Home » date » 2010 » Dec » 05 »

Ws 9 - ACF (d = D = 1)

*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: Sun, 05 Dec 2010 14:15:47 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/05/t12915584492awvr7z77y34wad.htm/, Retrieved Sun, 05 Dec 2010 15:14:09 +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/2010/Dec/05/t12915584492awvr7z77y34wad.htm/},
    year = {2010},
}
@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 = {2010},
    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 «
167.16 179.84 174.44 180.35 193.17 195.16 202.43 189.91 195.98 212.09 205.81 204.31 196.07 199.98 199.10 198.31 195.72 223.04 238.41 259.73 326.54 335.15 321.81 368.62 369.59 425.00 439.72 362.23 328.76 348.55 328.18 329.34 295.55 237.38 226.85 220.14 239.36 224.69 230.98 233.47 256.70 253.41 224.95 210.37 191.09 198.85 211.04 206.25 201.51 194.54 191.07 192.82 181.88 157.67 195.82 246.25 271.69 270.29
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3262322.18840.016935
20.0267610.17950.429169
30.032680.21920.413734
4-0.013486-0.09050.464158
50.3004182.01530.024937
60.1357840.91090.183609
7-0.32291-2.16610.017818
8-0.226171-1.51720.068105
9-0.060232-0.4040.344047
10-0.014244-0.09560.46215
110.0220230.14770.441606
12-0.408123-2.73780.004414
13-0.324703-2.17820.017336
14-0.030806-0.20670.418608
150.123140.8260.206568
160.1771481.18830.120466
17-0.060111-0.40320.344342
18-0.196673-1.31930.096867
190.031430.21080.416983
200.1736831.16510.125058
210.0280850.18840.425705
22-0.049634-0.3330.370357
23-0.159915-1.07270.144553
24-0.11274-0.75630.226711
250.0430670.28890.386991
260.0054440.03650.485514
27-0.116659-0.78260.218988
28-0.089475-0.60020.275687
29-0.022096-0.14820.441414
300.0456430.30620.380438
310.0713210.47840.317329
320.0045430.03050.487912
33-0.027241-0.18270.427911
340.0220270.14780.441596
350.0710730.47680.317917
360.0733940.49230.312436
370.050790.34070.367455
380.0073960.04960.480325
39-0.004093-0.02750.489108
40-0.014102-0.09460.462525
41-0.008115-0.05440.478413
42-0.005454-0.03660.485489
43-0.006475-0.04340.482774
440.0013780.00920.496334
45NANANA
46NANANA
47NANANA
48NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3262322.18840.016935
2-0.089155-0.59810.276396
30.0589490.39540.347193
4-0.04704-0.31560.376901
50.3657672.45360.009039
6-0.129451-0.86840.194896
7-0.388471-2.60590.006189
8-0.01275-0.08550.466111
90.1206410.80930.211304
10-0.117751-0.78990.216866
11-0.09004-0.6040.274435
12-0.316465-2.12290.019648
130.1213310.81390.20999
14-0.037988-0.25480.400007
150.1567451.05150.149327
160.0298960.20060.420977
170.0137480.09220.463464
18-0.115246-0.77310.221754
19-0.058782-0.39430.347604
20-0.013963-0.09370.462895
21-0.159667-1.07110.144923
22-0.022535-0.15120.440258
230.0588790.3950.347364
24-0.247468-1.66010.051928
25-0.123781-0.83030.205363
260.0319060.2140.415744
270.1136840.76260.224837
280.0226480.15190.439961
29-0.00071-0.00480.498111
30-0.035535-0.23840.406335
31-0.123537-0.82870.205822
320.0302390.20280.420084
33-0.061126-0.410.34186
34-0.045574-0.30570.380614
35-0.0339-0.22740.410569
36-0.049321-0.33090.371144
37-0.004861-0.03260.487066
38-0.046836-0.31420.377417
39-0.024635-0.16530.434742
400.0334050.22410.411852
410.0400930.26890.394599
42-0.051948-0.34850.364553
43-0.079253-0.53160.298793
440.0600370.40270.344522
45NANANA
46NANANA
47NANANA
48NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/05/t12915584492awvr7z77y34wad/140ww1291558543.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/05/t12915584492awvr7z77y34wad/140ww1291558543.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/05/t12915584492awvr7z77y34wad/240ww1291558543.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/05/t12915584492awvr7z77y34wad/240ww1291558543.ps (open in new window)


 
Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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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