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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 computationMon, 10 Dec 2012 10:16:35 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/10/t1355152611yecothvl2hlhh6g.htm/, Retrieved Thu, 25 Apr 2024 00:23:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198186, Retrieved Thu, 25 Apr 2024 00:23:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [] [2012-12-10 15:16:35] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   P         [(Partial) Autocorrelation Function] [] [2012-12-19 15:26:35] [74be16979710d4c4e7c6647856088456]
-   P           [(Partial) Autocorrelation Function] [] [2012-12-19 16:17:43] [bbed103f50d9b60ea97669d7e6947a11]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
59.8
60.7
59.7
60.2
61.3
59.8
61.2
59.3
59.4
63.1
68
69.4
70.2
72.6
72.1
69.7
71.5
75.7
76
76.4
83.8
86.2
88.5
95.9
103.1
113.5
115.7
113.1
112.7
121.9
120.3
108.7
102.8
83.4
79.4
77.8
85.7
83.2
82
86.9
95.7
97.9
89.3
91.5
86.8
91
93.8
96.8
95.7
91.4
88.7
88.2
87.7
89.5
95.6
100.5
106.3
112
117.7
125
132.4
138.1
134.7
136.7
134.3
131.6
129.8
131.9
129.8
119.4
116.7
112.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198186&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198186&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198186&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.336699-2.8170.003147
2-0.045269-0.37880.353009
3-0.146617-1.22670.112025
40.0995210.83270.203936
50.015140.12670.449784
6-0.092959-0.77780.219668
70.2175721.82030.036491
8-0.320909-2.68490.004525
90.1399751.17110.122762
10-0.207275-1.73420.043643
110.3083822.58010.005989
12-0.086441-0.72320.235978
13-0.112174-0.93850.175604
140.0074370.06220.47528
15-0.01241-0.10380.458801
160.1696751.41960.080081
17-0.12401-1.03750.151528
180.0352090.29460.384593

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.336699 & -2.817 & 0.003147 \tabularnewline
2 & -0.045269 & -0.3788 & 0.353009 \tabularnewline
3 & -0.146617 & -1.2267 & 0.112025 \tabularnewline
4 & 0.099521 & 0.8327 & 0.203936 \tabularnewline
5 & 0.01514 & 0.1267 & 0.449784 \tabularnewline
6 & -0.092959 & -0.7778 & 0.219668 \tabularnewline
7 & 0.217572 & 1.8203 & 0.036491 \tabularnewline
8 & -0.320909 & -2.6849 & 0.004525 \tabularnewline
9 & 0.139975 & 1.1711 & 0.122762 \tabularnewline
10 & -0.207275 & -1.7342 & 0.043643 \tabularnewline
11 & 0.308382 & 2.5801 & 0.005989 \tabularnewline
12 & -0.086441 & -0.7232 & 0.235978 \tabularnewline
13 & -0.112174 & -0.9385 & 0.175604 \tabularnewline
14 & 0.007437 & 0.0622 & 0.47528 \tabularnewline
15 & -0.01241 & -0.1038 & 0.458801 \tabularnewline
16 & 0.169675 & 1.4196 & 0.080081 \tabularnewline
17 & -0.12401 & -1.0375 & 0.151528 \tabularnewline
18 & 0.035209 & 0.2946 & 0.384593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198186&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]-0.336699[/C][C]-2.817[/C][C]0.003147[/C][/ROW]
[ROW][C]2[/C][C]-0.045269[/C][C]-0.3788[/C][C]0.353009[/C][/ROW]
[ROW][C]3[/C][C]-0.146617[/C][C]-1.2267[/C][C]0.112025[/C][/ROW]
[ROW][C]4[/C][C]0.099521[/C][C]0.8327[/C][C]0.203936[/C][/ROW]
[ROW][C]5[/C][C]0.01514[/C][C]0.1267[/C][C]0.449784[/C][/ROW]
[ROW][C]6[/C][C]-0.092959[/C][C]-0.7778[/C][C]0.219668[/C][/ROW]
[ROW][C]7[/C][C]0.217572[/C][C]1.8203[/C][C]0.036491[/C][/ROW]
[ROW][C]8[/C][C]-0.320909[/C][C]-2.6849[/C][C]0.004525[/C][/ROW]
[ROW][C]9[/C][C]0.139975[/C][C]1.1711[/C][C]0.122762[/C][/ROW]
[ROW][C]10[/C][C]-0.207275[/C][C]-1.7342[/C][C]0.043643[/C][/ROW]
[ROW][C]11[/C][C]0.308382[/C][C]2.5801[/C][C]0.005989[/C][/ROW]
[ROW][C]12[/C][C]-0.086441[/C][C]-0.7232[/C][C]0.235978[/C][/ROW]
[ROW][C]13[/C][C]-0.112174[/C][C]-0.9385[/C][C]0.175604[/C][/ROW]
[ROW][C]14[/C][C]0.007437[/C][C]0.0622[/C][C]0.47528[/C][/ROW]
[ROW][C]15[/C][C]-0.01241[/C][C]-0.1038[/C][C]0.458801[/C][/ROW]
[ROW][C]16[/C][C]0.169675[/C][C]1.4196[/C][C]0.080081[/C][/ROW]
[ROW][C]17[/C][C]-0.12401[/C][C]-1.0375[/C][C]0.151528[/C][/ROW]
[ROW][C]18[/C][C]0.035209[/C][C]0.2946[/C][C]0.384593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198186&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198186&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
1-0.336699-2.8170.003147
2-0.045269-0.37880.353009
3-0.146617-1.22670.112025
40.0995210.83270.203936
50.015140.12670.449784
6-0.092959-0.77780.219668
70.2175721.82030.036491
8-0.320909-2.68490.004525
90.1399751.17110.122762
10-0.207275-1.73420.043643
110.3083822.58010.005989
12-0.086441-0.72320.235978
13-0.112174-0.93850.175604
140.0074370.06220.47528
15-0.01241-0.10380.458801
160.1696751.41960.080081
17-0.12401-1.03750.151528
180.0352090.29460.384593






