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_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationTue, 02 Dec 2008 13:18:21 -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/02/t1228249197mk9kpw5x4rbana1.htm/, Retrieved Sat, 18 May 2024 08:25:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28362, Retrieved Sat, 18 May 2024 08:25:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPartial correlation eigen tijdsreeks
Estimated Impact146

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 correlati...] [2008-12-02 20:04:35] [12d343c4448a5f9e527bb31caeac580b]
- RMPD  [Cross Correlation Function] [Cross correlatie ...] [2008-12-02 20:15:37] [12d343c4448a5f9e527bb31caeac580b]
-   PD      [Cross Correlation Function] [Partial correlati...] [2008-12-02 20:18:21] [0cdfeda4aa2f9e551c2e529c44a404df] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
119.5
125
145
105.3
116.9
120.1
88.9
78.4
114.6
113.3
117
99.6
99.4
101.9
115.2
108.5
113.8
121
92.2
90.2
101.5
126.6
93.9
89.8
93.4
101.5
110.4
105.9
108.4
113.9
86.1
69.4
101.2
100.5
98
106.6
90.1
96.9
125.9
112
100
123.9
79.8
83.4
113.6
112.9
104
109.9
99
106.3
128.9
111.1
102.9
130
87
87.5
117.6
103.4
110.8
112.6
102.5
112.4
135.6
105.1
127.7
137
91
90.5
122.4
123.3
124.3
120
118.1
119
142.7
123.6
129.6
151.6
110.4
99.2
130.5
136.2
129.7
128
121.6
Dataseries Y:
Download CSV
Histogram 
98.6
98
106.8
96.6
100.1
107.7
91.5
97.8
107.4
117.5
105.6
97.4
99.5
98
104.3
100.6
101.1
103.9
96.9
95.5
108.4
117
103.8
100.8
110.6
104
112.6
107.3
98.9
109.8
104.9
102.2
123.9
124.9
112.7
121.9
100.6
104.3
120.4
107.5
102.9
125.6
107.5
108.8
128.4
121.1
119.5
128.7
108.7
105.5
119.8
111.3
110.6
120.1
97.5
107.7
127.3
117.2
119.8
116.2
111
112.4
130.6
109.1
118.8
123.9
101.6
112.8
128
129.6
125.8
119.5
115.7
113.6
129.7
112
116.8
127
112.1
114.2
121.1
131.6
125
120.4
117.7

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=28362&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=28362&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28362&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






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0.3
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series-1.8
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-16-0.132004866088583
-150.174221623123277
-14-0.233081448459481
-13-0.249864299092885
-120.592648862740482
-11-0.117939176513765
-10-0.361138332194136
-90.327760396066963
-8-0.139891314554085
-7-0.164379206687980
-60.390671094260933
-5-0.075562426409541
-4-0.196073719537936
-30.369247545654746
-2-0.440067754561784
-1-0.329496313129651
00.827754368208874
1-0.203332206996330
2-0.401001955163751
30.435038177868258
4-0.233664726674106
5-0.179194596166811
60.455751910076626
7-0.181241705405038
8-0.086813910961025
90.326690870105137
10-0.45569157757879
11-0.205841353358516
120.673252798815437
13-0.216480276052021
14-0.218376674386249
150.287049574254554
16-0.243639193380135

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0.3 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \tabularnewline
Seasonal Period (s) & 1 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & -1.8 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & -0.132004866088583 \tabularnewline
-15 & 0.174221623123277 \tabularnewline
-14 & -0.233081448459481 \tabularnewline
-13 & -0.249864299092885 \tabularnewline
-12 & 0.592648862740482 \tabularnewline
-11 & -0.117939176513765 \tabularnewline
-10 & -0.361138332194136 \tabularnewline
-9 & 0.327760396066963 \tabularnewline
-8 & -0.139891314554085 \tabularnewline
-7 & -0.164379206687980 \tabularnewline
-6 & 0.390671094260933 \tabularnewline
-5 & -0.075562426409541 \tabularnewline
-4 & -0.196073719537936 \tabularnewline
-3 & 0.369247545654746 \tabularnewline
-2 & -0.440067754561784 \tabularnewline
-1 & -0.329496313129651 \tabularnewline
0 & 0.827754368208874 \tabularnewline
1 & -0.203332206996330 \tabularnewline
2 & -0.401001955163751 \tabularnewline
3 & 0.435038177868258 \tabularnewline
4 & -0.233664726674106 \tabularnewline
5 & -0.179194596166811 \tabularnewline
6 & 0.455751910076626 \tabularnewline
7 & -0.181241705405038 \tabularnewline
8 & -0.086813910961025 \tabularnewline
9 & 0.326690870105137 \tabularnewline
10 & -0.45569157757879 \tabularnewline
11 & -0.205841353358516 \tabularnewline
12 & 0.673252798815437 \tabularnewline
13 & -0.216480276052021 \tabularnewline
14 & -0.218376674386249 \tabularnewline
15 & 0.287049574254554 \tabularnewline
16 & -0.243639193380135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28362&T=1

