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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: Sun, 27 Dec 2009 07:10:55 -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/27/t126192309427lm9z56er8pf4m.htm/, Retrieved Sun, 27 Dec 2009 15:11:37 +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/27/t126192309427lm9z56er8pf4m.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 «

2921.44 2981.85 3080.58 3106.22 3119.31 3061.26 3097.31 3161.69 3257.16 3277.01 3295.32 3363.99 3494.17 3667.03 3813.06 3917.96 3895.51 3801.06 3570.12 3701.61 3862.27 3970.1 4138.52 4199.75 4290.89 4443.91 4502.64 4356.98 4591.27 4696.96 4621.4 4562.84 4202.52 4296.49 4435.23 4105.18 4116.68 3844.49 3720.98 3674.4 3857.62 3801.06 3504.37 3032.6 3047.03 2962.34 2197.82 2014.45 1862.83 1905.41 1810.99 1670.07 1864.44 2052.02 2029.6 2070.83 2293.41 2443.27 2513.17 2466.92

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	0.266368	2.046	0.02261
2	0.064166	0.4929	0.311968
3	0.203517	1.5632	0.061672
4	0.196781	1.5115	0.067999
5	0.268308	2.0609	0.021864
6	0.020052	0.154	0.439059
7	-0.026561	-0.204	0.41952
8	0.145837	1.1202	0.133585
9	0.035502	0.2727	0.393019
10	-0.127379	-0.9784	0.165931
11	0.153597	1.1798	0.121407
12	-0.010011	-0.0769	0.469485
13	-0.051774	-0.3977	0.346149
14	0.069318	0.5324	0.29821
15	-0.054372	-0.4176	0.338863
16	0.033286	0.2557	0.399547
17	-0.133338	-1.0242	0.154964
18	-0.186654	-1.4337	0.078466
19	0.015264	0.1172	0.453532
20	-0.096282	-0.7396	0.231252
21	-0.176625	-1.3567	0.090025
22	-0.190431	-1.4627	0.074424
23	-0.174313	-1.3389	0.092865
24	-0.127338	-0.9781	0.166009
25	-0.06477	-0.4975	0.310341
26	-0.114013	-0.8757	0.192359
27	-0.026254	-0.2017	0.420439
28	0.044812	0.3442	0.365958
29	-0.045402	-0.3487	0.364262
30	-0.050796	-0.3902	0.348908
31	-0.084895	-0.6521	0.258438
32	-0.020789	-0.1597	0.436838
33	-0.044852	-0.3445	0.365841
34	-0.085492	-0.6567	0.25697
35	-0.106906	-0.8212	0.207431
36	-0.040974	-0.3147	0.377039
37	-0.005046	-0.0388	0.484607
38	-0.026432	-0.203	0.419905
39	-0.049329	-0.3789	0.353061
40	-0.045881	-0.3524	0.362891
41	0.006715	0.0516	0.479519
42	0.012554	0.0964	0.461753
43	0.021998	0.169	0.433199
44	-0.005728	-0.044	0.482528
45	0.003329	0.0256	0.489845
46	0.010701	0.0822	0.467384
47	0.002142	0.0165	0.493464
48	0.006778	0.0521	0.479328
49	0.01289	0.099	0.460732
50	0.019274	0.148	0.441406
51	0.012979	0.0997	0.460464
52	0.004254	0.0327	0.487023
53	0.004026	0.0309	0.487717
54	0.015945	0.1225	0.451468
55	0.014984	0.1151	0.454379
56	0.007904	0.0607	0.475897
57	0.000525	0.004	0.498398
58	-0.00117	-0.009	0.496429
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.266368	2.046	0.02261
2	-0.007304	-0.0561	0.477724
3	0.202634	1.5565	0.062474
4	0.103109	0.792	0.215768
5	0.217732	1.6724	0.049868
6	-0.144707	-1.1115	0.135427
7	-0.043069	-0.3308	0.370977
8	0.069809	0.5362	0.296914
9	-0.06455	-0.4958	0.310933
10	-0.169403	-1.3012	0.099123
11	0.282075	2.1667	0.017155
12	-0.157217	-1.2076	0.116009
13	-0.009789	-0.0752	0.470158
14	0.108696	0.8349	0.203567
15	-0.050862	-0.3907	0.348722
16	-0.076273	-0.5859	0.280102
17	-0.119823	-0.9204	0.180561
18	-0.064125	-0.4926	0.312078
19	-0.015826	-0.1216	0.45183
20	-0.082601	-0.6345	0.264113
21	0.029784	0.2288	0.409916
22	-0.194617	-1.4949	0.070138
23	-0.016766	-0.1288	0.448985
24	-0.039968	-0.307	0.379962
25	0.038822	0.2982	0.383301
26	0.032948	0.2531	0.400545
27	0.068163	0.5236	0.301271
28	0.112473	0.8639	0.195565
29	-0.000723	-0.0056	0.497795
30	-0.148945	-1.1441	0.128608
31	-0.013782	-0.1059	0.458025
32	-0.054088	-0.4155	0.339657
33	-0.090588	-0.6958	0.244637
34	-0.00324	-0.0249	0.490114
35	-0.051662	-0.3968	0.346464
36	0.034907	0.2681	0.394769
37	0.028616	0.2198	0.413391
38	0.059511	0.4571	0.324634
39	-0.123035	-0.945	0.174244
40	-0.073212	-0.5624	0.288003
41	0.0051	0.0392	0.484442
42	-0.038148	-0.293	0.385268
43	-0.001571	-0.0121	0.495206
44	0.019829	0.1523	0.43973
45	-0.007468	-0.0574	0.477224
46	-0.004557	-0.035	0.486099
47	-0.032573	-0.2502	0.401651
48	-0.005685	-0.0437	0.482658
49	0.034174	0.2625	0.396927
50	0.045861	0.3523	0.362949
51	0.01718	0.132	0.447733
52	-0.039402	-0.3027	0.381609
53	-0.054207	-0.4164	0.339323
54	-0.03617	-0.2778	0.391059
55	-0.051654	-0.3968	0.346487
56	-0.055305	-0.4248	0.336261
57	-0.08148	-0.6259	0.26691
58	0.04317	0.3316	0.370685
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/27/t126192309427lm9z56er8pf4m/1kkpx1261923053.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/27/t126192309427lm9z56er8pf4m/1kkpx1261923053.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/27/t126192309427lm9z56er8pf4m/20qsu1261923053.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/27/t126192309427lm9z56er8pf4m/20qsu1261923053.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1.4 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 1.4 ; 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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