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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 computationThu, 09 Dec 2010 09:25:48 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/09/t1291886613pdxrdjzjsm50kn3.htm/, Retrieved Sun, 28 Apr 2024 23:55:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107144, Retrieved Sun, 28 Apr 2024 23:55:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact264

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Ws4 part 1.1 s090...] [2009-10-27 21:56:53] [e0fc65a5811681d807296d590d5b45de]
-  M D    [Bivariate Explorative Data Analysis] [Paper; bivariate ...] [2009-12-19 19:10:37] [e0fc65a5811681d807296d590d5b45de]
- RMPD      [Cross Correlation Function] [cross correlation...] [2010-12-08 19:50:23] [74be16979710d4c4e7c6647856088456]
-   PD          [Cross Correlation Function] [] [2010-12-09 09:25:48] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- R P             [Cross Correlation Function] [PAPER DMA Cross C...] [2010-12-09 19:56:08] [2099aacba481f75a7f949aa310cab952]
-   P               [Cross Correlation Function] [Paper DMA Cross C...] [2010-12-15 17:50:43] [2099aacba481f75a7f949aa310cab952]
- RMPD            [Variance Reduction Matrix] [PAPER DMA Varianc...] [2010-12-09 20:08:14] [2099aacba481f75a7f949aa310cab952]
- RMPD            [Variance Reduction Matrix] [PAPER DMA VRM Olie] [2010-12-09 20:10:17] [2099aacba481f75a7f949aa310cab952]
-   PD            [Cross Correlation Function] [Cross validation ...] [2010-12-10 08:46:08] [aeb27d5c05332f2e597ad139ee63fbe4]
- RMPD              [Kendall tau Correlation Matrix] [WS10 Feedback Pea...] [2010-12-22 16:18:54] [abf4ff90b26c6b37be4a30063b404639]
- RMPD              [Kendall tau Correlation Matrix] [WS10 Feedback Ken...] [2010-12-22 16:20:27] [abf4ff90b26c6b37be4a30063b404639]
- RMPD              [Recursive Partitioning (Regression Trees)] [WS10 Feedback Rec...] [2010-12-22 16:40:24] [abf4ff90b26c6b37be4a30063b404639]
- R  D            [Cross Correlation Function] [Paper/ Cross Corr...] [2010-12-10 14:13:23] [d59201e34006b7e3f71c33fa566f42b3]
- R  D            [Cross Correlation Function] [CCF ] [2010-12-11 10:57:31] [04d4386fa51dbd2ef12d0f1f80644886]
-    D            [Cross Correlation Function] [Cross Correlation...] [2010-12-11 15:22:29] [62f7c80c4d96454bbd2b2b026ea9aad9]
- R  D            [Cross Correlation Function] [workshop 10] [2010-12-12 13:50:13] [717f3d787904f94c39256c5c1fc72d4c]
- R PD            [Cross Correlation Function] [CCF ] [2010-12-14 17:49:20] [04d4386fa51dbd2ef12d0f1f80644886]
- RMPD              [(Partial) Autocorrelation Function] [ACF aanvoerwaarde] [2010-12-16 11:01:16] [04d4386fa51dbd2ef12d0f1f80644886]
-   PD              [Cross Correlation Function] [CCF aanvoer en aa...] [2010-12-16 10:58:21] [04d4386fa51dbd2ef12d0f1f80644886]
-    D            [Cross Correlation Function] [] [2010-12-19 19:09:45] [de55ccbf69577500a5f46ed42a101114]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3030.29
2803.47
2767.63
2882.6
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.1
2995.55
2833.18
2848.96
2794.83
2845.26
2915.03
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
Dataseries Y:
Download CSV
Histogram 
25.64
27.97
27.62
23.31
29.07
29.58
28.63
29.92
32.68
31.54
32.43
26.54
25.85
27.6
25.71
25.38
28.57
27.64
25.36
25.9
26.29
21.74
19.2
19.32
19.82
20.36
24.31
25.97
25.61
24.67
25.59
26.09
28.37
27.34
24.46
27.46
30.23
32.33
29.87
24.87
25.48
27.28
28.24
29.58
26.95
29.08
28.76
29.59
30.7
30.52
32.67
33.19
37.13
35.54
37.75
41.84
42.94
49.14
44.61
40.22
44.23
45.85
53.38
53.26
51.8
55.3
57.81
63.96
63.77
59.15
56.12
57.42
63.52
61.71
63.01
68.18
72.03
69.75
74.41
74.33
64.24
60.03
59.44
62.5
55.04
58.34
61.92
67.65
67.68
70.3
75.26
71.44
76.36
81.71
92.6
90.6
92.23
94.09
102.79
109.65
124.05
132.69
135.81
116.07
101.42
75.73
55.48
43.8
45.29

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107144&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107144&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107144&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'RServer@AstonUniversity' @ vre.aston.ac.uk






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])
-170.510551338276896
-160.552685313139875
-150.590852201350441
-140.625125145301863
-130.652534391644605
-120.674918216886265
-110.693777567578099
-100.708378819310337
-90.719553843543682
-80.72208106593207
-70.723179061932862
-60.721918018956564
-50.719190631210772
-40.711318207072968
-30.699600949652282
-20.683129333034759
-10.656713223898862
00.615794096477654
10.564879524093758
20.506881082324737
30.450718846592548
40.408738362503416
50.388045317076134
60.380015532117937
70.385462116784928
80.395667343958972
90.404221090572123
100.406297602609595
110.40527112636616
120.400710506234783
130.397159029076456
140.395406528435647
150.391057941837555
160.38531464715224
170.376246609532751

