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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, 16 Dec 2009 05:10:27 -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/2009/Dec/16/t12609654612f98bs9fsbn4dnq.htm/, Retrieved Tue, 30 Apr 2024 14:01:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68256, Retrieved Tue, 30 Apr 2024 14:01:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

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] [cC] [2008-12-16 18:11:49] [c4e82a203a5642d47e013a6c97b9cd86]
-  M      [Cross Correlation Function] [] [2009-12-16 12:10:27] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
358.59
362.96
362.42
364.97
364.04
361.06
358.48
352.96
359.59
360.39
357.40
362.93
364.55
365.73
364.70
364.65
359.43
362.14
356.97
354.82
353.17
357.06
356.18
355.01
355.65
357.31
357.07
357.91
358.48
358.97
351.77
352.16
359.08
360.35
359.53
359.30
358.41
359.68
355.31
357.08
349.71
354.13
345.49
341.69
344.25
340.17
342.47
344.43
333.23
339.72
342.61
346.36
339.09
339.73
341.12
335.94
333.46
335.66
341.12
342.21
342.62
346.06
344.43
346.65
343.74
335.67
342.75
341.77
345.84
346.52
350.79
345.44
345.87
338.48
337.21
340.81
339.86
342.86
343.33
341.73
351.38
351.13
345.99
347.55
346.02
345.29
347.03
348.01
345.48
349.40
351.05
349.70
350.86
354.45
355.30
357.48
355.24
351.79
355.22
351.02
350.28
350.17
348.16
340.30
343.75
344.71
344.13
342.14
345.04
346.02
346.43
347.07
339.33
339.10
337.19
339.58
327.85
326.81
321.73
320.45
327.69
323.95
320.47
322.13
316.34
314.78
308.90
308.62
314.41
306.88
310.60
321.60
321.50
325.68
324.35
320.01
326.88
332.39
331.48
332.62
324.79
327.12
328.91
328.37
324.83
325.90
326.18
328.94
333.78
328.06
325.87
325.41
318.86
319.13
310.16
311.73
306.54
311.16
311.98
306.72
308.05
300.76
301.90
293.09
292.76
294.58
289.90
296.69
297.21
293.31
296.25
298.60
296.87
301.02
304.73
301.92
295.72
293.18
298.35
297.99
299.85
299.85
304.45
299.45
298.14
298.78
297.02
301.33
294.96
296.69
300.73
301.96
297.38
293.87
285.96
285.41
283.70
284.76
277.11
274.73
274.73
274.73
274.73
274.69
275.42
264.15
276.24
268.88
277.97
280.49
281.09
276.16
272.58
270.94
284.31
283.94
284.18
282.83
283.84
282.71
279.29
280.70
274.47
273.44
275.49
279.46
280.19
288.21
284.80
281.41
283.39
287.97
290.77
290.60
289.67
289.84
298.55
296.07
297.14
295.34
296.25
294.30
296.15
296.49
298.05
301.03
300.52
301.50
296.93
289.84
291.44
286.88
286.74
288.93
292.19
295.39
295.86
293.36
292.86
292.73
296.73
285.02
285.24
288.62
283.36
285.84
291.48
291.41
287.77
284.97
286.05
278.19
281.21
277.92
280.08
269.24
268.48
268.83
269.54
262.37
265.12
265.34
263.32
267.18
260.75
261.78
257.27
255.63
251.39
259.49
261.18
261.65
262.01
265.23
268.10
262.27
263.59
257.85
265.69
271.15
266.69
265.77
262.32
270.48
273.03
269.13
280.65
282.75
281.44
281.99
282.86
287.21
283.11
280.66
282.39
280.83
284.71
279.99
283.50
284.88
288.60
284.80
287.20
286.22
286.54
279.58
283.08
288.88
280.18
284.16
290.57
286.82
273.00
278.69
264.54
271.92
283.60
269.25
263.58
264.16
268.85
269.67
249.41
268.99
268.65
260.16
256.55
251.47
234.93
232.96
215.49
213.68
236.07
235.41
214.77
225.85
224.64
238.26
232.44
222.50
225.28
220.49
216.86
234.70
230.06
238.27
