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verb 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: Thu, 03 Dec 2009 10:54:48 -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/Dec/03/t1259862921bvtfq4po8clfj1n.htm/, Retrieved Thu, 03 Dec 2009 18:55:24 +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/Dec/03/t1259862921bvtfq4po8clfj1n.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
10.4609043.54030.000394
2-0.063535-0.4880.313672
3-0.503906-3.87060.000137
4-0.479515-3.68320.000251
5-0.161761-1.24250.109482
60.158121.21450.11469
70.2450871.88250.032348
80.2324951.78580.039633
90.0384780.29560.384304
10-0.090533-0.69540.244769
11-0.151272-1.16190.124969
12-0.05185-0.39830.345935
13-0.081301-0.62450.267357
140.0863920.66360.254769
150.0715220.54940.292413
160.0040240.03090.487724
17-0.045476-0.34930.36405
18-0.096115-0.73830.231637
19-0.015679-0.12040.452276
200.1016650.78090.21899
210.0901360.69240.245717
22-0.000904-0.00690.497243
23-0.13561-1.04160.150914
24-0.224372-1.72340.045024
25-0.120469-0.92530.179279
260.0853470.65560.257327
270.1164210.89420.187411
28-0.001502-0.01150.495417
29-0.092466-0.71020.240175
30-0.103843-0.79760.214141
310.0874680.67190.252149
320.1756511.34920.091214
330.1619191.24370.10926
340.004810.03690.485326
35-0.178043-1.36760.088316
36-0.293688-2.25590.0139
37-0.159561-1.22560.112607
380.0406350.31210.378023
390.2083291.60020.057448
400.2315811.77880.040212
410.1596781.22650.112439
42-0.061222-0.47030.319954
43-0.133124-1.02250.155348
44-0.227506-1.74750.042876
45-0.098998-0.76040.225016
460.0731760.56210.288098
470.245351.88460.032209
480.2417181.85670.034176
490.0958490.73620.232255
50-0.140695-1.08070.142114
51-0.200296-1.53850.064636
52-0.127757-0.98130.165221
530.0488210.3750.354501
540.0640240.49180.312351
550.0591780.45460.325549
56-0.028445-0.21850.413902
57-0.011799-0.09060.464046
58-0.007532-0.05790.477029
59NANANA
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4609043.54030.000394
2-0.350405-2.69150.00462
3-0.438375-3.36720.000671
4-0.082715-0.63530.263831
50.028990.22270.412278
6-0.046555-0.35760.360961
7-0.10993-0.84440.200932
80.1304771.00220.160166
9-0.034701-0.26650.395375
10-0.021801-0.16750.433792
110.005870.04510.482094
120.1075490.82610.206039
13-0.230001-1.76670.041228
140.1952661.49990.069491
15-0.019636-0.15080.440313
16-0.198475-1.52450.066361
170.0459680.35310.362642
18-0.013027-0.10010.460316
190.0258070.19820.421775
200.0068880.05290.478991
210.0305420.23460.407667
22-0.120688-0.9270.178846
23-0.082767-0.63570.263701
24-0.122838-0.94350.174626
250.0466350.35820.360733
26-0.049445-0.37980.352731
27-0.183669-1.41080.081779
28-0.2194-1.68520.048612
29-0.022957-0.17630.430316
300.0316990.24350.404237
310.049470.380.352661
320.028920.22210.412486
330.088030.67620.250787
34-0.059945-0.46040.323444
35-0.106562-0.81850.208177
36-0.095647-0.73470.232723
37-0.0448-0.34410.365992
38-0.043562-0.33460.369556
39-0.052465-0.4030.344205
40-0.034907-0.26810.39477
410.0339920.26110.397463
42-0.101868-0.78250.218535
430.0800520.61490.270497
44-0.048733-0.37430.354752
45-0.046055-0.35380.362393
460.0140730.10810.457142
470.1160920.89170.188083
48-0.014626-0.11230.455465
49-0.080269-0.61660.269948
500.0222960.17130.432304
510.0195680.15030.440518
52-0.107053-0.82230.207111
53-0.02776-0.21320.415942
54-0.056922-0.43720.331772
55-0.049541-0.38050.352459
560.0477720.36690.357487
57-0.008811-0.06770.473136
58-0.07446-0.57190.284768
59NANANA
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259862921bvtfq4po8clfj1n/1p1nu1259862886.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259862921bvtfq4po8clfj1n/1p1nu1259862886.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/03/t1259862921bvtfq4po8clfj1n/2hhug1259862886.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/03/t1259862921bvtfq4po8clfj1n/2hhug1259862886.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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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