Home » date » 2009 » Nov » 27 »

WS 8 Identifying Integration Processes ACF (2)

*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, 27 Nov 2009 03:57:40 -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/Nov/27/t1259319506rsz15wy9fdvg6q2.htm/, Retrieved Fri, 27 Nov 2009 11:58:28 +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/Nov/27/t1259319506rsz15wy9fdvg6q2.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 «

96.8 114.1 110.3 103.9 101.6 94.6 95.9 104.7 102.8 98.1 113.9 80.9 95.7 113.2 105.9 108.8 102.3 99 100.7 115.5 100.7 109.9 114.6 85.4 100.5 114.8 116.5 112.9 102 106 105.3 118.8 106.1 109.3 117.2 92.5 104.2 112.5 122.4 113.3 100 110.7 112.8 109.8 117.3 109.1 115.9 96 99.8 116.8 115.7 99.4 94.3 91 93.2 103.1 94.1 91.8 102.7 82.6

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	0.184074	1.4258	0.07955
2	-0.00925	-0.0716	0.47156
3	0.113444	0.8787	0.191526
4	0.034011	0.2634	0.396553
5	0.300407	2.3269	0.011681
6	0.297463	2.3041	0.012347
7	0.136523	1.0575	0.147261
8	-0.047156	-0.3653	0.358097
9	-0.107359	-0.8316	0.204467
10	-0.286103	-2.2161	0.015243
11	0.060725	0.4704	0.319896
12	0.437447	3.3884	0.000623
13	-0.098623	-0.7639	0.223952
14	-0.245833	-1.9042	0.03084
15	-0.21719	-1.6823	0.04885
16	-0.104338	-0.8082	0.211085
17	0.062107	0.4811	0.316104
18	0.033826	0.262	0.397103
19	0.002253	0.0175	0.493066
20	-0.166378	-1.2888	0.101214
21	-0.206837	-1.6022	0.057187
22	-0.233455	-1.8083	0.037783
23	-0.02581	-0.1999	0.421109
24	0.247843	1.9198	0.029822
25	-0.111242	-0.8617	0.196148
26	-0.266714	-2.066	0.021579
27	-0.200448	-1.5527	0.062881
28	-0.103646	-0.8028	0.212619
29	0.01724	0.1335	0.447106
30	-0.002119	-0.0164	0.493479
31	-0.029411	-0.2278	0.410281
32	-0.162475	-1.2585	0.106538
33	-0.148473	-1.1501	0.12734
34	-0.118954	-0.9214	0.180263
35	-0.033721	-0.2612	0.397416
36	0.18153	1.4061	0.082422
37	-0.054281	-0.4205	0.337825
38	-0.180832	-1.4007	0.083225
39	-0.055348	-0.4287	0.33483
40	-0.012891	-0.0999	0.460396
41	0.039362	0.3049	0.380751
42	0.102834	0.7965	0.214427
43	0.045518	0.3526	0.362819
44	-0.049254	-0.3815	0.352083
45	0.062774	0.4862	0.314282
46	-0.005394	-0.0418	0.483407
47	0.098273	0.7612	0.224753
48	0.207816	1.6097	0.056353

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.184074	1.4258	0.07955
2	-0.044646	-0.3458	0.365342
3	0.128025	0.9917	0.162669
4	-0.013347	-0.1034	0.459
5	0.321911	2.4935	0.007712
6	0.191343	1.4821	0.071769
7	0.113537	0.8795	0.191332
8	-0.141646	-1.0972	0.138473
9	-0.144951	-1.1228	0.133001
10	-0.4874	-3.7754	0.000184
11	-0.033089	-0.2563	0.399295
12	0.44196	3.4234	0.00056
13	0.002344	0.0182	0.492788
14	-0.149667	-1.1593	0.12546
15	-0.115099	-0.8916	0.188098
16	0.119865	0.9285	0.178442
17	-0.123541	-0.9569	0.171217
18	-0.17887	-1.3855	0.085511
19	0.046701	0.3617	0.359408
20	-0.018559	-0.1438	0.443086
21	-0.008259	-0.064	0.474603
22	0.090149	0.6983	0.243846
23	-0.127836	-0.9902	0.163023
24	-0.078244	-0.6061	0.273376
25	-0.073945	-0.5728	0.284469
26	0.020975	0.1625	0.43574
27	-0.077674	-0.6017	0.274834
28	-0.11799	-0.9139	0.182201
29	0.032216	0.2495	0.401896
30	-0.006013	-0.0466	0.481503
31	-0.038339	-0.297	0.383757
32	-0.055762	-0.4319	0.333671
33	0.004898	0.0379	0.484931
34	0.079946	0.6193	0.269046
35	-0.144616	-1.1202	0.133549
36	-0.088876	-0.6884	0.246917
37	-0.023666	-0.1833	0.427584
38	-0.047701	-0.3695	0.356532
39	0.074524	0.5773	0.282962
40	0.002943	0.0228	0.490943
41	-0.091245	-0.7068	0.241218
42	0.055338	0.4286	0.334857
43	0.072729	0.5634	0.287646
44	0.014166	0.1097	0.456495
45	-0.006005	-0.0465	0.481527
46	-0.078399	-0.6073	0.27298
47	0.105144	0.8144	0.209306
48	-0.100304	-0.777	0.220119

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259319506rsz15wy9fdvg6q2/1jfy41259319458.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259319506rsz15wy9fdvg6q2/1jfy41259319458.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259319506rsz15wy9fdvg6q2/2kc6e1259319458.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/27/t1259319506rsz15wy9fdvg6q2/2kc6e1259319458.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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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