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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, 17 Dec 2008 14:31:48 -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/17/t1229549523hcss8bi7vn4135o.htm/, Retrieved Mon, 27 May 2024 07:57:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34569, Retrieved Mon, 27 May 2024 07:57:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact252

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Pearson Correlation] [Correlation: inve...] [2008-12-16 19:18:46] [5161246d1ccc1b670cc664d03050f084]
- RMPD  [Univariate Data Series] [] [2008-12-17 14:56:45] [b98453cac15ba1066b407e146608df68]
- RMP     [ARIMA Backward Selection] [] [2008-12-17 19:26:06] [b98453cac15ba1066b407e146608df68]
- RMPD        [Cross Correlation Function] [] [2008-12-17 21:31:48] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.44
0.09
0.2
0.82
0.5
0.2
1
0.47
0.49
0.82
0.39
0.6
0.59
0.72
0.97
0.58
0.27
0.84
0.51
0.13
0.65
0.51
1.06
0.81
0.54
0.85
0.93
0.29
1.01
0.65
0.88
0.45
0.74
1.08
0.27
0.24
0.27
0.25
0.69
0.73
1.04
1.04
0.3
0.59
0.72
0.22
1.12
0.93
0.99
0.56
1
0.57
1
0.97
0.3
0.45
0.73
1.13
0.65
0.64
0.68
0.41
0.98
0.3
0.37
1.12
0.4
0.5
1.23
0.94
1.08
1.12
0.83
1.22
0.55
0.38
1.26
0.49
1.13
1.07
0.86
0.94
0.45
0.66
0.71
0.54
0.9
1.23
0.46
1.33
0.64
0.9
0.5
1.37
0.96
0.62
1.24
1.1
0.86
1.2
0.77
0.67
1.05
1.32
0.6
1.31
1.41
Dataseries Y:
Download CSV
Histogram 
1721
1476
1842
2171
1670
1540
1266
897
1266
1519
1074
1435
1385
1440
1883
1822
1661
1774
1133
1361
1688
2216
2896
1382
1330
1419
1662
2040
2126
1649
1610
1952
2102
1749
2091
3036
2414
2097
2705
2431
4192
3990
2854
1966
2431
2763
2831
2023
2934
2489
3252
3018
3193
3976
2584
2512
2169
2504
1843
1408
2179
3690
2372
2494
3872
2786
2312
1599
3167
3433
2648
1978
1947
3113
2856
3174
3507
4174
2978
4428
2832
2930
3681
3253
1660
2208
3139
3409
3445
2410
3262
2897
2526
3982
4097
3403
3362
2708
3129
3550
2696
2885
2945
3600
3808
3671
4005

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=34569&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=34569&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34569&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])
-170.179796975575060
-160.0409924899478075
-150.117308283073031
-140.115702918521655
-130.124126737926343
-120.214217763238825
-110.154271716595235
-100.172183095286799
-90.243769906674315
-80.258380523475967
-70.305267697130967
-60.22539620121157
-50.216735177388278
-40.219123102714226
-30.218528469649035
-20.203695314281379
-10.287588016981424
00.39298665402065
10.304572970765964
20.184529943738231
30.222676185322090
40.267576715475851
50.183656389806308
60.226145553411551
70.258859810115864
80.24782364247858
90.174308269883179
100.213292154708913
110.220420429880352
120.30550387516025
130.0538228248967192
140.0634087393067413
150.150741377161713
160.184281777348452
170.238886236640485

