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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationTue, 02 Dec 2008 08:13:56 -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/2008/Dec/02/t1228231051adahx72ak5g8itv.htm/, Retrieved Fri, 17 May 2024 01:42:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27935, Retrieved Fri, 17 May 2024 01:42:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Non Stationary Ti...] [2008-12-02 15:13:56] [b72e060d4eaf5aae1831b15bc791ef7e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,3
101
113,2
101
105,7
113,9
86,4
96,5
103,3
114,9
105,8
94,2
98,4
99,4
108,8
112,6
104,4
112,2
81,1
97,1
112,6
113,8
107,8
103,2
103,3
101,2
107,7
110,4
101,9
115,9
89,9
88,6
117,2
123,9
100
103,6
94,1
98,7
119,5
112,7
104,4
124,7
89,1
97
121,6
118,8
114
111,5
97,2
102,5
113,4
109,8
104,9
126,1
80
96,8
117,2
112,3
117,3
111,1
102,2
104,3
122,9
107,6
121,3
131,5
89
104,4
128,9
135,9
133,3
121,3
120,5
120,4
137,9
126,1
133,2
151,1
105
119
140,4
156,6
137,1
122,7
Dataseries Y:
Download CSV
Histogram 
93,5
94,7
112,9
99,2
105,6
113
83,1
81,1
96,9
104,3
97,7
102,6
89,9
96
112,7
107,1
106,2
121
101,2
83,2
105,1
113,3
99,1
100,3
93,5
98,8
106,2
98,3
102,1
117,1
101,5
80,5
105,9
109,5
97,2
114,5
93,5
100,9
121,1
116,5
109,3
118,1
108,3
105,4
116,2
111,2
105,8
122,7
99,5
107,9
124,6
115
110,3
132,7
99,7
96,5
118,7
112,9
130,5
137,9
115
116,8
140,9
120,7
134,2
147,3
112,4
107,1
128,4
137,7
135
151
137,4
132,4
161,3
139,8
146
166,5
143,3
121
152,6
154,4
154,6
158

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27935&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27935&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27935&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'George Udny Yule' @ 72.249.76.132






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-16-0.0117022464224267
-150.113455471199060
-140.0720744652025885
-130.269737849580410
-120.420083385945470
-110.111398482738580
-100.079170491684424
-90.323785912444826
-80.251074646293997
-70.368817192829972
-60.589555033571056
-50.323917383181546
-40.299918786084032
-30.442136287547846
-20.401617340268327
-10.634651733750375
00.821575855124338
10.377991255656903
20.296242445197188
30.523634060147097
40.40453330128483
50.487954006218868
60.619375475764131
70.341392960966621
80.279297593614509
90.334121485779114
100.235745042564731
110.392306977154499
120.503641962008964
130.132917825350671
140.0504420950213798
150.223271793932359
160.145615041692912