238.56
242.70
249.14
234.89
227.78
234.04
230.70
230.17
218.23
232.20
220.76
215.60
217.69
204.35
191.44
203.84
211.86
210.57
219.57
219.98
226.01
207.04
212.52
217.92
210.45
218.53
223.32
218.76
217.63
Dataseries Y:
Download CSV
Histogram 
122.36
123.33
123.04
124.53
125.13
125.85
126.50
126.53
127.07
124.55
124.90
124.32
122.84
123.31
123.31
124.87
124.64
124.73
124.90
124.04
123.28
123.86
122.29
124.09
124.54
125.65
125.70
125.53
125.61
125.55
125.41
127.60
124.68
124.41
126.43
126.38
125.78
124.70
125.07
125.25
126.58
127.13
125.82
123.70
124.39
123.70
124.42
121.05
121.02
123.23
121.32
120.91
120.72
123.31
119.58
119.53
120.59
118.63
118.47
111.81
114.71
117.34
115.77
118.38
117.84
118.83
120.02
116.21
117.08
120.20
119.83
118.92
118.03
117.71
119.55
116.13
115.97
115.99
114.96
116.46
116.55
113.05
117.44
118.84
117.06
117.54
119.31
118.72
121.55
122.61
121.53
123.31
124.07
123.59
122.97
123.22
123.04
122.96
122.81
122.81
122.62
120.82
119.41
121.56
121.59
118.50
118.77
118.86
117.60
119.90
121.83
121.84
122.12
122.12
121.36
119.66
119.32
120.36
117.06
117.48
115.60
113.86
116.92
117.75
117.75
115.31
116.28
115.22
115.65
115.11
118.67
118.04
116.50
119.78
119.95
120.37
119.79
119.43
121.06
121.74
121.09
122.97
120.50
117.18
115.03
113.36
112.59
111.65
111.98
114.87
114.67
114.09
114.77
117.05
117.22
113.18
110.95
112.14
112.72
110.01
110.29
110.74
110.32
105.89
108.97
109.34
106.57
99.49
101.81
104.29
109.73
105.06
107.97
108.13
109.86
108.95
111.20
110.69
106.10
105.68
104.12
104.71
104.30
103.52
107.76
107.80
107.30
108.64
105.03
108.30
107.21
109.27
109.50
111.68
111.80
111.75
106.68
106.37
105.76
109.01
109.01
109.01
109.01
107.69
105.19
105.48
102.22
100.54
105.00
105.44
107.89
108.64
106.70
109.10
105.23
108.41
108.80
110.39
110.22
110.86
108.58
107.70
106.62
109.84
107.16
107.26
108.70
109.85
109.41
112.36
111.03
110.67
109.21
113.58
113.88
114.08
112.33
113.92
114.41
114.57
115.35
113.13
113.29
112.56
113.06
113.46
115.39
116.62
117.04
117.42
115.62
115.16
115.69
112.85
114.05
112.00
113.74
116.26
118.63
116.49
118.23
116.83
118.82
114.36
112.02
113.24
109.75
110.33
112.86
113.04
113.80
110.90
109.96
108.69
108.84
108.47
108.07
107.94
108.11
108.11
106.81
105.58
105.61
106.52
103.86
104.60
104.73
105.12
104.76
103.85
103.83
103.22
101.64
102.13
104.33
104.92
107.78
104.49
102.80
102.86
104.51
104.73
102.58
99.93
101.41
101.05
99.86
101.11
100.89
101.09
98.31
98.08
99.55
99.62
97.37
98.16
97.98
98.15
97.10
97.24
96.70
96.64
100.65
96.75
97.74
97.92
98.34
93.84
97.80
96.20
95.99
95.18
95.95
92.23
91.78
92.97
89.76
92.88
96.23
95.79
93.97
93.90
93.60
93.96
88.69
88.57
85.62
86.25
85.33
83.33
77.78
78.70
72.05
80.75
81.41
82.65
75.85
75.70
78.25
77.41
76.84
74.25
74.95
68.78
73.21
73.26
78.67
75.63
74.99
83.87
79.62
80.13
79.76
78.20
78.05
79.05
73.32
75.17
73.26
73.72
73.57
70.60
71.25
74.22
73.32
73.01
74.21
75.32
71.73
71.94
72.94
72.47
71.94
74.30
74.30

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68256&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68256&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68256&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'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 series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