\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
-17 & 0.179796975575060 \tabularnewline
-16 & 0.0409924899478075 \tabularnewline
-15 & 0.117308283073031 \tabularnewline
-14 & 0.115702918521655 \tabularnewline
-13 & 0.124126737926343 \tabularnewline
-12 & 0.214217763238825 \tabularnewline
-11 & 0.154271716595235 \tabularnewline
-10 & 0.172183095286799 \tabularnewline
-9 & 0.243769906674315 \tabularnewline
-8 & 0.258380523475967 \tabularnewline
-7 & 0.305267697130967 \tabularnewline
-6 & 0.22539620121157 \tabularnewline
-5 & 0.216735177388278 \tabularnewline
-4 & 0.219123102714226 \tabularnewline
-3 & 0.218528469649035 \tabularnewline
-2 & 0.203695314281379 \tabularnewline
-1 & 0.287588016981424 \tabularnewline
0 & 0.39298665402065 \tabularnewline
1 & 0.304572970765964 \tabularnewline
2 & 0.184529943738231 \tabularnewline
3 & 0.222676185322090 \tabularnewline
4 & 0.267576715475851 \tabularnewline
5 & 0.183656389806308 \tabularnewline
6 & 0.226145553411551 \tabularnewline
7 & 0.258859810115864 \tabularnewline
8 & 0.24782364247858 \tabularnewline
9 & 0.174308269883179 \tabularnewline
10 & 0.213292154708913 \tabularnewline
11 & 0.220420429880352 \tabularnewline
12 & 0.30550387516025 \tabularnewline
13 & 0.0538228248967192 \tabularnewline
14 & 0.0634087393067413 \tabularnewline
15 & 0.150741377161713 \tabularnewline
16 & 0.184281777348452 \tabularnewline
17 & 0.238886236640485 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34569&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]-17[/C][C]0.179796975575060[/C][/ROW]
[ROW][C]-16[/C][C]0.0409924899478075[/C][/ROW]
[ROW][C]-15[/C][C]0.117308283073031[/C][/ROW]
[ROW][C]-14[/C][C]0.115702918521655[/C][/ROW]
[ROW][C]-13[/C][C]0.124126737926343[/C][/ROW]
[ROW][C]-12[/C][C]0.214217763238825[/C][/ROW]
[ROW][C]-11[/C][C]0.154271716595235[/C][/ROW]
[ROW][C]-10[/C][C]0.172183095286799[/C][/ROW]
[ROW][C]-9[/C][C]0.243769906674315[/C][/ROW]
[ROW][C]-8[/C][C]0.258380523475967[/C][/ROW]
[ROW][C]-7[/C][C]0.305267697130967[/C][/ROW]
[ROW][C]-6[/C][C]0.22539620121157[/C][/ROW]
[ROW][C]-5[/C][C]0.216735177388278[/C][/ROW]
[ROW][C]-4[/C][C]0.219123102714226[/C][/ROW]
[ROW][C]-3[/C][C]0.218528469649035[/C][/ROW]
[ROW][C]-2[/C][C]0.203695314281379[/C][/ROW]
[ROW][C]-1[/C][C]0.287588016981424[/C][/ROW]
[ROW][C]0[/C][C]0.39298665402065[/C][/ROW]
[ROW][C]1[/C][C]0.304572970765964[/C][/ROW]
[ROW][C]2[/C][C]0.184529943738231[/C][/ROW]
[ROW][C]3[/C][C]0.222676185322090[/C][/ROW]
[ROW][C]4[/C][C]0.267576715475851[/C][/ROW]
[ROW][C]5[/C][C]0.183656389806308[/C][/ROW]
[ROW][C]6[/C][C]0.226145553411551[/C][/ROW]
[ROW][C]7[/C][C]0.258859810115864[/C][/ROW]
[ROW][C]8[/C][C]0.24782364247858[/C][/ROW]
[ROW][C]9[/C][C]0.174308269883179[/C][/ROW]
[ROW][C]10[/C][C]0.213292154708913[/C][/ROW]
[ROW][C]11[/C][C]0.220420429880352[/C][/ROW]
[ROW][C]12[/C][C]0.30550387516025[/C][/ROW]
[ROW][C]13[/C][C]0.0538228248967192[/C][/ROW]
[ROW][C]14[/C][C]0.0634087393067413[/C][/ROW]
[ROW][C]15[/C][C]0.150741377161713[/C][/ROW]
[ROW][C]16[/C][C]0.184281777348452[/C][/ROW]
[ROW][C]17[/C][C]0.238886236640485[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34569&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34569&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])
-170.179796975575060
-160.0409924899478075
-150.117308283073031
-140.115702918521655
-130.124126737926343
-120.214217763238825
-110.154271716595235
-100.172183095286799
-90.243769906674315
-80.258380523475967
-70.305267697130967
-60.22539620121157
-50.216735177388278
-40.219123102714226
-30.218528469649035
-20.203695314281379
-10.287588016981424
00.39298665402065
10.304572970765964
20.184529943738231
30.222676185322090
40.267576715475851
50.183656389806308
60.226145553411551
70.258859810115864
80.24782364247858
90.174308269883179
100.213292154708913
110.220420429880352
120.30550387516025
130.0538228248967192
140.0634087393067413
150.150741377161713
160.184281777348452
170.238886236640485


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')