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Step 2 ACF eigen tijd reeks na differentiatie

*Unverified author*
R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Tue, 09 Dec 2008 17:28:55 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/10/t1228868985ml1f4eljxqmudtt.htm/, Retrieved Wed, 10 Dec 2008 00:29:47 +0000
 
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/2008/Dec/10/t1228868985ml1f4eljxqmudtt.htm/},
    year = {2008},
}
@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 = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
Feedback Forum:
2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc] [reply] 
test

Post a new message
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
1.1372 1.1139 1.1222 1.1692 1.1702 1.2286 1.2613 1.2646 1.2262 1.1985 1.2007 1.2138 1.2266 1.2176 1.2218 1.249 1.2991 1.3408 1.3119 1.3014 1.3201 1.2938 1.2694 1.2165 1.2037 1.2292 1.2256 1.2015 1.1786 1.1856 1.2103 1.1938 1.202 1.2271 1.277 1.265 1.2684 1.2811 1.2727 1.2611 1.2881 1.3213 1.2999 1.3074 1.3242 1.3516 1.3511 1.3419 1.3716 1.3622 1.3896 1.4227 1.4684 1.457 1.4718 1.4748 1.5527 1.575 1.5557 1.5553 1.577
 
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'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1975541.53020.065606
2-0.149501-1.1580.125721
3-0.100594-0.77920.219464
40.1711671.32590.094957
50.0762750.59080.27843
6-0.139726-1.08230.141722
7-0.132221-1.02420.154931
8-0.02363-0.1830.427692
90.0242580.18790.425792
100.0405060.31380.377396
110.0956430.74080.230839
120.0001119e-040.499659
13-0.042916-0.33240.370363
140.0786870.60950.272244
150.0619940.48020.316416
16-0.025025-0.19380.423477
17-0.059212-0.45870.324069
18-0.035241-0.2730.392903
190.029740.23040.409297
200.0415170.32160.37444
21-0.111108-0.86060.196432
22-0.004285-0.03320.486817
230.0021550.01670.493368
24-0.062831-0.48670.314126
25-0.138993-1.07660.142977
26-0.020801-0.16110.43627
270.0361930.28030.390088
28-0.05717-0.44280.329739
29-0.085381-0.66140.255456
30-0.021557-0.1670.433974
310.0761780.59010.278679
32-0.107776-0.83480.203563
33-0.241859-1.87340.032941
34-0.011423-0.08850.464894
350.075170.58230.281286
360.0329760.25540.399633
37-0.044881-0.34770.36466
38-0.031474-0.24380.404109
390.0201550.15610.438232
400.1212980.93960.175603
410.0328950.25480.399874
42-0.08086-0.62630.266734
43-0.095655-0.74090.230809
44-0.058842-0.45580.325095
450.1152380.89260.18781
460.0394580.30560.380468
47-0.035022-0.27130.393553
48-0.075769-0.58690.279736
490.0353610.27390.39255
500.0346650.26850.394611
510.0770820.59710.276352
52-0.01442-0.11170.455718
530.0215250.16670.43407
540.0234220.18140.428323
55-0.060747-0.47050.319835
56-0.022134-0.17140.432225
570.0345880.26790.394842
580.0062920.04870.480646
59-0.011046-0.08560.46605
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1975541.53020.065606
2-0.196185-1.51960.066927
3-0.028689-0.22220.412448
40.1860041.44080.077423
5-0.030386-0.23540.407363
6-0.117004-0.90630.184198
7-0.038454-0.29790.383419
8-0.050268-0.38940.349189
9-0.019564-0.15150.440027
100.0692630.53650.296796
110.118150.91520.181879
12-0.043528-0.33720.368585
13-0.022447-0.17390.431274
140.0963350.74620.229228
15-0.03872-0.29990.382635
16-0.018813-0.14570.442313
170.0289670.22440.411614
18-0.046035-0.35660.361326
190.013230.10250.459358
200.0556890.43140.333875
21-0.135573-1.05010.148933
220.0672340.52080.302213
23-0.034268-0.26540.395791
24-0.119442-0.92520.179285
25-0.100816-0.78090.218961
260.0353340.27370.392629
27-0.022295-0.17270.431734
28-0.089488-0.69320.245438
290.0073160.05670.4775
30-0.036298-0.28120.389777
31-0.006247-0.04840.480784
32-0.125461-0.97180.167522
33-0.210327-1.62920.054256
340.0518380.40150.344727
350.0127430.09870.460851
360.0097330.07540.470078
370.0354840.27490.392185
38-0.023102-0.17890.429292
39-0.039149-0.30320.381375
400.109090.8450.200732
41-0.019675-0.15240.439692
42-0.100403-0.77770.219897
430.029480.22840.410075
44-0.041303-0.31990.375065
450.0742590.57520.283651
460.0046150.03570.4858
470.0592790.45920.323883
48-0.084888-0.65750.256675
49-0.018239-0.14130.444061
50-0.059718-0.46260.322671
510.0281880.21830.41395
520.0373220.28910.386751
530.0655250.50760.306813
54-0.077707-0.60190.27475
55-0.091057-0.70530.241669
56-0.014007-0.10850.456982
57-0.0468-0.36250.359121
58-0.06134-0.47510.318208
590.0514690.39870.345774
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228868985ml1f4eljxqmudtt/1n36y1228868933.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228868985ml1f4eljxqmudtt/1n36y1228868933.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228868985ml1f4eljxqmudtt/2n9z01228868933.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228868985ml1f4eljxqmudtt/2n9z01228868933.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
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 (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='lags',ylab='ACF')
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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