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Tijdsreeks A - stap 21

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Fri, 06 Aug 2010 11:49:45 +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/Aug/06/t1281095369el3ei6fmd48vvzb.htm/, Retrieved Fri, 06 Aug 2010 13:49:31 +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/Aug/06/t1281095369el3ei6fmd48vvzb.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:

Gosselin Claudia

Dataseries X:

» Textbox « » Textfile « » CSV «

155 154 153 151 171 170 155 145 146 146 147 149 146 155 149 140 155 152 137 127 134 125 132 141 133 143 141 132 144 140 130 122 124 119 128 131 121 123 116 109 116 109 103 98 95 83 92 94 76 75 77 68 80 66 69 67 68 64 72 70 55 55 54 55 67 54 57 53 49 47 64 58 38 41 38 41 60 49 53 55 56 52 68 68 41 46 41 47 62 48 53 61 59 46 69 69 42 42 42 50 64 47 51 66 64 49 71 68 39 30 22 33 46 24 27 45 38 18 36 31

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	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.215645	-2.3524	0.010147
2	-0.358829	-3.9144	7.6e-05
3	0.214491	2.3398	0.010479
4	-0.075865	-0.8276	0.204781
5	-0.085278	-0.9303	0.177056
6	0.167345	1.8255	0.035215
7	-0.106078	-1.1572	0.12476
8	-0.081215	-0.886	0.188715
9	0.264091	2.8809	0.002352
10	-0.337512	-3.6818	0.000175
11	-0.193377	-2.1095	0.018499
12	0.774155	8.445	0
13	-0.202812	-2.2124	0.014423
14	-0.243653	-2.6579	0.004471
15	0.13036	1.4221	0.078812
16	-0.105338	-1.1491	0.126409
17	-0.031944	-0.3485	0.364052
18	0.190013	2.0728	0.020175
19	-0.124285	-1.3558	0.088866
20	-0.101822	-1.1107	0.134459
21	0.239997	2.6181	0.004996
22	-0.259695	-2.8329	0.002709
23	-0.149112	-1.6266	0.053232
24	0.589987	6.436	0
25	-0.204392	-2.2297	0.013823
26	-0.140226	-1.5297	0.064374
27	0.084372	0.9204	0.179615
28	-0.132765	-1.4483	0.075082
29	0.006888	0.0751	0.470114
30	0.209277	2.2829	0.012104
31	-0.115846	-1.2637	0.104399
32	-0.126869	-1.384	0.084478
33	0.185046	2.0186	0.022888
34	-0.200031	-2.1821	0.015534
35	-0.1024	-1.1171	0.133112
36	0.410178	4.4745	9e-06
37	-0.195364	-2.1312	0.017566
38	-0.070292	-0.7668	0.22236
39	0.057757	0.6301	0.264934
40	-0.130397	-1.4225	0.078755
41	0.035426	0.3865	0.349925
42	0.204229	2.2279	0.013884
43	-0.126049	-1.375	0.085852
44	-0.096134	-1.0487	0.148222
45	0.148277	1.6175	0.054207
46	-0.159074	-1.7353	0.042639
47	-0.067796	-0.7396	0.230509
48	0.314005	3.4254	0.000422
49	-0.211323	-2.3053	0.011442
50	-0.015911	-0.1736	0.431251
51	0.045829	0.4999	0.309023
52	-0.12086	-1.3184	0.094946
53	0.067312	0.7343	0.232108
54	0.177829	1.9399	0.02738
55	-0.127769	-1.3938	0.082989
56	-0.063501	-0.6927	0.244921
57	0.120254	1.3118	0.096053
58	-0.149921	-1.6354	0.052299
59	-0.008562	-0.0934	0.46287
60	0.235457	2.5685	0.005725

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.215645	-2.3524	0.010147
2	-0.4251	-4.6373	5e-06
3	0.016061	0.1752	0.430606
4	-0.203224	-2.2169	0.014265
5	-0.079286	-0.8649	0.194416
6	0.029266	0.3193	0.375047
7	-0.102971	-1.1233	0.13179
8	-0.069712	-0.7605	0.224238
9	0.16658	1.8172	0.035854
10	-0.342089	-3.7317	0.000146
11	-0.293172	-3.1981	0.000886
12	0.618617	6.7483	0
13	-0.015682	-0.1711	0.432231
14	0.233687	2.5492	0.006034
15	-0.123441	-1.3466	0.090337
16	-0.040955	-0.4468	0.327929
17	0.001854	0.0202	0.491949
18	0.025834	0.2818	0.389285
19	0.039082	0.4263	0.335319
20	-0.053633	-0.5851	0.279805
21	-0.133393	-1.4551	0.074131
22	0.07914	0.8633	0.194849
23	-0.034901	-0.3807	0.352042
24	0.07775	0.8482	0.199028
25	-0.074444	-0.8121	0.20918
26	0.015325	0.1672	0.433759
27	-0.026289	-0.2868	0.387392
28	-0.027212	-0.2969	0.383549
29	0.030515	0.3329	0.369904
30	0.022019	0.2402	0.405294
31	0.019206	0.2095	0.417202
32	-0.028232	-0.308	0.379319
33	-0.091361	-0.9966	0.160483
34	-0.007315	-0.0798	0.468266
35	-0.067593	-0.7374	0.231179
36	-0.127479	-1.3906	0.083467
37	-0.039912	-0.4354	0.332035
38	-0.135227	-1.4751	0.071407
39	-0.016992	-0.1854	0.426633
40	-0.049488	-0.5399	0.295153
41	0.022745	0.2481	0.402234
42	-0.001777	-0.0194	0.492282
43	-0.103284	-1.1267	0.13107
44	0.072138	0.7869	0.216443
45	-0.001243	-0.0136	0.494602
46	0.02747	0.2997	0.382477
47	-0.019358	-0.2112	0.416559
48	0.003081	0.0336	0.486622
49	-0.105496	-1.1508	0.126056
50	0.014517	0.1584	0.43722
51	-0.077523	-0.8457	0.199717
52	0.02122	0.2315	0.40867
53	-0.042356	-0.4621	0.322444
54	-0.008274	-0.0903	0.464117
55	-0.017137	-0.1869	0.426014
56	0.019825	0.2163	0.414577
57	0.003145	0.0343	0.486344
58	-0.017052	-0.186	0.426375
59	0.056039	0.6113	0.271078
60	-0.03065	-0.3344	0.36935

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281095369el3ei6fmd48vvzb/1me7f1281095384.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281095369el3ei6fmd48vvzb/1me7f1281095384.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281095369el3ei6fmd48vvzb/2me7f1281095384.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281095369el3ei6fmd48vvzb/2me7f1281095384.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; 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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