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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 26 Nov 2007 16:53:00 -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/27/t11961205944wtswyymapzr14k.htm/, Retrieved Sun, 05 May 2024 17:53:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6750, Retrieved Sun, 05 May 2024 17:53:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact202

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Inducing Stationa...] [2007-11-26 23:53:00] [640491d00f3c9cca22cbf779aa38ac16] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.30
97.60
96.40
97.00
96.40
94.70
89.30
85.90
83.30
81.50
85.00
84.80
87.50
89.00
90.00
89.60
87.40
84.80
81.90
81.10
79.10
80.50
88.50
90.90
84.90
80.00
76.50
75.40
73.50
74.30
77.70
77.90
76.70
77.20
86.00
86.90
92.00
101.70
104.50
101.70
100.60
100.30
102.50
101.00
108.60
103.40
106.40
106.60
108.90
110.50
114.00
112.80
109.60
116.00
124.60
129.00
131.50
138.60
138.10
146.30
157.60
158.40
176.30
199.90
210.40
202.60
207.10
202.00
203.40
216.30
207.30
203.50
204.40
203.70
205.70
208.00
209.30
208.70
206.50
204.50
Dataseries Y:
Download CSV
Histogram 
100.70
97.90
96.50
96.60
96.60
95.50
91.80
89.30
87.00
85.90
88.00
87.90
89.20
90.90
91.60
90.20
89.10
87.50
86.30
86.00
84.40
86.10
91.00
92.70
88.00
84.30
82.20
80.80
79.40
80.20
82.20
82.20
81.20
82.10
88.10
88.50
92.10
98.60
100.90
100.60
101.10
102.10
103.60
102.80
108.30
104.00
106.10
106.30
109.00
111.00
113.70
112.70
110.30
114.50
119.30
121.80
125.40
129.70
129.40
134.50
141.20
141.40
152.20
167.70
173.30
168.70
172.60
169.80
172.00
179.40
174.60
172.50
172.60
176.30
178.90
179.60
179.90
180.30
180.90
177.70

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6750&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6750&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6750&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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])
-160.290667926846007
-150.348452608010461
-140.401455019196863
-130.455407204633671
-120.505930465610967
-110.555822773316329
-100.61143399705338
-90.661381591738072
-80.70650630596006
-70.751597604337248
-60.793767570795849
-50.832860265677843
-40.8711503544984
-30.90810222223632
-20.9420082712898
-10.972663069726136
00.997991167946192
10.97052055448084
20.936214790638355
30.900673779887743
40.86250917072187
50.82315581779459
60.782844201607607
70.740046254837308
80.696928545556026
90.653464227723602
100.606360895290632
110.55549095633606
120.509695603722267
130.464418726433781
140.415745046161139
150.368829390640196
160.317938172099804

