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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, 09 Dec 2008 06:00:38 -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/09/t1228827684exffi54wd5077dx.htm/, Retrieved Sat, 25 May 2024 15:02:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31354, Retrieved Sat, 25 May 2024 15:02:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152

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] [] [2008-12-09 13:00:38] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
137.0
135.9
138.1
137.1
135.1
139.6
131.8
136.7
128.9
131.3
129.5
129.0
129.8
125.4
128.6
130.2
124.6
123.7
124.4
119.2
124.4
123.1
120.9
120.9
117.8
113.6
113.2
115.9
121.1
107.6
114.7
112.8
112.1
109.8
108.5
102.7
110.6
108.2
112.7
107.9
102.7
108.4
108.4
106.9
108.9
103.7
103.6
111.6
105.5
105.5
101.3
103.8
100.3
108.2
105.6
103.0
100.5
104.3
99.1
91.5
Dataseries Y:
Download CSV
Histogram 
108.9
110.5
111.0
110.7
110.0
111.4
107.7
110.4
110.5
106.4
107.5
108.8
107.1
107.9
107.2
106.3
106.7
105.4
109.4
106.7
105.2
107.0
105.4
106.1
105.8
104.2
102.7
102.7
104.9
102.3
104.0
101.2
102.2
101.4
101.1
97.2
99.7
99.4
98.0
103.1
99.4
100.8
96.4
99.7
100.9
101.3
102.6
105.6
107.2
104.0
108.7
104.9
105.3
105.0
106.1
103.7
102.1
97.2
99.5
102.9

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31354&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31354&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31354&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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])
-140.0920016609373398
-130.154466280366041
-120.194524158733177
-110.250765575947323
-100.259613688177206
-90.329226351978227
-80.37445538564076
-70.440675123195381
-60.480347191079799
-50.509315355950837
-40.534259486315367
-30.622214093599933
-20.656866908576027
-10.711727896362574
00.745586071226967
10.704365965756206
20.689017102751329
30.617232486587064
40.57909946443498
50.53529150338017
60.519751413613349
70.514272369243894
80.496560926570763
90.470128584421902
100.504188160830599
110.42861569619182
120.448966771542577
130.461645997052091
140.451689968516802

\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
-14 & 0.0920016609373398 \tabularnewline
-13 & 0.154466280366041 \tabularnewline
-12 & 0.194524158733177 \tabularnewline
-11 & 0.250765575947323 \tabularnewline
-10 & 0.259613688177206 \tabularnewline
-9 & 0.329226351978227 \tabularnewline
-8 & 0.37445538564076 \tabularnewline
-7 & 0.440675123195381 \tabularnewline
-6 & 0.480347191079799 \tabularnewline
-5 & 0.509315355950837 \tabularnewline
-4 & 0.534259486315367 \tabularnewline
-3 & 0.622214093599933 \tabularnewline
-2 & 0.656866908576027 \tabularnewline
-1 & 0.711727896362574 \tabularnewline
0 & 0.745586071226967 \tabularnewline
1 & 0.704365965756206 \tabularnewline
2 & 0.689017102751329 \tabularnewline
3 & 0.617232486587064 \tabularnewline
4 & 0.57909946443498 \tabularnewline
5 & 0.53529150338017 \tabularnewline
6 & 0.519751413613349 \tabularnewline
7 & 0.514272369243894 \tabularnewline
8 & 0.496560926570763 \tabularnewline
9 & 0.470128584421902 \tabularnewline
10 & 0.504188160830599 \tabularnewline
11 & 0.42861569619182 \tabularnewline
12 & 0.448966771542577 \tabularnewline
13 & 0.461645997052091 \tabularnewline
14 & 0.451689968516802 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31354&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]-14[/C][C]0.0920016609373398[/C][/ROW]
[ROW][C]-13[/C][C]0.154466280366041[/C][/ROW]
[ROW][C]-12[/C][C]0.194524158733177[/C][/ROW]
[ROW][C]-11[/C][C]0.250765575947323[/C][/ROW]
[ROW][C]-10[/C][C]0.259613688177206[/C][/ROW]
[ROW][C]-9[/C][C]0.329226351978227[/C][/ROW]
[ROW][C]-8[/C][C]0.37445538564076[/C][/ROW]
[ROW][C]-7[/C][C]0.440675123195381[/C][/ROW]
[ROW][C]-6[/C][C]0.480347191079799[/C][/ROW]
[ROW][C]-5[/C][C]0.509315355950837[/C][/ROW]
[ROW][C]-4[/C][C]0.534259486315367[/C][/ROW]
[ROW][C]-3[/C][C]0.622214093599933[/C][/ROW]
[ROW][C]-2[/C][C]0.656866908576027[/C][/ROW]
[ROW][C]-1[/C][C]0.711727896362574[/C][/ROW]
[ROW][C]0[/C][C]0.745586071226967[/C][/ROW]
[ROW][C]1[/C][C]0.704365965756206[/C][/ROW]
[ROW][C]2[/C][C]0.689017102751329[/C][/ROW]
[ROW][C]3[/C][C]0.617232486587064[/C][/ROW]
[ROW][C]4[/C][C]0.57909946443498[/C][/ROW]
[ROW][C]5[/C][C]0.53529150338017[/C][/ROW]
[ROW][C]6[/C][C]0.519751413613349[/C][/ROW]
[ROW][C]7[/C][C]0.514272369243894[/C][/ROW]
[ROW][C]8[/C][C]0.496560926570763[/C][/ROW]
[ROW][C]9[/C][C]0.470128584421902[/C][/ROW]
[ROW][C]10[/C][C]0.504188160830599[/C][/ROW]
[ROW][C]11[/C][C]0.42861569619182[/C][/ROW]
[ROW][C]12[/C][C]0.448966771542577[/C][/ROW]
[ROW][C]13[/C][C]0.461645997052091[/C][/ROW]
[ROW][C]14[/C][C]0.451689968516802[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31354&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31354&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])
-140.0920016609373398
-130.154466280366041
-120.194524158733177
-110.250765575947323
-100.259613688177206
-90.329226351978227
-80.37445538564076
-70.440675123195381
-60.480347191079799
-50.509315355950837
-40.534259486315367
-30.622214093599933
-20.656866908576027
-10.711727896362574
00.745586071226967
10.704365965756206
20.689017102751329
30.617232486587064
40.57909946443498
50.53529150338017
60.519751413613349
70.514272369243894
80.496560926570763
90.470128584421902
100.504188160830599
110.42861569619182
120.448966771542577
130.461645997052091
140.451689968516802


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')