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])
-220.680119282205235
-210.688246312613417
-200.69981392537782
-190.70981576385908
-180.72072569905561
-170.732746419951042
-160.743283031439858
-150.757130885292122
-140.772335382778188
-130.784783062894511
-120.796654088523095
-110.807022586130934
-100.816697563678369
-90.8268578626822
-80.836428318535638
-70.848448265266254
-60.860056527129005
-50.87071842371361
-40.882500743589803
-30.893138977938219
-20.903337066512838
-10.906348486313418
00.909044788056128
10.899160155998081
20.888579091846268
30.87637088644813
40.865033492012095
50.853344131524164
60.842156116265274
70.82916279092775
80.818606544334944
90.807810288172586
100.794641050327074
110.781924829442681
120.769942997188214
130.757719326426606
140.745918772043617
150.734612805774904
160.722038267514051
170.711216231176876
180.698895761459958
190.686644802744466
200.677417019009611
210.666145515430089
220.655939330025705

\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) & 1 \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
-22 & 0.680119282205235 \tabularnewline
-21 & 0.688246312613417 \tabularnewline
-20 & 0.69981392537782 \tabularnewline
-19 & 0.70981576385908 \tabularnewline
-18 & 0.72072569905561 \tabularnewline
-17 & 0.732746419951042 \tabularnewline
-16 & 0.743283031439858 \tabularnewline
-15 & 0.757130885292122 \tabularnewline
-14 & 0.772335382778188 \tabularnewline
-13 & 0.784783062894511 \tabularnewline
-12 & 0.796654088523095 \tabularnewline
-11 & 0.807022586130934 \tabularnewline
-10 & 0.816697563678369 \tabularnewline
-9 & 0.8268578626822 \tabularnewline
-8 & 0.836428318535638 \tabularnewline
-7 & 0.848448265266254 \tabularnewline
-6 & 0.860056527129005 \tabularnewline
-5 & 0.87071842371361 \tabularnewline
-4 & 0.882500743589803 \tabularnewline
-3 & 0.893138977938219 \tabularnewline
-2 & 0.903337066512838 \tabularnewline
-1 & 0.906348486313418 \tabularnewline
0 & 0.909044788056128 \tabularnewline
1 & 0.899160155998081 \tabularnewline
2 & 0.888579091846268 \tabularnewline
3 & 0.87637088644813 \tabularnewline
4 & 0.865033492012095 \tabularnewline
5 & 0.853344131524164 \tabularnewline
6 & 0.842156116265274 \tabularnewline
7 & 0.82916279092775 \tabularnewline
8 & 0.818606544334944 \tabularnewline
9 & 0.807810288172586 \tabularnewline
10 & 0.794641050327074 \tabularnewline
11 & 0.781924829442681 \tabularnewline
12 & 0.769942997188214 \tabularnewline
13 & 0.757719326426606 \tabularnewline
14 & 0.745918772043617 \tabularnewline
15 & 0.734612805774904 \tabularnewline
16 & 0.722038267514051 \tabularnewline
17 & 0.711216231176876 \tabularnewline
18 & 0.698895761459958 \tabularnewline
19 & 0.686644802744466 \tabularnewline
20 & 0.677417019009611 \tabularnewline
21 & 0.666145515430089 \tabularnewline
22 & 0.655939330025705 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68256&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]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]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]-22[/C][C]0.680119282205235[/C][/ROW]
[ROW][C]-21[/C][C]0.688246312613417[/C][/ROW]
[ROW][C]-20[/C][C]0.69981392537782[/C][/ROW]