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \tabularnewline
Seasonal Period (s) & 1 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & -0.0117022464224267 \tabularnewline
-15 & 0.113455471199060 \tabularnewline
-14 & 0.0720744652025885 \tabularnewline
-13 & 0.269737849580410 \tabularnewline
-12 & 0.420083385945470 \tabularnewline
-11 & 0.111398482738580 \tabularnewline
-10 & 0.079170491684424 \tabularnewline
-9 & 0.323785912444826 \tabularnewline
-8 & 0.251074646293997 \tabularnewline
-7 & 0.368817192829972 \tabularnewline
-6 & 0.589555033571056 \tabularnewline
-5 & 0.323917383181546 \tabularnewline
-4 & 0.299918786084032 \tabularnewline
-3 & 0.442136287547846 \tabularnewline
-2 & 0.401617340268327 \tabularnewline
-1 & 0.634651733750375 \tabularnewline
0 & 0.821575855124338 \tabularnewline
1 & 0.377991255656903 \tabularnewline
2 & 0.296242445197188 \tabularnewline
3 & 0.523634060147097 \tabularnewline
4 & 0.40453330128483 \tabularnewline
5 & 0.487954006218868 \tabularnewline
6 & 0.619375475764131 \tabularnewline
7 & 0.341392960966621 \tabularnewline
8 & 0.279297593614509 \tabularnewline
9 & 0.334121485779114 \tabularnewline
10 & 0.235745042564731 \tabularnewline
11 & 0.392306977154499 \tabularnewline
12 & 0.503641962008964 \tabularnewline
13 & 0.132917825350671 \tabularnewline
14 & 0.0504420950213798 \tabularnewline
15 & 0.223271793932359 \tabularnewline
16 & 0.145615041692912 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27935&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]1[/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]0[/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[/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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]-0.0117022464224267[/C][/ROW]
[ROW][C]-15[/C][C]0.113455471199060[/C][/ROW]
[ROW][C]-14[/C][C]0.0720744652025885[/C][/ROW]
[ROW][C]-13[/C][C]0.269737849580410[/C][/ROW]
[ROW][C]-12[/C][C]0.420083385945470[/C][/ROW]
[ROW][C]-11[/C][C]0.111398482738580[/C][/ROW]
[ROW][C]-10[/C][C]0.079170491684424[/C][/ROW]
[ROW][C]-9[/C][C]0.323785912444826[/C][/ROW]
[ROW][C]-8[/C][C]0.251074646293997[/C][/ROW]
[ROW][C]-7[/C][C]0.368817192829972[/C][/ROW]
[ROW][C]-6[/C][C]0.589555033571056[/C][/ROW]
[ROW][C]-5[/C][C]0.323917383181546[/C][/ROW]
[ROW][C]-4[/C][C]0.299918786084032[/C][/ROW]
[ROW][C]-3[/C][C]0.442136287547846[/C][/ROW]
[ROW][C]-2[/C][C]0.401617340268327[/C][/ROW]
[ROW][C]-1[/C][C]0.634651733750375[/C][/ROW]
[ROW][C]0[/C][C]0.821575855124338[/C][/ROW]
[ROW][C]1[/C][C]0.377991255656903[/C][/ROW]
[ROW][C]2[/C][C]0.296242445197188[/C][/ROW]
[ROW][C]3[/C][C]0.523634060147097[/C][/ROW]
[ROW][C]4[/C][C]0.40453330128483[/C][/ROW]
[ROW][C]5[/C][C]0.487954006218868[/C][/ROW]
[ROW][C]6[/C][C]0.619375475764131[/C][/ROW]
[ROW][C]7[/C][C]0.341392960966621[/C][/ROW]
[ROW][C]8[/C][C]0.279297593614509[/C][/ROW]
[ROW][C]9[/C][C]0.334121485779114[/C][/ROW]
[ROW][C]10[/C][C]0.235745042564731[/C][/ROW]
[ROW][C]11[/C][C]0.392306977154499[/C][/ROW]
[ROW][C]12[/C][C]0.503641962008964[/C][/ROW]
[ROW][C]13[/C][C]0.132917825350671[/C][/ROW]
[ROW][C]14[/C][C]0.0504420950213798[/C][/ROW]
[ROW][C]15[/C][C]0.223271793932359[/C][/ROW]
[ROW][C]16[/C][C]0.145615041692912[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27935&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27935&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 series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-16-0.0117022464224267
-150.113455471199060
-140.0720744652025885
-130.269737849580410
-120.420083385945470
-110.111398482738580
-100.079170491684424
-90.323785912444826
-80.251074646293997
-70.368817192829972
-60.589555033571056
-50.323917383181546
-40.299918786084032
-30.442136287547846
-20.401617340268327
-10.634651733750375
00.821575855124338
10.377991255656903
20.296242445197188
30.523634060147097
40.40453330128483
50.487954006218868
60.619375475764131
70.341392960966621
80.279297593614509
90.334121485779114
100.235745042564731
110.392306977154499
120.503641962008964
130.132917825350671
140.0504420950213798
150.223271793932359
160.145615041692912


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
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')