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ACF 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: Thu, 26 Nov 2009 15:15:53 -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/26/t1259274137a3o6diqht2zd056.htm/, Retrieved Thu, 26 Nov 2009 23:22:19 +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/26/t1259274137a3o6diqht2zd056.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 «

96.2 96.8 109.9 88 91.1 106.4 68.6 100.1 108 106 108.6 91.5 99.2 98 96.6 102.8 96.9 110 70.5 101.9 109.6 107.8 113 93.8 108 102.8 116.3 89.2 106.7 112.1 74.2 108.8 111.5 118.8 118.9 97.6 116.4 107.9 121.2 97.9 113.4 117.6 79.6 115.9 115.7 129.1 123.3 96.7 121.2 118.2 102.1 125.4 116.7 121.3 85.3 114.2 124.4 131 118.3 99.6

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	0.061516	0.4765	0.317724
2	0.118556	0.9183	0.18106
3	0.14813	1.1474	0.127883
4	0.048635	0.3767	0.353853
5	0.364919	2.8267	0.003191
6	0.00847	0.0656	0.473952
7	0.298602	2.313	0.012085
8	0.091025	0.7051	0.241746
9	0.053879	0.4173	0.338958
10	0.04778	0.3701	0.356305
11	0.053232	0.4123	0.340782
12	0.618693	4.7924	6e-06
13	-0.001695	-0.0131	0.494784
14	0.013064	0.1012	0.459867
15	0.046882	0.3631	0.358885
16	-0.088081	-0.6823	0.248847
17	0.185023	1.4332	0.078499
18	-0.095749	-0.7417	0.23059
19	0.117024	0.9065	0.184158
20	-0.034478	-0.2671	0.395168
21	-0.040145	-0.311	0.378454
22	-0.113406	-0.8784	0.191604
23	-0.020858	-0.1616	0.436095
24	0.329101	2.5492	0.006686
25	-0.124899	-0.9675	0.168598
26	-0.075416	-0.5842	0.280649
27	-0.096926	-0.7508	0.227859
28	-0.167175	-1.2949	0.100152
29	0.037907	0.2936	0.38503
30	-0.169332	-1.3116	0.097319
31	-0.011338	-0.0878	0.465156
32	-0.110241	-0.8539	0.198272
33	-0.145097	-1.1239	0.132762
34	-0.153179	-1.1865	0.120047
35	-0.114009	-0.8831	0.190351
36	0.161826	1.2535	0.107443
37	-0.17065	-1.3218	0.095618
38	-0.110135	-0.8531	0.198498
39	-0.15717	-1.2174	0.114102
40	-0.173812	-1.3463	0.091628
41	-0.017423	-0.135	0.446547
42	-0.144691	-1.1208	0.133426
43	-0.065027	-0.5037	0.308159
44	-0.073742	-0.5712	0.284998
45	-0.185392	-1.436	0.078092
46	-0.093881	-0.7272	0.234965
47	-0.064013	-0.4958	0.310908
48	0.009752	0.0755	0.470018
49	-0.072598	-0.5623	0.287989
50	-0.077693	-0.6018	0.274785
51	-0.088127	-0.6826	0.248735
52	-0.103488	-0.8016	0.212969
53	-0.034893	-0.2703	0.393938
54	-0.038937	-0.3016	0.381998
55	-0.024526	-0.19	0.424985
56	-0.021661	-0.1678	0.43366
57	-0.033744	-0.2614	0.397346
58	-0.00569	-0.0441	0.482496
59	0.005299	0.041	0.483697
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.061516	0.4765	0.317724
2	0.115208	0.8924	0.187872
3	0.136919	1.0606	0.146568
4	0.022509	0.1744	0.431087
5	0.342372	2.652	0.005111
6	-0.048942	-0.3791	0.352975
7	0.273019	2.1148	0.019305
8	-0.025801	-0.1999	0.421136
9	0.032826	0.2543	0.400079
10	-0.180825	-1.4007	0.083233
11	0.09025	0.6991	0.243603
12	0.529687	4.1029	6.2e-05
13	-0.088148	-0.6828	0.248684
14	-0.183422	-1.4208	0.080278
15	-0.110795	-0.8582	0.197095
16	-0.160063	-1.2398	0.109931
17	-0.149299	-1.1565	0.126037
18	-0.080061	-0.6202	0.268753
19	-0.051839	-0.4015	0.344723
20	-0.11641	-0.9017	0.185409
21	0.124919	0.9676	0.16856
22	-0.098624	-0.7639	0.223948
23	0.05459	0.4229	0.336958
24	0.017856	0.1383	0.445228
25	-0.007861	-0.0609	0.475825
26	-0.077272	-0.5985	0.275864
27	-0.007284	-0.0564	0.477596
28	-0.045462	-0.3521	0.36298
29	-0.019309	-0.1496	0.440805
30	-0.005798	-0.0449	0.482165
31	-0.018372	-0.1423	0.443656
32	-0.038256	-0.2963	0.384
33	-0.051867	-0.4018	0.344645
34	0.02874	0.2226	0.412293
35	-0.091982	-0.7125	0.239462
36	-0.004879	-0.0378	0.484991
37	0.011871	0.092	0.463521
38	0.000944	0.0073	0.497096
39	-0.03459	-0.2679	0.394836
40	0.045602	0.3532	0.362577
41	-0.009644	-0.0747	0.470349
42	0.039607	0.3068	0.38003
43	-0.033549	-0.2599	0.397928
44	0.054125	0.4192	0.338266
45	-0.130823	-1.0134	0.15748
46	0.09958	0.7713	0.221766
47	0.012954	0.1003	0.460205
48	-0.169581	-1.3136	0.096996
49	0.03093	0.2396	0.405736
50	0.086474	0.6698	0.25277
51	0.004981	0.0386	0.484676
52	-0.001458	-0.0113	0.495514
53	-0.019862	-0.1539	0.439122
54	0.000335	0.0026	0.498968
55	-0.009989	-0.0774	0.469293
56	0.043081	0.3337	0.369883
57	0.101548	0.7866	0.217309
58	0.051566	0.3994	0.345497
59	-0.058794	-0.4554	0.325227
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/26/t1259274137a3o6diqht2zd056/1mehs1259273751.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/26/t1259274137a3o6diqht2zd056/1mehs1259273751.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/26/t1259274137a3o6diqht2zd056/208iv1259273751.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/26/t1259274137a3o6diqht2zd056/208iv1259273751.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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