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WS 9 Autocorrelatie na d=0 & 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: Sat, 11 Dec 2010 01:58:00 +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/11/t1292032593u8lhpq8zgy97ds6.htm/, Retrieved Thu, 23 May 2013 10:45:40 +0000

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

System-generated keywords (parent):

t129174036030xqf0f6kxecm7a (pk = 106517)

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.316648	-2.4527	0.008551
2	0.190318	1.4742	0.072829
3	0.087479	0.6776	0.250311
4	-0.029326	-0.2272	0.410538
5	0.0762	0.5902	0.278621
6	-0.071919	-0.5571	0.289772
7	-0.176453	-1.3668	0.088394
8	-0.052345	-0.4055	0.343289
9	-0.043459	-0.3366	0.368785
10	-0.229343	-1.7765	0.040361
11	0.180567	1.3987	0.08353
12	-0.426667	-3.3049	0.000803
13	0.112805	0.8738	0.192861
14	-0.002853	-0.0221	0.49122
15	-0.010012	-0.0776	0.469221
16	0.012634	0.0979	0.461183
17	0.06757	0.5234	0.301313
18	0.170223	1.3185	0.096167
19	0.032824	0.2543	0.400084
20	0.032033	0.2481	0.40244
21	0.136064	1.0539	0.148066
22	-0.040764	-0.3158	0.376642
23	0.155522	1.2047	0.116531
24	-0.082881	-0.642	0.261662
25	-0.013864	-0.1074	0.457418
26	0.007819	0.0606	0.475954
27	-0.090578	-0.7016	0.242817
28	0.00922	0.0714	0.47165
29	-0.04318	-0.3345	0.369596
30	-0.197404	-1.5291	0.065749
31	0.064056	0.4962	0.310791
32	0.070366	0.5451	0.293868
33	-0.222102	-1.7204	0.045257
34	0.185405	1.4361	0.078078
35	-0.136896	-1.0604	0.146608
36	0.10523	0.8151	0.209116
37	0.007978	0.0618	0.475464
38	0.004154	0.0322	0.487219
39	0.031219	0.2418	0.404871
40	0.004909	0.038	0.484898
41	-0.013757	-0.1066	0.457745
42	0.074827	0.5796	0.282175
43	-0.034446	-0.2668	0.395263
44	-0.072221	-0.5594	0.288978
45	0.089686	0.6947	0.24496
46	-0.073629	-0.5703	0.285292
47	0.025728	0.1993	0.421356
48	-0.040912	-0.3169	0.37621

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.316648	-2.4527	0.008551
2	0.100087	0.7753	0.220613
3	0.194678	1.508	0.068405
4	0.034243	0.2652	0.395865
5	0.030075	0.233	0.408293
6	-0.07043	-0.5455	0.293699
7	-0.272883	-2.1137	0.019352
8	-0.22221	-1.7212	0.045181
9	-0.03703	-0.2868	0.387614
10	-0.184094	-1.426	0.079527
11	0.150914	1.169	0.123518
12	-0.295596	-2.2897	0.012786
13	-0.176761	-1.3692	0.088022
14	-0.025235	-0.1955	0.422844
15	0.066028	0.5115	0.305455
16	-0.051199	-0.3966	0.346539
17	0.024828	0.1923	0.424073
18	0.206611	1.6004	0.057381
19	-0.024439	-0.1893	0.425247
20	-0.196181	-1.5196	0.06693
21	0.125377	0.9712	0.167682
22	-0.131384	-1.0177	0.156455
23	0.244204	1.8916	0.031687
24	-0.070411	-0.5454	0.293751
25	-0.027725	-0.2148	0.415344
26	0.005305	0.0411	0.483679
27	-0.003511	-0.0272	0.489198
28	0.025105	0.1945	0.423236
29	0.053877	0.4173	0.338962
30	-0.027506	-0.2131	0.416
31	0.054997	0.426	0.335814
32	0.036324	0.2814	0.3897
33	-0.015275	-0.1183	0.453104
34	-0.07445	-0.5767	0.283154
35	0.088937	0.6889	0.24677
36	-0.039483	-0.3058	0.380394
37	-0.082713	-0.6407	0.26208
38	0.052888	0.4097	0.341753
39	-0.03166	-0.2452	0.403553
40	-0.104062	-0.8061	0.211696
41	-0.043039	-0.3334	0.370006
42	-0.012985	-0.1006	0.46011
43	-0.01296	-0.1004	0.460186
44	-0.030405	-0.2355	0.407305
45	-0.006173	-0.0478	0.48101
46	-0.088201	-0.6832	0.248554
47	0.028428	0.2202	0.413229
48	0.032265	0.2499	0.401751

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/11/t1292032593u8lhpq8zgy97ds6/15yip1292032676.png (opens in new window)

http://www.freestatistics.org/blog/date/2010/Dec/11/t1292032593u8lhpq8zgy97ds6/15yip1292032676.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2010/Dec/11/t1292032593u8lhpq8zgy97ds6/25yip1292032676.png (opens in new window)

http://www.freestatistics.org/blog/date/2010/Dec/11/t1292032593u8lhpq8zgy97ds6/25yip1292032676.ps (opens in new window)

Click here to open pdf file.

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; 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')