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.336699-2.8170.003147
2-0.178919-1.49690.069452
3-0.261961-2.19170.015864
4-0.083265-0.69660.244167
5-0.031519-0.26370.396391
6-0.144664-1.21030.115109
70.1796791.50330.06863
8-0.250008-2.09170.020047
9-0.052304-0.43760.331509
10-0.274741-2.29860.012258
110.0627950.52540.300489
12-0.005624-0.04710.481302
13-0.155929-1.30460.098151
14-0.115741-0.96840.168099
15-0.075294-0.630.265389
16-0.020491-0.17140.432186
170.0107480.08990.464301
18-0.200542-1.67790.048918

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.336699 & -2.817 & 0.003147 \tabularnewline
2 & -0.178919 & -1.4969 & 0.069452 \tabularnewline
3 & -0.261961 & -2.1917 & 0.015864 \tabularnewline
4 & -0.083265 & -0.6966 & 0.244167 \tabularnewline
5 & -0.031519 & -0.2637 & 0.396391 \tabularnewline
6 & -0.144664 & -1.2103 & 0.115109 \tabularnewline
7 & 0.179679 & 1.5033 & 0.06863 \tabularnewline
8 & -0.250008 & -2.0917 & 0.020047 \tabularnewline
9 & -0.052304 & -0.4376 & 0.331509 \tabularnewline
10 & -0.274741 & -2.2986 & 0.012258 \tabularnewline
11 & 0.062795 & 0.5254 & 0.300489 \tabularnewline
12 & -0.005624 & -0.0471 & 0.481302 \tabularnewline
13 & -0.155929 & -1.3046 & 0.098151 \tabularnewline
14 & -0.115741 & -0.9684 & 0.168099 \tabularnewline
15 & -0.075294 & -0.63 & 0.265389 \tabularnewline
16 & -0.020491 & -0.1714 & 0.432186 \tabularnewline
17 & 0.010748 & 0.0899 & 0.464301 \tabularnewline
18 & -0.200542 & -1.6779 & 0.048918 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198186&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]-0.336699[/C][C]-2.817[/C][C]0.003147[/C][/ROW]
[ROW][C]2[/C][C]-0.178919[/C][C]-1.4969[/C][C]0.069452[/C][/ROW]
[ROW][C]3[/C][C]-0.261961[/C][C]-2.1917[/C][C]0.015864[/C][/ROW]
[ROW][C]4[/C][C]-0.083265[/C][C]-0.6966[/C][C]0.244167[/C][/ROW]
[ROW][C]5[/C][C]-0.031519[/C][C]-0.2637[/C][C]0.396391[/C][/ROW]
[ROW][C]6[/C][C]-0.144664[/C][C]-1.2103[/C][C]0.115109[/C][/ROW]
[ROW][C]7[/C][C]0.179679[/C][C]1.5033[/C][C]0.06863[/C][/ROW]
[ROW][C]8[/C][C]-0.250008[/C][C]-2.0917[/C][C]0.020047[/C][/ROW]
[ROW][C]9[/C][C]-0.052304[/C][C]-0.4376[/C][C]0.331509[/C][/ROW]
[ROW][C]10[/C][C]-0.274741[/C][C]-2.2986[/C][C]0.012258[/C][/ROW]
[ROW][C]11[/C][C]0.062795[/C][C]0.5254[/C][C]0.300489[/C][/ROW]
[ROW][C]12[/C][C]-0.005624[/C][C]-0.0471[/C][C]0.481302[/C][/ROW]
[ROW][C]13[/C][C]-0.155929[/C][C]-1.3046[/C][C]0.098151[/C][/ROW]
[ROW][C]14[/C][C]-0.115741[/C][C]-0.9684[/C][C]0.168099[/C][/ROW]
[ROW][C]15[/C][C]-0.075294[/C][C]-0.63[/C][C]0.265389[/C][/ROW]
[ROW][C]16[/C][C]-0.020491[/C][C]-0.1714[/C][C]0.432186[/C][/ROW]
[ROW][C]17[/C][C]0.010748[/C][C]0.0899[/C][C]0.464301[/C][/ROW]
[ROW][C]18[/C][C]-0.200542[/C][C]-1.6779[/C][C]0.048918[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198186&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198186&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
1-0.336699-2.8170.003147
2-0.178919-1.49690.069452
3-0.261961-2.19170.015864
4-0.083265-0.69660.244167
5-0.031519-0.26370.396391
6-0.144664-1.21030.115109
70.1796791.50330.06863
8-0.250008-2.09170.020047
9-0.052304-0.43760.331509
10-0.274741-2.29860.012258
110.0627950.52540.300489
12-0.005624-0.04710.481302
13-0.155929-1.30460.098151
14-0.115741-0.96840.168099
15-0.075294-0.630.265389
16-0.020491-0.17140.432186
170.0107480.08990.464301
18-0.200542-1.67790.048918


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 2 ; 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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')