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autocorrelate met trend- verkoopcijfers X - Lehaen Joni

*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Thu, 29 Apr 2010 08:12:20 +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/Apr/29/t1272528804aykzptybqnjac89.htm/, Retrieved Thu, 29 Apr 2010 10:13:24 +0200

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/Apr/29/t1272528804aykzptybqnjac89.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:

KDGP2W21

Dataseries X:

» Textbox « » Textfile « » CSV «

154 96 73 49 36 59 95 169 210 278 298 245 200 118 90 79 78 91 167 169 289 347 375 203 223 104 107 85 75 99 135 211 335 460 488 326 346 261 224 141 148 145 223 272 445 560 612 467 518 404 300 210 196 186 247 343 464 680 711 610 613 392 273 322 189 257 324 404 677 858 895 664 628 308 324 248 272

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	1 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.305102	2.6598	0.004766
2	0.30399	2.6501	0.004892
3	-0.100856	-0.8792	0.191021
4	-0.29839	-2.6013	0.005579
5	-0.487021	-4.2458	3e-05
6	-0.386231	-3.3671	0.000597
7	-0.428973	-3.7397	0.000178
8	-0.219159	-1.9106	0.029915
9	0.019508	0.1701	0.432705
10	0.177039	1.5434	0.063445
11	0.37686	3.2854	0.000771
12	0.625291	5.4512	0
13	0.254658	2.2201	0.014698
14	0.186119	1.6226	0.054413
15	-0.043144	-0.3761	0.353938
16	-0.247422	-2.157	0.017084
17	-0.330869	-2.8845	0.002549
18	-0.332563	-2.8992	0.002444
19	-0.316542	-2.7596	0.003625
20	-0.129017	-1.1247	0.132119
21	-0.048485	-0.4227	0.336862
22	0.163694	1.4271	0.07883
23	0.215962	1.8827	0.031783
24	0.481794	4.2002	3.6e-05
25	0.182503	1.591	0.057877
26	0.219916	1.9172	0.029487
27	-0.030176	-0.2631	0.396605
28	-0.131304	-1.1447	0.127967
29	-0.272736	-2.3777	0.009969
30	-0.222004	-1.9354	0.028332
31	-0.25086	-2.1869	0.015911
32	-0.126061	-1.099	0.137625
33	-0.083068	-0.7242	0.235593
34	0.090229	0.7866	0.216981
35	0.136587	1.1907	0.118731
36	0.350851	3.0586	0.001535
37	0.172315	1.5022	0.068594
38	0.167473	1.46	0.074206
39	0.022789	0.1987	0.421526
40	-0.12491	-1.0889	0.13981
41	-0.157705	-1.3748	0.08661
42	-0.167519	-1.4604	0.074151
43	-0.169131	-1.4744	0.072246
44	-0.136576	-1.1906	0.11875
45	-0.059375	-0.5176	0.303114
46	0.042621	0.3716	0.355627
47	0.082331	0.7177	0.237559
48	0.262633	2.2896	0.012411

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.305102	2.6598	0.004766
2	0.23255	2.0273	0.023068
3	-0.283246	-2.4693	0.007892
4	-0.34544	-3.0115	0.001764
5	-0.325442	-2.8371	0.002916
6	-0.097519	-0.8501	0.198957
7	-0.271762	-2.3692	0.010184
8	-0.295808	-2.5788	0.005923
9	-0.097947	-0.8539	0.197926
10	-0.121305	-1.0575	0.146814
11	-0.039995	-0.3487	0.36415
12	0.386042	3.3654	6e-04
13	-0.154921	-1.3506	0.090421
14	-0.229335	-1.9993	0.024576
15	0.129376	1.1279	0.131461
16	0.124465	1.0851	0.140662
17	0.010553	0.092	0.463469
18	-0.10007	-0.8724	0.192871
19	0.031642	0.2758	0.391708
20	0.130732	1.1397	0.128996
21	-0.213954	-1.8652	0.033006
22	0.0331	0.2886	0.386851
23	-0.136631	-1.1911	0.118656
24	0.107413	0.9364	0.176015
25	0.058359	0.5088	0.306196
26	-0.05149	-0.4489	0.327397
27	-0.052801	-0.4603	0.323305
28	0.003088	0.0269	0.489297
29	0.04312	0.3759	0.354016
30	0.133509	1.1639	0.124051
31	-0.072302	-0.6303	0.26519
32	-0.061371	-0.535	0.2971
33	-0.024635	-0.2148	0.415265
34	0.102055	0.8897	0.188219
35	-0.023738	-0.2069	0.418305
36	-0.084878	-0.74	0.230804
37	0.006161	0.0537	0.478652
38	-0.019786	-0.1725	0.431754
39	-0.026363	-0.2298	0.409422
40	-0.093466	-0.8148	0.208861
41	0.016289	0.142	0.443727
42	0.039241	0.3421	0.366611
43	-0.010465	-0.0912	0.463774
44	-0.093513	-0.8152	0.208744
45	0.00537	0.0468	0.481392
46	0.042773	0.3729	0.355135
47	-0.031958	-0.2786	0.390654
48	-0.024434	-0.213	0.415944

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272528804aykzptybqnjac89/17dtt1272528737.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272528804aykzptybqnjac89/17dtt1272528737.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272528804aykzptybqnjac89/2i5sw1272528737.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272528804aykzptybqnjac89/2i5sw1272528737.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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