[TABLE]
[ROW][C]Cross Correlation Function[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of X series[/C][C]0.3[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]1[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]-1.8[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]-0.132004866088583[/C][/ROW]
[ROW][C]-15[/C][C]0.174221623123277[/C][/ROW]
[ROW][C]-14[/C][C]-0.233081448459481[/C][/ROW]
[ROW][C]-13[/C][C]-0.249864299092885[/C][/ROW]
[ROW][C]-12[/C][C]0.592648862740482[/C][/ROW]
[ROW][C]-11[/C][C]-0.117939176513765[/C][/ROW]
[ROW][C]-10[/C][C]-0.361138332194136[/C][/ROW]
[ROW][C]-9[/C][C]0.327760396066963[/C][/ROW]
[ROW][C]-8[/C][C]-0.139891314554085[/C][/ROW]
[ROW][C]-7[/C][C]-0.164379206687980[/C][/ROW]
[ROW][C]-6[/C][C]0.390671094260933[/C][/ROW]
[ROW][C]-5[/C][C]-0.075562426409541[/C][/ROW]
[ROW][C]-4[/C][C]-0.196073719537936[/C][/ROW]
[ROW][C]-3[/C][C]0.369247545654746[/C][/ROW]
[ROW][C]-2[/C][C]-0.440067754561784[/C][/ROW]
[ROW][C]-1[/C][C]-0.329496313129651[/C][/ROW]
[ROW][C]0[/C][C]0.827754368208874[/C][/ROW]
[ROW][C]1[/C][C]-0.203332206996330[/C][/ROW]
[ROW][C]2[/C][C]-0.401001955163751[/C][/ROW]
[ROW][C]3[/C][C]0.435038177868258[/C][/ROW]
[ROW][C]4[/C][C]-0.233664726674106[/C][/ROW]
[ROW][C]5[/C][C]-0.179194596166811[/C][/ROW]
[ROW][C]6[/C][C]0.455751910076626[/C][/ROW]
[ROW][C]7[/C][C]-0.181241705405038[/C][/ROW]
[ROW][C]8[/C][C]-0.086813910961025[/C][/ROW]
[ROW][C]9[/C][C]0.326690870105137[/C][/ROW]
[ROW][C]10[/C][C]-0.45569157757879[/C][/ROW]
[ROW][C]11[/C][C]-0.205841353358516[/C][/ROW]
[ROW][C]12[/C][C]0.673252798815437[/C][/ROW]
[ROW][C]13[/C][C]-0.216480276052021[/C][/ROW]
[ROW][C]14[/C][C]-0.218376674386249[/C][/ROW]
[ROW][C]15[/C][C]0.287049574254554[/C][/ROW]
[ROW][C]16[/C][C]-0.243639193380135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28362&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28362&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:

Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0.3
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series-1.8
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-16-0.132004866088583
-150.174221623123277
-14-0.233081448459481
-13-0.249864299092885
-120.592648862740482
-11-0.117939176513765
-10-0.361138332194136
-90.327760396066963
-8-0.139891314554085
-7-0.164379206687980
-60.390671094260933
-5-0.075562426409541
-4-0.196073719537936
-30.369247545654746
-2-0.440067754561784
-1-0.329496313129651
00.827754368208874
1-0.203332206996330
2-0.401001955163751
30.435038177868258
4-0.233664726674106
5-0.179194596166811
60.455751910076626
7-0.181241705405038
8-0.086813910961025
90.326690870105137
10-0.45569157757879
11-0.205841353358516
120.673252798815437
13-0.216480276052021
14-0.218376674386249
150.287049574254554
16-0.243639193380135


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.3 ; par2 = 0 ; par3 = 1 ; par4 = 1 ; par5 = -1.8 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = 0.3 ; par2 = 0 ; par3 = 1 ; par4 = 1 ; par5 = -1.8 ; par6 = 0 ; par7 = 1 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) y <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',xlab='Lag (k)'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Cross Correlation Function',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE)
a<-table.element(a,par7)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'k',header=TRUE)
a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE)
a<-table.row.end(a)
mylength <- length(r$acf)
myhalf <- floor((mylength-1)/2)
for (i in 1:mylength) {
a<-table.row.start(a)
a<-table.element(a,i-myhalf-1,header=TRUE)
a<-table.element(a,r$acf[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')