\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 & 0.510551338276896 \tabularnewline
-16 & 0.552685313139875 \tabularnewline
-15 & 0.590852201350441 \tabularnewline
-14 & 0.625125145301863 \tabularnewline
-13 & 0.652534391644605 \tabularnewline
-12 & 0.674918216886265 \tabularnewline
-11 & 0.693777567578099 \tabularnewline
-10 & 0.708378819310337 \tabularnewline
-9 & 0.719553843543682 \tabularnewline
-8 & 0.72208106593207 \tabularnewline
-7 & 0.723179061932862 \tabularnewline
-6 & 0.721918018956564 \tabularnewline
-5 & 0.719190631210772 \tabularnewline
-4 & 0.711318207072968 \tabularnewline
-3 & 0.699600949652282 \tabularnewline
-2 & 0.683129333034759 \tabularnewline
-1 & 0.656713223898862 \tabularnewline
0 & 0.615794096477654 \tabularnewline
1 & 0.564879524093758 \tabularnewline
2 & 0.506881082324737 \tabularnewline
3 & 0.450718846592548 \tabularnewline
4 & 0.408738362503416 \tabularnewline
5 & 0.388045317076134 \tabularnewline
6 & 0.380015532117937 \tabularnewline
7 & 0.385462116784928 \tabularnewline
8 & 0.395667343958972 \tabularnewline
9 & 0.404221090572123 \tabularnewline
10 & 0.406297602609595 \tabularnewline
11 & 0.40527112636616 \tabularnewline
12 & 0.400710506234783 \tabularnewline
13 & 0.397159029076456 \tabularnewline
14 & 0.395406528435647 \tabularnewline
15 & 0.391057941837555 \tabularnewline
16 & 0.38531464715224 \tabularnewline
17 & 0.376246609532751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107144&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]0.510551338276896[/C][/ROW]
[ROW][C]-16[/C][C]0.552685313139875[/C][/ROW]
[ROW][C]-15[/C][C]0.590852201350441[/C][/ROW]
[ROW][C]-14[/C][C]0.625125145301863[/C][/ROW]
[ROW][C]-13[/C][C]0.652534391644605[/C][/ROW]
[ROW][C]-12[/C][C]0.674918216886265[/C][/ROW]
[ROW][C]-11[/C][C]0.693777567578099[/C][/ROW]
[ROW][C]-10[/C][C]0.708378819310337[/C][/ROW]
[ROW][C]-9[/C][C]0.719553843543682[/C][/ROW]
[ROW][C]-8[/C][C]0.72208106593207[/C][/ROW]
[ROW][C]-7[/C][C]0.723179061932862[/C][/ROW]
[ROW][C]-6[/C][C]0.721918018956564[/C][/ROW]
[ROW][C]-5[/C][C]0.719190631210772[/C][/ROW]
[ROW][C]-4[/C][C]0.711318207072968[/C][/ROW]
[ROW][C]-3[/C][C]0.699600949652282[/C][/ROW]
[ROW][C]-2[/C][C]0.683129333034759[/C][/ROW]
[ROW][C]-1[/C][C]0.656713223898862[/C][/ROW]
[ROW][C]0[/C][C]0.615794096477654[/C][/ROW]
[ROW][C]1[/C][C]0.564879524093758[/C][/ROW]
[ROW][C]2[/C][C]0.506881082324737[/C][/ROW]
[ROW][C]3[/C][C]0.450718846592548[/C][/ROW]
[ROW][C]4[/C][C]0.408738362503416[/C][/ROW]
[ROW][C]5[/C][C]0.388045317076134[/C][/ROW]
[ROW][C]6[/C][C]0.380015532117937[/C][/ROW]
[ROW][C]7[/C][C]0.385462116784928[/C][/ROW]
[ROW][C]8[/C][C]0.395667343958972[/C][/ROW]
[ROW][C]9[/C][C]0.404221090572123[/C][/ROW]
[ROW][C]10[/C][C]0.406297602609595[/C][/ROW]
[ROW][C]11[/C][C]0.40527112636616[/C][/ROW]
[ROW][C]12[/C][C]0.400710506234783[/C][/ROW]
[ROW][C]13[/C][C]0.397159029076456[/C][/ROW]
[ROW][C]14[/C][C]0.395406528435647[/C][/ROW]
[ROW][C]15[/C][C]0.391057941837555[/C][/ROW]
[ROW][C]16[/C][C]0.38531464715224[/C][/ROW]
[ROW][C]17[/C][C]0.376246609532751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107144&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107144&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])
-170.510551338276896
-160.552685313139875
-150.590852201350441
-140.625125145301863
-130.652534391644605
-120.674918216886265
-110.693777567578099
-100.708378819310337
-90.719553843543682
-80.72208106593207
-70.723179061932862
-60.721918018956564
-50.719190631210772
-40.711318207072968
-30.699600949652282
-20.683129333034759
-10.656713223898862
00.615794096477654
10.564879524093758
20.506881082324737
30.450718846592548
40.408738362503416
50.388045317076134
60.380015532117937
70.385462116784928
80.395667343958972
90.404221090572123
100.406297602609595
110.40527112636616
120.400710506234783
130.397159029076456
140.395406528435647
150.391057941837555
160.38531464715224
170.376246609532751


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')