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SHW WS8

*The author of this computation has been verified*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Tue, 24 Nov 2009 04:55:31 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063794gkhkq1wqsjgzn3d.htm/, Retrieved Tue, 24 Nov 2009 12:56:36 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063794gkhkq1wqsjgzn3d.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
8.6 8.5 8.3 7.8 7.8 8 8.6 8.9 8.9 8.6 8.3 8.3 8.3 8.4 8.5 8.4 8.6 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.6 8.4 8.1 8 8 8 8 7.9 7.8 7.8 7.9 8.1 8 7.6 7.3 7 6.8 7 7.1 7.2 7.1 6.9 6.7 6.7 6.6 6.9 7.3 7.5 7.3 7.1 6.9 7.1
 
Output produced by software:


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


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8783116.08510
20.6203894.29824.2e-05
30.3672542.54440.007109
40.2211151.53190.066052
50.2042181.41490.081781
60.2507681.73740.044367
70.2798141.93860.029221
80.2655921.84010.035972
90.2010621.3930.085019
100.1266310.87730.19234
110.0614910.4260.335998
120.0077080.05340.478816
13-0.035563-0.24640.403216
14-0.065084-0.45090.327041
15-0.093197-0.64570.260778
16-0.117227-0.81220.21035
17-0.152849-1.0590.147457
18-0.200813-1.39130.085279
19-0.243286-1.68550.049188
20-0.266566-1.84680.035471
21-0.27999-1.93980.029144
22-0.282997-1.96070.027868
23-0.282671-1.95840.028004
24-0.281266-1.94870.028597
25-0.27911-1.93370.029527
26-0.278034-1.92630.030001
27-0.284044-1.96790.027435
28-0.276444-1.91530.030714
29-0.233648-1.61880.056026
30-0.155985-1.08070.142617
31-0.07405-0.5130.30514
32-0.032334-0.2240.411848
33-0.063122-0.43730.33192
34-0.140041-0.97020.168398
35-0.210859-1.46090.075283
36-0.211331-1.46410.074837
37-0.1217-0.84320.201659
380.0098840.06850.472844
390.1194130.82730.206076
400.166011.15010.12789
410.1510371.04640.150306
420.1102530.76390.224347
430.0674510.46730.321195
440.0340350.23580.407295
450.014040.09730.461457
460.0049330.03420.486438
470.0008010.00550.497798
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8783116.08510
2-0.660814-4.57831.7e-05
30.3315122.29680.013018
40.2071721.43530.078839
50.087940.60930.27261
6-0.139544-0.96680.169247
7-0.02381-0.1650.434835
80.1621451.12340.133434
9-0.195685-1.35570.090763
100.1223150.84740.200482
11-0.193399-1.33990.093293
120.0035560.02460.490224
13-0.04217-0.29220.385711
140.035570.24640.403197
15-0.156292-1.08280.142148
16-0.005525-0.03830.484812
17-0.11883-0.82330.207211
18-0.035662-0.24710.402952
190.0508390.35220.363106
20-0.092744-0.64260.261786
21-0.137529-0.95280.172725
220.0409560.28380.38891
230.0517060.35820.360871
24-0.123859-0.85810.197545
25-0.014098-0.09770.4613
26-0.045349-0.31420.377371
27-0.059409-0.41160.341232
280.1561821.08210.142316
290.1522981.05520.148319
30-0.126302-0.8750.192953
31-0.057639-0.39930.34571
32-0.032398-0.22450.411677
33-0.151509-1.04970.14956
340.0435670.30180.382039
35-0.009509-0.06590.473875
360.0931390.64530.260906
370.0304090.21070.417014
380.007550.05230.47925
39-0.003381-0.02340.490704
40-0.039183-0.27150.393598
410.1319170.91390.182657
42-0.175825-1.21820.11456
43-0.063827-0.44220.330162
44-0.017909-0.12410.450885
45-0.054513-0.37770.353669
46-0.076614-0.53080.299003
47-0.027141-0.1880.42582
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063794gkhkq1wqsjgzn3d/1t3ti1259063730.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063794gkhkq1wqsjgzn3d/1t3ti1259063730.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063794gkhkq1wqsjgzn3d/2zu2q1259063730.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063794gkhkq1wqsjgzn3d/2zu2q1259063730.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
 





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