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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSat, 24 Nov 2007 19:38:22 -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/2007/Nov/25/t11959577780qm74riu12n60ws.htm/, Retrieved Sat, 04 May 2024 08:59:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6379, Retrieved Sat, 04 May 2024 08:59:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact225
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [WS10Q2FINSIT] [2007-11-24 18:03:18] [6b20c0ed55154a4fb9df5a5e4fa0b426]
- RMPD    [Cross Correlation Function] [WS10Q5ZONDER DIFF] [2007-11-25 02:38:22] [e0964b90cb3acfe235da067e79729c23] [Current]
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Dataseries X:
22
27
24
24
22
23
25
23
21
21
22
20
22
22
20
21
20
21
21
21
19
21
21
22
19
24
22
22
22
24
22
23
24
21
20
22
23
23
22
20
21
21
20
20
17
18
19
19
20
21
20
21
19
22
20
18
16
17
18
19
Dataseries Y:
2529
2196
3202
2718
2728
2354
2697
2651
2067
2641
2539
2294
2712
2314
3092
2677
2813
2668
2939
2617
2231
2481
2421
2408
2560
2100
3315
2801
2403
3024
2507
2980
2211
2471
2594
2452
2232
2373
3127
2802
2641
2787
2619
2806
2193
2323
2529
2412
2262
2154
3230
2295
2715
2733
2317
2730
1913
2390
2484
1960




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

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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=6379&T=0

[TABLE]
[ROW][C]Summary of compuational 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=6379&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6379&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

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 series0.8
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series0
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 series0
krho(Y[t],X[t+k])
-140.163836150159792
-130.210059697473169
-120.197983714731124
-110.119917367735499
-100.0465996985205035
-90.112992208242562
-80.0313954387588195
-7-0.0938100086597455
-6-0.00344984206397549
-5-0.0149739290627079
-40.134124444380226
-30.125909636611306
-20.226246523382633
-10.37929632115464
00.192779796595279
10.146772047110428
2-0.00417938568486774
30.151740249836177
4-0.0662877774290374
5-0.108100641167133
6-0.120783306042374
7-0.00447138069005909
80.059252123147986
90.0831584312198996
100.144107414232115
110.214470591378432
120.0642068710328209
130.0258213120367760
14-0.0202337739473857

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0.8 \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) & 12 \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 & 0.163836150159792 \tabularnewline
-13 & 0.210059697473169 \tabularnewline
-12 & 0.197983714731124 \tabularnewline
-11 & 0.119917367735499 \tabularnewline
-10 & 0.0465996985205035 \tabularnewline
-9 & 0.112992208242562 \tabularnewline
-8 & 0.0313954387588195 \tabularnewline
-7 & -0.0938100086597455 \tabularnewline
-6 & -0.00344984206397549 \tabularnewline
-5 & -0.0149739290627079 \tabularnewline
-4 & 0.134124444380226 \tabularnewline
-3 & 0.125909636611306 \tabularnewline
-2 & 0.226246523382633 \tabularnewline
-1 & 0.37929632115464 \tabularnewline
0 & 0.192779796595279 \tabularnewline
1 & 0.146772047110428 \tabularnewline
2 & -0.00417938568486774 \tabularnewline
3 & 0.151740249836177 \tabularnewline
4 & -0.0662877774290374 \tabularnewline
5 & -0.108100641167133 \tabularnewline
6 & -0.120783306042374 \tabularnewline
7 & -0.00447138069005909 \tabularnewline
8 & 0.059252123147986 \tabularnewline
9 & 0.0831584312198996 \tabularnewline
10 & 0.144107414232115 \tabularnewline
11 & 0.214470591378432 \tabularnewline
12 & 0.0642068710328209 \tabularnewline
13 & 0.0258213120367760 \tabularnewline
14 & -0.0202337739473857 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6379&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]0.8[/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]12[/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]0.163836150159792[/C][/ROW]
[ROW][C]-13[/C][C]0.210059697473169[/C][/ROW]
[ROW][C]-12[/C][C]0.197983714731124[/C][/ROW]
[ROW][C]-11[/C][C]0.119917367735499[/C][/ROW]
[ROW][C]-10[/C][C]0.0465996985205035[/C][/ROW]
[ROW][C]-9[/C][C]0.112992208242562[/C][/ROW]
[ROW][C]-8[/C][C]0.0313954387588195[/C][/ROW]
[ROW][C]-7[/C][C]-0.0938100086597455[/C][/ROW]
[ROW][C]-6[/C][C]-0.00344984206397549[/C][/ROW]
[ROW][C]-5[/C][C]-0.0149739290627079[/C][/ROW]
[ROW][C]-4[/C][C]0.134124444380226[/C][/ROW]
[ROW][C]-3[/C][C]0.125909636611306[/C][/ROW]
[ROW][C]-2[/C][C]0.226246523382633[/C][/ROW]
[ROW][C]-1[/C][C]0.37929632115464[/C][/ROW]
[ROW][C]0[/C][C]0.192779796595279[/C][/ROW]
[ROW][C]1[/C][C]0.146772047110428[/C][/ROW]
[ROW][C]2[/C][C]-0.00417938568486774[/C][/ROW]
[ROW][C]3[/C][C]0.151740249836177[/C][/ROW]
[ROW][C]4[/C][C]-0.0662877774290374[/C][/ROW]
[ROW][C]5[/C][C]-0.108100641167133[/C][/ROW]
[ROW][C]6[/C][C]-0.120783306042374[/C][/ROW]
[ROW][C]7[/C][C]-0.00447138069005909[/C][/ROW]
[ROW][C]8[/C][C]0.059252123147986[/C][/ROW]
[ROW][C]9[/C][C]0.0831584312198996[/C][/ROW]
[ROW][C]10[/C][C]0.144107414232115[/C][/ROW]
[ROW][C]11[/C][C]0.214470591378432[/C][/ROW]
[ROW][C]12[/C][C]0.0642068710328209[/C][/ROW]
[ROW][C]13[/C][C]0.0258213120367760[/C][/ROW]
[ROW][C]14[/C][C]-0.0202337739473857[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6379&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6379&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0.8
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series0
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 series0
krho(Y[t],X[t+k])
-140.163836150159792
-130.210059697473169
-120.197983714731124
-110.119917367735499
-100.0465996985205035
-90.112992208242562
-80.0313954387588195
-7-0.0938100086597455
-6-0.00344984206397549
-5-0.0149739290627079
-40.134124444380226
-30.125909636611306
-20.226246523382633
-10.37929632115464
00.192779796595279
10.146772047110428
2-0.00417938568486774
30.151740249836177
4-0.0662877774290374
5-0.108100641167133
6-0.120783306042374
7-0.00447138069005909
80.059252123147986
90.0831584312198996
100.144107414232115
110.214470591378432
120.0642068710328209
130.0258213120367760
14-0.0202337739473857



Parameters (Session):
par1 = 0.8 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 0.8 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; 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) 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')