[ROW][C]-19[/C][C]0.70981576385908[/C][/ROW]
[ROW][C]-18[/C][C]0.72072569905561[/C][/ROW]
[ROW][C]-17[/C][C]0.732746419951042[/C][/ROW]
[ROW][C]-16[/C][C]0.743283031439858[/C][/ROW]
[ROW][C]-15[/C][C]0.757130885292122[/C][/ROW]
[ROW][C]-14[/C][C]0.772335382778188[/C][/ROW]
[ROW][C]-13[/C][C]0.784783062894511[/C][/ROW]
[ROW][C]-12[/C][C]0.796654088523095[/C][/ROW]
[ROW][C]-11[/C][C]0.807022586130934[/C][/ROW]
[ROW][C]-10[/C][C]0.816697563678369[/C][/ROW]
[ROW][C]-9[/C][C]0.8268578626822[/C][/ROW]
[ROW][C]-8[/C][C]0.836428318535638[/C][/ROW]
[ROW][C]-7[/C][C]0.848448265266254[/C][/ROW]
[ROW][C]-6[/C][C]0.860056527129005[/C][/ROW]
[ROW][C]-5[/C][C]0.87071842371361[/C][/ROW]
[ROW][C]-4[/C][C]0.882500743589803[/C][/ROW]
[ROW][C]-3[/C][C]0.893138977938219[/C][/ROW]
[ROW][C]-2[/C][C]0.903337066512838[/C][/ROW]
[ROW][C]-1[/C][C]0.906348486313418[/C][/ROW]
[ROW][C]0[/C][C]0.909044788056128[/C][/ROW]
[ROW][C]1[/C][C]0.899160155998081[/C][/ROW]
[ROW][C]2[/C][C]0.888579091846268[/C][/ROW]
[ROW][C]3[/C][C]0.87637088644813[/C][/ROW]
[ROW][C]4[/C][C]0.865033492012095[/C][/ROW]
[ROW][C]5[/C][C]0.853344131524164[/C][/ROW]
[ROW][C]6[/C][C]0.842156116265274[/C][/ROW]
[ROW][C]7[/C][C]0.82916279092775[/C][/ROW]
[ROW][C]8[/C][C]0.818606544334944[/C][/ROW]
[ROW][C]9[/C][C]0.807810288172586[/C][/ROW]
[ROW][C]10[/C][C]0.794641050327074[/C][/ROW]
[ROW][C]11[/C][C]0.781924829442681[/C][/ROW]
[ROW][C]12[/C][C]0.769942997188214[/C][/ROW]
[ROW][C]13[/C][C]0.757719326426606[/C][/ROW]
[ROW][C]14[/C][C]0.745918772043617[/C][/ROW]
[ROW][C]15[/C][C]0.734612805774904[/C][/ROW]
[ROW][C]16[/C][C]0.722038267514051[/C][/ROW]
[ROW][C]17[/C][C]0.711216231176876[/C][/ROW]
[ROW][C]18[/C][C]0.698895761459958[/C][/ROW]
[ROW][C]19[/C][C]0.686644802744466[/C][/ROW]
[ROW][C]20[/C][C]0.677417019009611[/C][/ROW]
[ROW][C]21[/C][C]0.666145515430089[/C][/ROW]
[ROW][C]22[/C][C]0.655939330025705[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68256&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68256&T=1

As an alternative you can also use a QR Code:  
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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)1
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])
-220.680119282205235
-210.688246312613417
-200.69981392537782
-190.70981576385908
-180.72072569905561
-170.732746419951042
-160.743283031439858
-150.757130885292122
-140.772335382778188
-130.784783062894511
-120.796654088523095
-110.807022586130934
-100.816697563678369
-90.8268578626822
-80.836428318535638
-70.848448265266254
-60.860056527129005
-50.87071842371361
-40.882500743589803
-30.893138977938219
-20.903337066512838
-10.906348486313418
00.909044788056128
10.899160155998081
20.888579091846268
30.87637088644813
40.865033492012095
50.853344131524164
60.842156116265274
70.82916279092775
80.818606544334944
90.807810288172586
100.794641050327074
110.781924829442681
120.769942997188214
130.757719326426606
140.745918772043617
150.734612805774904
160.722038267514051
170.711216231176876
180.698895761459958
190.686644802744466
200.677417019009611
210.666145515430089
220.655939330025705


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; 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')