\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
-16 & 0.290667926846007 \tabularnewline
-15 & 0.348452608010461 \tabularnewline
-14 & 0.401455019196863 \tabularnewline
-13 & 0.455407204633671 \tabularnewline
-12 & 0.505930465610967 \tabularnewline
-11 & 0.555822773316329 \tabularnewline
-10 & 0.61143399705338 \tabularnewline
-9 & 0.661381591738072 \tabularnewline
-8 & 0.70650630596006 \tabularnewline
-7 & 0.751597604337248 \tabularnewline
-6 & 0.793767570795849 \tabularnewline
-5 & 0.832860265677843 \tabularnewline
-4 & 0.8711503544984 \tabularnewline
-3 & 0.90810222223632 \tabularnewline
-2 & 0.9420082712898 \tabularnewline
-1 & 0.972663069726136 \tabularnewline
0 & 0.997991167946192 \tabularnewline
1 & 0.97052055448084 \tabularnewline
2 & 0.936214790638355 \tabularnewline
3 & 0.900673779887743 \tabularnewline
4 & 0.86250917072187 \tabularnewline
5 & 0.82315581779459 \tabularnewline
6 & 0.782844201607607 \tabularnewline
7 & 0.740046254837308 \tabularnewline
8 & 0.696928545556026 \tabularnewline
9 & 0.653464227723602 \tabularnewline
10 & 0.606360895290632 \tabularnewline
11 & 0.55549095633606 \tabularnewline
12 & 0.509695603722267 \tabularnewline
13 & 0.464418726433781 \tabularnewline
14 & 0.415745046161139 \tabularnewline
15 & 0.368829390640196 \tabularnewline
16 & 0.317938172099804 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6750&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]-16[/C][C]0.290667926846007[/C][/ROW]
[ROW][C]-15[/C][C]0.348452608010461[/C][/ROW]
[ROW][C]-14[/C][C]0.401455019196863[/C][/ROW]
[ROW][C]-13[/C][C]0.455407204633671[/C][/ROW]
[ROW][C]-12[/C][C]0.505930465610967[/C][/ROW]
[ROW][C]-11[/C][C]0.555822773316329[/C][/ROW]
[ROW][C]-10[/C][C]0.61143399705338[/C][/ROW]
[ROW][C]-9[/C][C]0.661381591738072[/C][/ROW]
[ROW][C]-8[/C][C]0.70650630596006[/C][/ROW]
[ROW][C]-7[/C][C]0.751597604337248[/C][/ROW]
[ROW][C]-6[/C][C]0.793767570795849[/C][/ROW]
[ROW][C]-5[/C][C]0.832860265677843[/C][/ROW]
[ROW][C]-4[/C][C]0.8711503544984[/C][/ROW]
[ROW][C]-3[/C][C]0.90810222223632[/C][/ROW]
[ROW][C]-2[/C][C]0.9420082712898[/C][/ROW]
[ROW][C]-1[/C][C]0.972663069726136[/C][/ROW]
[ROW][C]0[/C][C]0.997991167946192[/C][/ROW]
[ROW][C]1[/C][C]0.97052055448084[/C][/ROW]
[ROW][C]2[/C][C]0.936214790638355[/C][/ROW]
[ROW][C]3[/C][C]0.900673779887743[/C][/ROW]
[ROW][C]4[/C][C]0.86250917072187[/C][/ROW]
[ROW][C]5[/C][C]0.82315581779459[/C][/ROW]
[ROW][C]6[/C][C]0.782844201607607[/C][/ROW]
[ROW][C]7[/C][C]0.740046254837308[/C][/ROW]
[ROW][C]8[/C][C]0.696928545556026[/C][/ROW]
[ROW][C]9[/C][C]0.653464227723602[/C][/ROW]
[ROW][C]10[/C][C]0.606360895290632[/C][/ROW]
[ROW][C]11[/C][C]0.55549095633606[/C][/ROW]
[ROW][C]12[/C][C]0.509695603722267[/C][/ROW]
[ROW][C]13[/C][C]0.464418726433781[/C][/ROW]
[ROW][C]14[/C][C]0.415745046161139[/C][/ROW]
[ROW][C]15[/C][C]0.368829390640196[/C][/ROW]
[ROW][C]16[/C][C]0.317938172099804[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6750&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6750&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])
-160.290667926846007
-150.348452608010461
-140.401455019196863
-130.455407204633671
-120.505930465610967
-110.555822773316329
-100.61143399705338
-90.661381591738072
-80.70650630596006
-70.751597604337248
-60.793767570795849
-50.832860265677843
-40.8711503544984
-30.90810222223632
-20.9420082712898
-10.972663069726136
00.997991167946192
10.97052055448084
20.936214790638355
30.900673779887743
40.86250917072187
50.82315581779459
60.782844201607607
70.740046254837308
80.696928545556026
90.653464227723602
100.606360895290632
110.55549095633606
120.509695603722267
130.464418726433781
140.415745046161139
150.368829390640196
160.317938172099804


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
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) 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')