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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 computationWed, 15 Dec 2010 16:10:46 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/15/t1292429309enuybtjy68xi4nu.htm/, Retrieved Fri, 03 May 2024 14:07:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110522, Retrieved Fri, 03 May 2024 14:07:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

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] [appelen] [2009-12-17 16:17:08] [7773f496f69461f4a67891f0ef752622]
-   PD    [Cross Correlation Function] [cross correlation...] [2010-12-15 16:10:46] [c1f1b5e209adb4577289f490325e36f2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.3031
1.3241
1.2961
1.2865
1.2305
1.2101
1.2125
1.2350
1.2014
1.1992
1.1791
1.1832
1.2159
1.1922
1.2114
1.2614
1.2812
1.2786
1.2772
1.2815
1.2679
1.2765
1.3247
1.3191
1.3029
1.3234
1.3354
1.3651
1.3453
1.3534
1.3706
1.3638
1.4268
1.4485
1.4635
1.4587
1.4876
1.5189
1.5783
1.5633
1.5554
1.5757
1.5593
1.4660
1.4065
1.2759
1.2705
1.3954
1.2793
1.2694
1.3282
1.3230
1.4135
1.4042
1.4253
1.4322
1.4632
1.4713
1.5016
1.4318
Dataseries Y:
Download CSV
Histogram 
0.6923
0.6886
0.6855
0.6745
0.6769
0.6758
0.6896
0.6843
0.6818
0.6774
0.6821
0.6885
0.6829
0.6796
0.6976
0.6924
0.6849
0.6921
0.6839
0.6727
0.6776
0.6692
0.6738
0.6740
0.6635
0.6737
0.6788
0.6828
0.6795
0.6740
0.6744
0.6764
0.6987
0.6967
0.7116
0.7357
0.7455
0.7639
0.7958
0.7864
0.7853
0.7903
0.7866
0.8039
0.7916
0.7903
0.8242
0.9567
0.8850
0.8865
0.9258
0.8948
0.8762
0.8527
0.8536
0.8805
0.9155
0.8961
0.9127
0.8857

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110522&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110522&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110522&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series1
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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-140.128804766491581
-130.0134124169852218
-12-0.116462799207541
-110.0613111780028842
-10-0.065091332769093
-90.313385019168966
-80.143314685987614
-7-0.168923085842182
-60.0979503403068176
-50.0702005256444544
-4-0.12268568372108
-30.125344819109878
-2-0.36174274507029
-1-0.299181913535032
00.54440764716908
1-0.160712049069138
2-0.0771348338335782
30.0596874832070044
4-0.0610941139248156
50.117027688822782
60.009081803860962
7-0.0624235396313726
8-0.103669514322854
90.0456643610569369
10-0.117516283495798
110.0601415313941308
12-0.117594249996284
13-0.120138491233208
14-0.0321124856439378

\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 & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.128804766491581 \tabularnewline
-13 & 0.0134124169852218 \tabularnewline
-12 & -0.116462799207541 \tabularnewline
-11 & 0.0613111780028842 \tabularnewline
-10 & -0.065091332769093 \tabularnewline
-9 & 0.313385019168966 \tabularnewline
-8 & 0.143314685987614 \tabularnewline
-7 & -0.168923085842182 \tabularnewline
-6 & 0.0979503403068176 \tabularnewline
-5 & 0.0702005256444544 \tabularnewline
-4 & -0.12268568372108 \tabularnewline
-3 & 0.125344819109878 \tabularnewline
-2 & -0.36174274507029 \tabularnewline
-1 & -0.299181913535032 \tabularnewline
0 & 0.54440764716908 \tabularnewline
1 & -0.160712049069138 \tabularnewline
2 & -0.0771348338335782 \tabularnewline
3 & 0.0596874832070044 \tabularnewline
4 & -0.0610941139248156 \tabularnewline
5 & 0.117027688822782 \tabularnewline
6 & 0.009081803860962 \tabularnewline
7 & -0.0624235396313726 \tabularnewline
8 & -0.103669514322854 \tabularnewline
9 & 0.0456643610569369 \tabularnewline
10 & -0.117516283495798 \tabularnewline
11 & 0.0601415313941308 \tabularnewline
12 & -0.117594249996284 \tabularnewline
13 & -0.120138491233208 \tabularnewline
14 & -0.0321124856439378 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110522&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]1[/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]1[/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]0.128804766491581[/C][/ROW]
[ROW][C]-13[/C][C]0.0134124169852218[/C][/ROW]
[ROW][C]-12[/C][C]-0.116462799207541[/C][/ROW]
[ROW][C]-11[/C][C]0.0613111780028842[/C][/ROW]
[ROW][C]-10[/C][C]-0.065091332769093[/C][/ROW]
[ROW][C]-9[/C][C]0.313385019168966[/C][/ROW]
[ROW][C]-8[/C][C]0.143314685987614[/C][/ROW]
[ROW][C]-7[/C][C]-0.168923085842182[/C][/ROW]
[ROW][C]-6[/C][C]0.0979503403068176[/C][/ROW]
[ROW][C]-5[/C][C]0.0702005256444544[/C][/ROW]
[ROW][C]-4[/C][C]-0.12268568372108[/C][/ROW]
[ROW][C]-3[/C][C]0.125344819109878[/C][/ROW]
[ROW][C]-2[/C][C]-0.36174274507029[/C][/ROW]
[ROW][C]-1[/C][C]-0.299181913535032[/C][/ROW]
[ROW][C]0[/C][C]0.54440764716908[/C][/ROW]
[ROW][C]1[/C][C]-0.160712049069138[/C][/ROW]
[ROW][C]2[/C][C]-0.0771348338335782[/C][/ROW]
[ROW][C]3[/C][C]0.0596874832070044[/C][/ROW]
[ROW][C]4[/C][C]-0.0610941139248156[/C][/ROW]
[ROW][C]5[/C][C]0.117027688822782[/C][/ROW]
[ROW][C]6[/C][C]0.009081803860962[/C][/ROW]
[ROW][C]7[/C][C]-0.0624235396313726[/C][/ROW]
[ROW][C]8[/C][C]-0.103669514322854[/C][/ROW]
[ROW][C]9[/C][C]0.0456643610569369[/C][/ROW]
[ROW][C]10[/C][C]-0.117516283495798[/C][/ROW]
[ROW][C]11[/C][C]0.0601415313941308[/C][/ROW]
[ROW][C]12[/C][C]-0.117594249996284[/C][/ROW]
[ROW][C]13[/C][C]-0.120138491233208[/C][/ROW]
[ROW][C]14[/C][C]-0.0321124856439378[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110522&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110522&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 series1
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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-140.128804766491581
-130.0134124169852218
-12-0.116462799207541
-110.0613111780028842
-10-0.065091332769093
-90.313385019168966
-80.143314685987614
-7-0.168923085842182
-60.0979503403068176
-50.0702005256444544
-4-0.12268568372108
-30.125344819109878
-2-0.36174274507029
-1-0.299181913535032
00.54440764716908
1-0.160712049069138
2-0.0771348338335782
30.0596874832070044
4-0.0610941139248156
50.117027688822782
60.009081803860962
7-0.0624235396313726
8-0.103669514322854
90.0456643610569369
10-0.117516283495798
110.0601415313941308
12-0.117594249996284
13-0.120138491233208
14-0.0321124856439378


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 1 ; 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')