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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 04:51:23 -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/t1259063607f4kk3wrh6tkxxdo.htm/, Retrieved Tue, 24 Nov 2009 12:53:30 +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/t1259063607f4kk3wrh6tkxxdo.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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9331617.22820
20.820576.35610
30.724085.60870
40.6910155.35261e-06
50.7059935.46860
60.7225425.59680
70.6944525.37921e-06
80.6247334.83925e-06
90.5354434.14755.4e-05
100.4487063.47570.000477
110.3827182.96450.002172
120.3349262.59430.005947
130.2934832.27330.0133
140.2516471.94930.027972
150.1944951.50660.068586
160.1253650.97110.167704
170.0549260.42550.336012
18-0.000851-0.00660.497382
19-0.039938-0.30940.379062
20-0.065803-0.50970.306064
21-0.098279-0.76130.224741
22-0.146202-1.13250.130971
23-0.19851-1.53770.064696
24-0.240215-1.86070.033845
25-0.260254-2.01590.024146
26-0.267662-2.07330.021223
27-0.283709-2.19760.015924
28-0.311145-2.41010.009515
29-0.342442-2.65250.005103
30-0.358097-2.77380.003687
31-0.347439-2.69120.004605
32-0.335537-2.59910.005874
33-0.342551-2.65340.005092
34-0.364097-2.82030.003247
35-0.386427-2.99330.002002
36-0.390758-3.02680.001819
37-0.366878-2.84180.00306
38-0.329253-2.55040.006665
39-0.298239-2.31020.012168
40-0.291443-2.25750.013814
41-0.302777-2.34530.011168
42-0.317515-2.45950.008407
43-0.318704-2.46870.008214
44-0.296461-2.29640.012581
45-0.254844-1.9740.026495
46-0.206353-1.59840.057603
47-0.170038-1.31710.096406
48-0.161212-1.24870.108304
49-0.17091-1.32390.095285
50-0.183488-1.42130.080204
51-0.168118-1.30220.098907
52-0.124667-0.96570.169043
53-0.066359-0.5140.304565
54-0.02965-0.22970.409564
55-0.029203-0.22620.410905
56-0.046821-0.36270.359061
57-0.057501-0.44540.328817
58-0.045992-0.35630.36145
59-0.021916-0.16980.432885
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9331617.22820
2-0.388664-3.01060.001905
30.2136291.65480.051597
40.3757162.91030.00253
50.0963740.74650.229136
6-0.067195-0.52050.30232
7-0.172593-1.33690.093151
8-0.028539-0.22110.412898
9-0.116522-0.90260.185181
10-0.221484-1.71560.045697
11-0.078106-0.6050.273727
12-0.060839-0.47130.319583
13-0.054581-0.42280.336983
140.0189070.14650.442028
15-0.101844-0.78890.216645
16-0.000618-0.00480.4981
170.0163950.1270.449686
180.0492870.38180.351988
190.0021180.01640.493483
200.0190290.14740.441655
21-0.054203-0.41990.338047
22-0.065764-0.50940.306168
230.0219120.16970.432897
240.0061050.04730.48122
250.0152980.11850.453033
26-0.051409-0.39820.345943
27-0.103728-0.80350.212436
280.0229980.17810.429605
29-0.010594-0.08210.467437
300.0589780.45680.324719
310.1002330.77640.220281
32-0.168539-1.30550.098354
33-0.085685-0.66370.254707
340.0377730.29260.385422
35-0.038004-0.29440.384742
36-0.012361-0.09570.46202
370.0637290.49360.311682
380.0606010.46940.320237
390.0021390.01660.493418
40-0.121807-0.94350.174601
410.0236250.1830.427708
42-0.022132-0.17140.432231
43-0.074595-0.57780.282777
440.0360810.27950.390419
450.0219590.17010.432755
460.0531830.4120.34092
470.0259990.20140.420538
48-0.081091-0.62810.266153
490.0128290.09940.460586
50-0.05315-0.41170.341015
510.0799380.61920.269066
52-0.022615-0.17520.430765
530.0451630.34980.363845
54-0.065176-0.50480.307757
55-0.095947-0.74320.23013
560.0645820.50020.309366
57-0.076607-0.59340.277573
58-0.055146-0.42720.335395
59-0.092267-0.71470.238783
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063607f4kk3wrh6tkxxdo/1xfcq1259063479.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063607f4kk3wrh6tkxxdo/1xfcq1259063479.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063607f4kk3wrh6tkxxdo/2kesp1259063479.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/24/t1259063607f4kk3wrh6tkxxdo/2kesp1259063479.ps (open in new window)


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