341704
10-0.026403-0.29990.617624
11-0.066662-0.75710.774824
12-0.078272-0.8890.812172
13-0.039809-0.45210.674038
140.0053760.06110.475703
150.0418370.47520.317733
160.0659430.7490.227621
170.0715030.81210.209111
180.0681840.77440.220048
190.0551420.62630.266116
200.012840.14580.44214






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.91388810.37980
1-0.250453-2.84460.997413
2-0.05269-0.59840.724702
3-0.055514-0.63050.735264
4-0.046398-0.5270.700443
5-0.102806-1.16770.877449
6-0.045329-0.51480.696227
70.0212020.24080.405042
8-0.048591-0.55190.709009
90.0114280.12980.448463
100.0398480.45260.325803
110.0872710.99120.161719
120.2298352.61040.005057
13-0.056894-0.64620.74035
14-0.044379-0.50410.692458
15-0.05469-0.62120.732204
16-0.093871-1.06620.855831
17-0.043116-0.48970.687414
18-0.048216-0.54760.707552
19-0.156424-1.77660.961007
20-0.006432-0.07310.529061

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & 0.913888 & 10.3798 & 0 \tabularnewline
1 & -0.250453 & -2.8446 & 0.997413 \tabularnewline
2 & -0.05269 & -0.5984 & 0.724702 \tabularnewline
3 & -0.055514 & -0.6305 & 0.735264 \tabularnewline
4 & -0.046398 & -0.527 & 0.700443 \tabularnewline
5 & -0.102806 & -1.1677 & 0.877449 \tabularnewline
6 & -0.045329 & -0.5148 & 0.696227 \tabularnewline
7 & 0.021202 & 0.2408 & 0.405042 \tabularnewline
8 & -0.048591 & -0.5519 & 0.709009 \tabularnewline
9 & 0.011428 & 0.1298 & 0.448463 \tabularnewline
10 & 0.039848 & 0.4526 & 0.325803 \tabularnewline
11 & 0.087271 & 0.9912 & 0.161719 \tabularnewline
12 & 0.229835 & 2.6104 & 0.005057 \tabularnewline
13 & -0.056894 & -0.6462 & 0.74035 \tabularnewline
14 & -0.044379 & -0.5041 & 0.692458 \tabularnewline
15 & -0.05469 & -0.6212 & 0.732204 \tabularnewline
16 & -0.093871 & -1.0662 & 0.855831 \tabularnewline
17 & -0.043116 & -0.4897 & 0.687414 \tabularnewline
18 & -0.048216 & -0.5476 & 0.707552 \tabularnewline
19 & -0.156424 & -1.7766 & 0.961007 \tabularnewline
20 & -0.006432 & -0.0731 & 0.529061 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3247&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]0[/C][C]0.913888[/C][C]10.3798[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]-0.250453[/C][C]-2.8446[/C][C]0.997413[/C][/ROW]
[ROW][C]2[/C][C]-0.05269[/C][C]-0.5984[/C][C]0.724702[/C][/ROW]
[ROW][C]3[/C][C]-0.055514[/C][C]-0.6305[/C][C]0.735264[/C][/ROW]
[ROW][C]4[/C][C]-0.046398[/C][C]-0.527[/C][C]0.700443[/C][/ROW]
[ROW][C]5[/C][C]-0.102806[/C][C]-1.1677[/C][C]0.877449[/C][/ROW]
[ROW][C]6[/C][C]-0.045329[/C][C]-0.5148[/C][C]0.696227[/C][/ROW]
[ROW][C]7[/C][C]0.021202[/C][C]0.2408[/C][C]0.405042[/C][/ROW]
[ROW][C]8[/C][C]-0.048591[/C][C]-0.5519[/C][C]0.709009[/C][/ROW]
[ROW][C]9[/C][C]0.011428[/C][C]0.1298[/C][C]0.448463[/C][/ROW]
[ROW][C]10[/C][C]0.039848[/C][C]0.4526[/C][C]0.325803[/C][/ROW]
[ROW][C]11[/C][C]0.087271[/C][C]0.9912[/C][C]0.161719[/C][/ROW]
[ROW][C]12[/C][C]0.229835[/C][C]2.6104[/C][C]0.005057[/C][/ROW]
[ROW][C]13[/C][C]-0.056894[/C][C]-0.6462[/C][C]0.74035[/C][/ROW]
[ROW][C]14[/C][C]-0.044379[/C][C]-0.5041[/C][C]0.692458[/C][/ROW]
[ROW][C]15[/C][C]-0.05469[/C][C]-0.6212[/C][C]0.732204[/C][/ROW]
[ROW][C]16[/C][C]-0.093871[/C][C]-1.0662[/C][C]0.855831[/C][/ROW]
[ROW][C]17[/C][C]-0.043116[/C][C]-0.4897[/C][C]0.687414[/C][/ROW]
[ROW][C]18[/C][C]-0.048216[/C][C]-0.5476[/C][C]0.707552[/C][/ROW]
[ROW][C]19[/C][C]-0.156424[/C][C]-1.7766[/C][C]0.961007[/C][/ROW]
[ROW][C]20[/C][C]-0.006432[/C][C]-0.0731[/C][C]0.529061[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3247&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3247&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
00.91388810.37980
1-0.250453-2.84460.997413
2-0.05269-0.59840.724702
3-0.055514-0.63050.735264
4-0.046398-0.5270.700443
5-0.102806-1.16770.877449
6-0.045329-0.51480.696227
70.0212020.24080.405042
8-0.048591-0.55190.709009
90.0114280.12980.448463
100.0398480.45260.325803
110.0872710.99120.161719
120.2298352.61040.005057
13-0.056894-0.64620.74035
14-0.044379-0.50410.692458
15-0.05469-0.62120.732204
16-0.093871-1.06620.855831
17-0.043116-0.48970.687414
18-0.048216-0.54760.707552
19-0.156424-1.77660.961007
20-0.006432-0.07310.529061


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 0.0 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 0.0 ; par3 = 0 ; par4 = 1 ; 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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')