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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 computationFri, 19 Dec 2008 08:45:56 -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/19/t12297016062092zhktga28pp1.htm/, Retrieved Wed, 15 May 2024 13:43:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35194, Retrieved Wed, 15 May 2024 13:43:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [ACF PAPER] [2008-12-19 15:11:04] [82d201ca7b4e7cd2c6f885d29b5b6937]
- RMP   [Spectral Analysis] [SPECTRUM PAPER] [2008-12-19 15:18:55] [82d201ca7b4e7cd2c6f885d29b5b6937]
- RMPD      [Cross Correlation Function] [Cross Correlation...] [2008-12-19 15:45:56] [00a0a665d7a07edd2e460056b0c0c354] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2175
2197
2350
2440
2409
2473
2408
2455
2448
2498
2646
2757
2849
2921
2982
3081
3106
3119
3061
3097
3162
3257
3277
3295
3364
3494
3667
3813
3918
3896
3801
3570
3702
3862
3970
4139
4200
4291
4444
4503
4357
4591
4697
4621
4563
4203
4296
4435
4105
4117
3844
3721
3674
3858
3801
3504
3033
3047
2962
2198
2014
Dataseries Y:
Download CSV
Histogram 
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572

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'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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35194&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35194&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35194&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'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)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])
-140.0207810691655898
-130.0705916044273008
-120.102079564465198
-110.0789315556152797
-100.0554211682510222
-90.0754378129894253
-80.0737039371045661
-70.050345893636774
-60.0750569279472323
-50.042079372203017
-40.00818956609740188
-3-0.014818261130663
-2-0.0248912719778722
-10.062522634243433
00.0906885998524437
10.0262453301480550
2-0.0108997911434078
3-0.0492956782402291
4-0.134760230156919
5-0.193968198908737
6-0.171110908667642
7-0.147830137960478
8-0.101089884764486
9-0.0781521414230487
10-0.0172734871273760
110.0779099529707688
120.0150239665124748
130.00302773227014405
140.00917325071018348

\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) & 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 & 0.0207810691655898 \tabularnewline
-13 & 0.0705916044273008 \tabularnewline
-12 & 0.102079564465198 \tabularnewline
-11 & 0.0789315556152797 \tabularnewline
-10 & 0.0554211682510222 \tabularnewline
-9 & 0.0754378129894253 \tabularnewline
-8 & 0.0737039371045661 \tabularnewline
-7 & 0.050345893636774 \tabularnewline
-6 & 0.0750569279472323 \tabularnewline
-5 & 0.042079372203017 \tabularnewline
-4 & 0.00818956609740188 \tabularnewline
-3 & -0.014818261130663 \tabularnewline
-2 & -0.0248912719778722 \tabularnewline
-1 & 0.062522634243433 \tabularnewline
0 & 0.0906885998524437 \tabularnewline
1 & 0.0262453301480550 \tabularnewline
2 & -0.0108997911434078 \tabularnewline
3 & -0.0492956782402291 \tabularnewline
4 & -0.134760230156919 \tabularnewline
5 & -0.193968198908737 \tabularnewline
6 & -0.171110908667642 \tabularnewline
7 & -0.147830137960478 \tabularnewline
8 & -0.101089884764486 \tabularnewline
9 & -0.0781521414230487 \tabularnewline
10 & -0.0172734871273760 \tabularnewline
11 & 0.0779099529707688 \tabularnewline
12 & 0.0150239665124748 \tabularnewline
13 & 0.00302773227014405 \tabularnewline
14 & 0.00917325071018348 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35194&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]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]0.0207810691655898[/C][/ROW]
[ROW][C]-13[/C][C]0.0705916044273008[/C][/ROW]
[ROW][C]-12[/C][C]0.102079564465198[/C][/ROW]
[ROW][C]-11[/C][C]0.0789315556152797[/C][/ROW]
[ROW][C]-10[/C][C]0.0554211682510222[/C][/ROW]
[ROW][C]-9[/C][C]0.0754378129894253[/C][/ROW]
[ROW][C]-8[/C][C]0.0737039371045661[/C][/ROW]
[ROW][C]-7[/C][C]0.050345893636774[/C][/ROW]
[ROW][C]-6[/C][C]0.0750569279472323[/C][/ROW]
[ROW][C]-5[/C][C]0.042079372203017[/C][/ROW]
[ROW][C]-4[/C][C]0.00818956609740188[/C][/ROW]
[ROW][C]-3[/C][C]-0.014818261130663[/C][/ROW]
[ROW][C]-2[/C][C]-0.0248912719778722[/C][/ROW]
[ROW][C]-1[/C][C]0.062522634243433[/C][/ROW]
[ROW][C]0[/C][C]0.0906885998524437[/C][/ROW]
[ROW][C]1[/C][C]0.0262453301480550[/C][/ROW]
[ROW][C]2[/C][C]-0.0108997911434078[/C][/ROW]
[ROW][C]3[/C][C]-0.0492956782402291[/C][/ROW]
[ROW][C]4[/C][C]-0.134760230156919[/C][/ROW]
[ROW][C]5[/C][C]-0.193968198908737[/C][/ROW]
[ROW][C]6[/C][C]-0.171110908667642[/C][/ROW]
[ROW][C]7[/C][C]-0.147830137960478[/C][/ROW]
[ROW][C]8[/C][C]-0.101089884764486[/C][/ROW]
[ROW][C]9[/C][C]-0.0781521414230487[/C][/ROW]
[ROW][C]10[/C][C]-0.0172734871273760[/C][/ROW]
[ROW][C]11[/C][C]0.0779099529707688[/C][/ROW]
[ROW][C]12[/C][C]0.0150239665124748[/C][/ROW]
[ROW][C]13[/C][C]0.00302773227014405[/C][/ROW]
[ROW][C]14[/C][C]0.00917325071018348[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35194&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35194&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)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])
-140.0207810691655898
-130.0705916044273008
-120.102079564465198
-110.0789315556152797
-100.0554211682510222
-90.0754378129894253
-80.0737039371045661
-70.050345893636774
-60.0750569279472323
-50.042079372203017
-40.00818956609740188
-3-0.014818261130663
-2-0.0248912719778722
-10.062522634243433
00.0906885998524437
10.0262453301480550
2-0.0108997911434078
3-0.0492956782402291
4-0.134760230156919
5-0.193968198908737
6-0.171110908667642
7-0.147830137960478
8-0.101089884764486
9-0.0781521414230487
10-0.0172734871273760
110.0779099529707688
120.0150239665124748
130.00302773227014405
140.00917325071018348


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 = 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) 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')