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R Software Module: rwasp_cross.wasp (opens new window with default values)
Title produced by software: Cross Correlation Function
Date of computation: Wed, 28 Nov 2007 04:56:24 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Nov/28/t1196250425zawyembe8xroygj.htm/, Retrieved Wed, 28 Nov 2007 12:47:07 +0100
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
-313 660 103 463 149 -865 -243 1022 236 -720 171 -576 -19 -5 106 667 -102 -702 -66 604 123 -552 -83 -254 -307 581 -277 700 -89 -245 17 329 167 -237 -727 166 -283 586 63 495 10 -637 287 309 -131 -1165 -94 651 -455 577 134 430 356 -573 9 505 -179 -272 -293 -415 -344 567 117 594 40 -622 254 443 -296 -518 109
 
Dataseries Y:
» Textbox « » Textfile « » CSV «
-426 923 180 546 196 -1115 -272 1270 447 -978 276 -805 -59 -51 243 716 -76 -720 -302 776 205 -722 -90 -383 -523 960 -400 743 37 -210 -120 565 3 -257 -861 85 -387 695 260 635 7 -705 313 251 -176 -1484 -224 846 -728 766 383 354 454 -743 179 274 -324 -266 -476 -568 -415 768 317 964 -72 -664 352 432 -413 -469 39
 
Text written by user:
 
Output produced by software:


Summary of compuational 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 series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-140.138412000499436
-13-0.143657690258127
-120.240946747073797
-11-0.122876275709446
-100.0157665092268943
-90.0797156240972814
-8-0.0785494711233344
-70.0418849079379991
-6-0.0954001783046864
-5-0.0919562133283884
-40.132718457853344
-3-0.103594281320707
-20.116208243252963
-10.228871849286587
0-0.51416965466013
10.140268912457874
20.0761265754347964
30.081653381074945
4-0.0754355732480002
5-0.0410808821569095
6-0.026702558175864
70.0431590146735732
8-0.0527114108777721
90.0280850385608055
100.0175238516672723
110.0462993935383508
12-0.00488379537487765
13-0.0350613029164303
14-0.0135361185560452
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/28/t1196250425zawyembe8xroygj/1uk7k1196250983.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/28/t1196250425zawyembe8xroygj/1uk7k1196250983.ps (open in new window)


 
Parameters:
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; 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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')
 





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