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Faillissementen Autocorrelatie 3

*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, 16 Dec 2010 10:03:26 +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/16/t1292493698kre4mbakb7u3smt.htm/, Retrieved Thu, 23 May 2013 23:51:59 +0000

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

System-generated keywords (parent):

t12914691325tfz014xn8ebmtf (pk = 105136)

Estimated Impact

Dataseries X:

» Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability «

Output produced by software:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.511233	-3.9269	0.000114
2	0.088771	0.6819	0.248998
3	-0.115485	-0.8871	0.189325
4	0.055388	0.4254	0.336031
5	-0.042298	-0.3249	0.373203
6	-0.018663	-0.1434	0.443251
7	0.047063	0.3615	0.359508
8	0.019515	0.1499	0.440678
9	-0.060163	-0.4621	0.322847
10	-0.005453	-0.0419	0.483366
11	0.324265	2.4907	0.007791
12	-0.417072	-3.2036	0.001095
13	0.090884	0.6981	0.24393
14	0.02293	0.1761	0.4304
15	0.043843	0.3368	0.368746
16	-0.015105	-0.116	0.454014
17	-0.054574	-0.4192	0.3383
18	0.068767	0.5282	0.299667
19	-0.002083	-0.016	0.493645
20	-0.096202	-0.7389	0.231437
21	0.039032	0.2998	0.382686
22	0.133371	1.0244	0.154905
23	-0.086999	-0.6683	0.253288
24	-0.079588	-0.6113	0.271666
25	0.207528	1.5941	0.058134
26	-0.239412	-1.839	0.035478
27	0.144988	1.1137	0.134968
28	-0.144962	-1.1135	0.13501
29	0.209092	1.6061	0.0568
30	-0.108513	-0.8335	0.203962
31	-0.064239	-0.4934	0.31177
32	0.102969	0.7909	0.21608
33	0.052226	0.4012	0.344878
34	-0.085521	-0.6569	0.256899
35	-0.025547	-0.1962	0.422551
36	0.041965	0.3223	0.374168
37	-0.130913	-1.0056	0.159367
38	0.165808	1.2736	0.1039
39	-0.101437	-0.7791	0.219503
40	0.150742	1.1579	0.12579
41	-0.177953	-1.3669	0.088424
42	0.072972	0.5605	0.288628
43	0.04291	0.3296	0.371436
44	-0.010028	-0.077	0.469433
45	-0.076522	-0.5878	0.279463
46	-0.004938	-0.0379	0.484935
47	0.056508	0.434	0.332918
48	-0.017645	-0.1355	0.446326

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.511233	-3.9269	0.000114
2	-0.233657	-1.7948	0.038908
3	-0.256263	-1.9684	0.026864
4	-0.184354	-1.416	0.081009
5	-0.183561	-1.41	0.0819
6	-0.231754	-1.7801	0.040101
7	-0.172939	-1.3284	0.094586
8	-0.107066	-0.8224	0.207084
9	-0.182652	-1.403	0.082932
10	-0.245783	-1.8879	0.03198
11	0.338065	2.5967	0.005931
12	-0.021801	-0.1675	0.43379
13	-0.192832	-1.4812	0.071941
14	-0.023784	-0.1827	0.427833
15	-0.020807	-0.1598	0.436783
16	-0.018186	-0.1397	0.44469
17	-0.107145	-0.823	0.206912
18	-0.133437	-1.025	0.154785
19	-0.068288	-0.5245	0.300939
20	-0.160527	-1.233	0.111227
21	-0.341173	-2.6206	0.005572
22	-0.228632	-1.7562	0.042126
23	0.182312	1.4004	0.08332
24	-0.153807	-1.1814	0.121089
25	0.066194	0.5084	0.306517
26	-0.102879	-0.7902	0.216279
27	0.00117	0.009	0.49643
28	-0.032504	-0.2497	0.401856
29	0.029384	0.2257	0.411106
30	0.02405	0.1847	0.427035
31	-0.049991	-0.384	0.351185
32	-0.043589	-0.3348	0.369475
33	-0.123506	-0.9487	0.17333
34	0.045326	0.3482	0.364482
35	0.196045	1.5058	0.068721
36	-0.036125	-0.2775	0.391191
37	-0.054987	-0.4224	0.337149
38	0.001272	0.0098	0.496119
39	0.026653	0.2047	0.419245
40	0.009552	0.0734	0.47088
41	-0.055058	-0.4229	0.336951
42	0.083657	0.6426	0.261493
43	0.102689	0.7888	0.216703
44	-0.000785	-0.006	0.497606
45	-0.118126	-0.9073	0.183959
46	-0.006589	-0.0506	0.479903
47	0.116081	0.8916	0.188106
48	-0.028806	-0.2213	0.412826

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/16/t1292493698kre4mbakb7u3smt/1uqyw1292493803.png (opens in new window)

http://www.freestatistics.org/blog/date/2010/Dec/16/t1292493698kre4mbakb7u3smt/1uqyw1292493803.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2010/Dec/16/t1292493698kre4mbakb7u3smt/2mhyh1292493803.png (opens in new window)

http://www.freestatistics.org/blog/date/2010/Dec/16/t1292493698kre4mbakb7u3smt/2mhyh1292493803.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2010/Dec/16/t1292493698kre4mbakb7u3smt/3mhyh1292493803.png (opens in new window)

http://www.freestatistics.org/blog/date/2010/Dec/16/t1292493698kre4mbakb7u3smt/3mhyh1292493803.ps (opens in new window)

Click here to open pdf file.

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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')