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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 computationSun, 30 Nov 2008 15:18:34 -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/Nov/30/t1228083549jgnx183tye15p60.htm/, Retrieved Mon, 20 May 2024 10:31:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26768, Retrieved Mon, 20 May 2024 10:31:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:40:39] [b98453cac15ba1066b407e146608df68]
- RMPD    [Cross Correlation Function] [Non Stationary Ti...] [2008-11-30 22:18:34] [7957bb37a64ed417bbed8444b0b0ea8a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2173
2363
2126
1905
2121
1983
1734
2074
2049
2406
2558
2251
2059
2397
1747
1707
2319
1631
1627
1791
2034
1997
2169
2028
2253
2218
1855
2187
1852
1570
1851
1954
1828
2251
2277
2085
2282
2266
1878
2267
2069
1746
2299
2360
2214
2825
2355
2333
3016
2155
2172
2150
2533
2058
2160
2259
2498
2695
2799
2945
2930
2318
2540
2570
2669
2450
2842
3439
2677
2979
2257
2842
2546
2455
2293
2379
2478
2054
2272
2351
2271
2542
2304
2194
2722
2395
2146
1894
2548
2087
2063
2481
2476
2212
2834
2148
2598
Dataseries Y:
Download CSV
Histogram 
2752
2373
1415
2466
2318
2346
1644
1421
1423
1930
2694
4938
1727
1899
1364
1992
2051
2082
1746
1271
1363
1664
2179
2305
2098
2231
1407
1966
2293
2045
1532
1333
1583
1712
2641
2267
2126
2231
1517
2010
2628
2115
1829
1636
1787
2122
2620
2555
2337
2524
1801
2417
2389
2267
2135
1760
1905
2176
2344
2673
2766
2785
2003
2588
2739
2703
2464
1974
2164
2385
2936
2700
2855
2764
1808
2588
2600
2526
2259
1738
1902
2137
2460
2495
2525
2465
1828
2273
2377
2344
2071
1611
1671
2256
1983
1921
2027

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26768&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26768&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26768&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'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 series1
Degree of seasonal differencing (D) of X series1
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 series1
krho(Y[t],X[t+k])
-160.0618185300707765
-150.0281614326032631
-14-0.0735480182168917
-130.0323649115384135
-120.0705332245655604
-11-0.0618340699731118
-10-0.0903311192673164
-90.215924406712974
-8-0.169130156763597
-7-0.0165917329697621
-60.181643024163942
-5-0.243004621204517
-40.186129493528045
-3-0.0555564417093326
-2-0.10640895838926
-10.18141855912619
0-0.0595044371578868
1-0.0531719377306916
20.00574137759465979
30.118922456332185
4-0.21554140708251
50.155606896734494
60.0409087731002311
7-0.163916807838812
80.101331218632969
90.0326358993664420
10-0.124160446255919
110.133882678847388
12-0.0736041754642513
130.0440231478953377
14-0.0402986521387078
15-0.0246265821342323
160.0949215387240538

