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ws8: acf verbetering

*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: Fri, 04 Dec 2009 12:00:06 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/04/t1259953275g2qzoydxyy2uawc.htm/, Retrieved Fri, 04 Dec 2009 20:01:17 +0100

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/2009/Dec/04/t1259953275g2qzoydxyy2uawc.htm/},
    year = {2009},
}
@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 = {2009},
    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:

Dataseries X:

» Textbox « » Textfile « » CSV «

6539 6699 6962 6981 7024 6940 6774 6671 6965 6969 6822 6878 6691 6837 7018 7167 7076 7171 7093 6971 7142 7047 6999 6650 6475 6437 6639 6422 6272 6232 6003 5673 6050 5977 5796 5752 5609 5839 6069 6006 5809 5797 5502 5568 5864 5764 5615 5615 5681 5915 6334 6494 6620 6578 6495 6538 6737 6651 6530 6563

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.941403	7.2921	0
2	0.866809	6.7143	0
3	0.806212	6.2449	0
4	0.74743	5.7896	0
5	0.703624	5.4502	0
6	0.656437	5.0847	2e-06
7	0.559228	4.3318	2.9e-05
8	0.454536	3.5208	0.000414
9	0.378883	2.9348	0.002362
10	0.316079	2.4483	0.008646
11	0.293258	2.2716	0.013356
12	0.255991	1.9829	0.025981
13	0.166381	1.2888	0.101211
14	0.074366	0.576	0.283372
15	0.009734	0.0754	0.470073
16	-0.056243	-0.4357	0.332324
17	-0.097273	-0.7535	0.227056
18	-0.144576	-1.1199	0.133613
19	-0.229479	-1.7775	0.040274
20	-0.308855	-2.3924	0.009944
21	-0.360183	-2.79	0.003528
22	-0.394487	-3.0557	0.001674
23	-0.405659	-3.1422	0.001302
24	-0.413245	-3.201	0.001095
25	-0.456885	-3.539	0.000391
26	-0.480596	-3.7227	0.000219
27	-0.480751	-3.7239	0.000218
28	-0.464969	-3.6016	0.000321
29	-0.427475	-3.3112	0.000788
30	-0.387391	-3.0007	0.00196
31	-0.371843	-2.8803	0.002751
32	-0.348845	-2.7021	0.004473
33	-0.309633	-2.3984	0.009796
34	-0.267416	-2.0714	0.021315
35	-0.21854	-1.6928	0.04784
36	-0.187121	-1.4494	0.076212
37	-0.18099	-1.4019	0.083042
38	-0.179465	-1.3901	0.084813
39	-0.16598	-1.2857	0.101748
40	-0.150893	-1.1688	0.123551
41	-0.125009	-0.9683	0.168387
42	-0.103829	-0.8043	0.212213
43	-0.094695	-0.7335	0.233053
44	-0.082897	-0.6421	0.261622
45	-0.062666	-0.4854	0.314577
46	-0.03463	-0.2682	0.394717
47	-0.002694	-0.0209	0.49171
48	0.023668	0.1833	0.427578
49	0.032038	0.2482	0.402426
50	0.035497	0.275	0.392145
51	0.035434	0.2745	0.392332
52	0.032428	0.2512	0.401266
53	0.030719	0.2379	0.406367
54	0.028252	0.2188	0.413759
55	0.021749	0.1685	0.433391
56	0.013708	0.1062	0.457896
57	0.007578	0.0587	0.476693
58	0.002886	0.0224	0.491118
59	0.000885	0.0069	0.497276
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.941403	7.2921	0
2	-0.170807	-1.3231	0.095416
3	0.105153	0.8145	0.209287
4	-0.056129	-0.4348	0.332644
5	0.122005	0.945	0.174213
6	-0.106554	-0.8254	0.206218
7	-0.441554	-3.4203	0.000565
8	-0.018798	-0.1456	0.442361
9	0.157996	1.2238	0.1129
10	0.01346	0.1043	0.458655
11	0.307581	2.3825	0.01019
12	-0.327009	-2.533	0.006971
13	-0.312743	-2.4225	0.009225
14	0.021517	0.1667	0.434095
15	0.079403	0.6151	0.270422
16	-0.198673	-1.5389	0.064541
17	-0.035834	-0.2776	0.391148
18	-0.114865	-0.8897	0.188579
19	0.073885	0.5723	0.284624
20	0.042291	0.3276	0.372182
21	0.012871	0.0997	0.460458
22	-0.081413	-0.6306	0.265342
23	-0.100074	-0.7752	0.220643
24	0.135356	1.0485	0.149316
25	-0.069478	-0.5382	0.296224
26	0.051829	0.4015	0.344751
27	-0.032736	-0.2536	0.400346
28	0.096755	0.7495	0.228255
29	0.094262	0.7302	0.234069
30	0.084898	0.6576	0.25665
31	0.053584	0.4151	0.33979
32	-0.068973	-0.5343	0.297567
33	-0.115902	-0.8978	0.186448
34	0.052022	0.403	0.344206
35	-0.194408	-1.5059	0.068673
36	-0.093204	-0.722	0.236564
37	-0.019076	-0.1478	0.441514
38	-0.144328	-1.118	0.13402
39	0.041814	0.3239	0.373575
40	0.050132	0.3883	0.349577
41	-0.050215	-0.389	0.349339
42	0.086973	0.6737	0.251548
43	-0.032681	-0.2531	0.400511
44	-0.027806	-0.2154	0.4151
45	-0.117603	-0.9109	0.182984
46	0.008477	0.0657	0.473931
47	0.086181	0.6676	0.253489
48	-0.005588	-0.0433	0.48281
49	0.031822	0.2465	0.403071
50	-0.018562	-0.1438	0.443078
51	-0.028477	-0.2206	0.413085
52	-0.016401	-0.127	0.449665
53	0.023486	0.1819	0.428128
54	-0.020319	-0.1574	0.437734
55	0.044004	0.3409	0.367201
56	0.00175	0.0136	0.494614
57	0.029117	0.2255	0.411162
58	-0.118493	-0.9178	0.181188
59	-0.024963	-0.1934	0.423664
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259953275g2qzoydxyy2uawc/1b0uu1259953204.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259953275g2qzoydxyy2uawc/1b0uu1259953204.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259953275g2qzoydxyy2uawc/2pnyc1259953204.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259953275g2qzoydxyy2uawc/2pnyc1259953204.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; 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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