\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 & 1 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.0618185300707765 \tabularnewline
-15 & 0.0281614326032631 \tabularnewline
-14 & -0.0735480182168917 \tabularnewline
-13 & 0.0323649115384135 \tabularnewline
-12 & 0.0705332245655604 \tabularnewline
-11 & -0.0618340699731118 \tabularnewline
-10 & -0.0903311192673164 \tabularnewline
-9 & 0.215924406712974 \tabularnewline
-8 & -0.169130156763597 \tabularnewline
-7 & -0.0165917329697621 \tabularnewline
-6 & 0.181643024163942 \tabularnewline
-5 & -0.243004621204517 \tabularnewline
-4 & 0.186129493528045 \tabularnewline
-3 & -0.0555564417093326 \tabularnewline
-2 & -0.10640895838926 \tabularnewline
-1 & 0.18141855912619 \tabularnewline
0 & -0.0595044371578868 \tabularnewline
1 & -0.0531719377306916 \tabularnewline
2 & 0.00574137759465979 \tabularnewline
3 & 0.118922456332185 \tabularnewline
4 & -0.21554140708251 \tabularnewline
5 & 0.155606896734494 \tabularnewline
6 & 0.0409087731002311 \tabularnewline
7 & -0.163916807838812 \tabularnewline
8 & 0.101331218632969 \tabularnewline
9 & 0.0326358993664420 \tabularnewline
10 & -0.124160446255919 \tabularnewline
11 & 0.133882678847388 \tabularnewline
12 & -0.0736041754642513 \tabularnewline
13 & 0.0440231478953377 \tabularnewline
14 & -0.0402986521387078 \tabularnewline
15 & -0.0246265821342323 \tabularnewline
16 & 0.0949215387240538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26768&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]1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]0.0618185300707765[/C][/ROW]
[ROW][C]-15[/C][C]0.0281614326032631[/C][/ROW]
[ROW][C]-14[/C][C]-0.0735480182168917[/C][/ROW]
[ROW][C]-13[/C][C]0.0323649115384135[/C][/ROW]
[ROW][C]-12[/C][C]0.0705332245655604[/C][/ROW]
[ROW][C]-11[/C][C]-0.0618340699731118[/C][/ROW]
[ROW][C]-10[/C][C]-0.0903311192673164[/C][/ROW]
[ROW][C]-9[/C][C]0.215924406712974[/C][/ROW]
[ROW][C]-8[/C][C]-0.169130156763597[/C][/ROW]
[ROW][C]-7[/C][C]-0.0165917329697621[/C][/ROW]
[ROW][C]-6[/C][C]0.181643024163942[/C][/ROW]
[ROW][C]-5[/C][C]-0.243004621204517[/C][/ROW]
[ROW][C]-4[/C][C]0.186129493528045[/C][/ROW]
[ROW][C]-3[/C][C]-0.0555564417093326[/C][/ROW]
[ROW][C]-2[/C][C]-0.10640895838926[/C][/ROW]
[ROW][C]-1[/C][C]0.18141855912619[/C][/ROW]
[ROW][C]0[/C][C]-0.0595044371578868[/C][/ROW]
[ROW][C]1[/C][C]-0.0531719377306916[/C][/ROW]
[ROW][C]2[/C][C]0.00574137759465979[/C][/ROW]
[ROW][C]3[/C][C]0.118922456332185[/C][/ROW]
[ROW][C]4[/C][C]-0.21554140708251[/C][/ROW]
[ROW][C]5[/C][C]0.155606896734494[/C][/ROW]
[ROW][C]6[/C][C]0.0409087731002311[/C][/ROW]
[ROW][C]7[/C][C]-0.163916807838812[/C][/ROW]
[ROW][C]8[/C][C]0.101331218632969[/C][/ROW]
[ROW][C]9[/C][C]0.0326358993664420[/C][/ROW]
[ROW][C]10[/C][C]-0.124160446255919[/C][/ROW]
[ROW][C]11[/C][C]0.133882678847388[/C][/ROW]
[ROW][C]12[/C][C]-0.0736041754642513[/C][/ROW]
[ROW][C]13[/C][C]0.0440231478953377[/C][/ROW]
[ROW][C]14[/C][C]-0.0402986521387078[/C][/ROW]
[ROW][C]15[/C][C]-0.0246265821342323[/C][/ROW]
[ROW][C]16[/C][C]0.0949215387240538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26768&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26768&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 series1
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 series1
krho(Y[t],X[t+k])
-160.0618185300707765
-150.0281614326032631
-14-0.0735480182168917
-130.0323649115384135
-120.0705332245655604
-11-0.0618340699731118
-10-0.0903311192673164
-90.215924406712974
-8-0.169130156763597
-7-0.0165917329697621
-60.181643024163942
-5-0.243004621204517
-40.186129493528045
-3-0.0555564417093326
-2-0.10640895838926
-10.18141855912619
0-0.0595044371578868
1-0.0531719377306916
20.00574137759465979
30.118922456332185
4-0.21554140708251
50.155606896734494
60.0409087731002311
7-0.163916807838812
80.101331218632969
90.0326358993664420
10-0.124160446255919
110.133882678847388
12-0.0736041754642513
130.0440231478953377
14-0.0402986521387078
15-0.0246265821342323
160.0949215387240538


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 2 ; par5 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 1 ; par6 = 1 ; 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) 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')