Home » date » 2010 » Dec » 07 »

ws 9: acf (zonder seizoenaliteit)

*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: Tue, 07 Dec 2010 09:32:15 +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/Dec/07/t1291714257q7v1s8awb5fmvub.htm/, Retrieved Tue, 07 Dec 2010 10:30:59 +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/2010/Dec/07/t1291714257q7v1s8awb5fmvub.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

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 89.1 104.5 105.1 95.1 88.7 86.3 91.8 111.5 99.7 97.5 111.7 86.2 95.4

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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.598829	4.4812	1.9e-05
2	0.667785	4.9972	3e-06
3	0.705521	5.2796	1e-06
4	0.453017	3.3901	0.000643
5	0.474208	3.5486	0.000396
6	0.361668	2.7065	0.004498
7	0.199272	1.4912	0.070759
8	0.226922	1.6981	0.047517
9	0.062778	0.4698	0.320165
10	0.003998	0.0299	0.48812
11	-0.01969	-0.1473	0.441693
12	-0.136933	-1.0247	0.154952
13	-0.131141	-0.9814	0.165315
14	-0.173678	-1.2997	0.099516
15	-0.184699	-1.3822	0.086205
16	-0.230349	-1.7238	0.045133
17	-0.165248	-1.2366	0.110699
18	-0.170027	-1.2724	0.104251
19	-0.185468	-1.3879	0.08533
20	-0.115669	-0.8656	0.195204
21	-0.135047	-1.0106	0.158277
22	-0.183711	-1.3748	0.087339
23	-0.025169	-0.1883	0.425643
24	-0.207048	-1.5494	0.063459
25	-0.119086	-0.8912	0.188329
26	-0.115043	-0.8609	0.196481
27	-0.225269	-1.6858	0.048704
28	-0.126941	-0.9499	0.173112
29	-0.183249	-1.3713	0.087875
30	-0.216472	-1.6199	0.055433
31	-0.167767	-1.2555	0.107264
32	-0.214099	-1.6022	0.057372
33	-0.205971	-1.5413	0.064432
34	-0.167738	-1.2552	0.107303
35	-0.220486	-1.65	0.052274
36	-0.151087	-1.1306	0.131514
37	-0.141235	-1.0569	0.147547
38	-0.121109	-0.9063	0.18433
39	-0.112557	-0.8423	0.201601
40	-0.074144	-0.5548	0.290607
41	-0.036217	-0.271	0.393684
42	-0.028515	-0.2134	0.4159
43	-0.012449	-0.0932	0.463056
44	0.008976	0.0672	0.473343
45	0.01537	0.115	0.454422
46	0.053514	0.4005	0.345169
47	0.028976	0.2168	0.414563
48	0.057951	0.4337	0.333098
49	0.069809	0.5224	0.301725
50	0.0525	0.3929	0.347952
51	0.066217	0.4955	0.311084
52	0.032245	0.2413	0.405102
53	0.039137	0.2929	0.385352
54	0.015487	0.1159	0.454076
55	0.009133	0.0683	0.472876
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.598829	4.4812	1.9e-05
2	0.48205	3.6073	0.00033
3	0.425976	3.1877	0.001174
4	-0.272197	-2.0369	0.023197
5	-0.215462	-1.6124	0.056252
6	-0.198286	-1.4838	0.07173
7	-0.162278	-1.2144	0.11485
8	0.08893	0.6655	0.254234
9	0.001678	0.0126	0.495012
10	-0.007714	-0.0577	0.477085
11	-0.059472	-0.445	0.329001
12	-0.063488	-0.4751	0.318282
13	0.009832	0.0736	0.470804
14	0.018682	0.1398	0.444658
15	0.129905	0.9721	0.167586
16	-0.140535	-1.0517	0.148735
17	0.084868	0.6351	0.263976
18	0.063732	0.4769	0.317636
19	-0.015587	-0.1166	0.453781
20	-0.039549	-0.296	0.384179
21	-0.099568	-0.7451	0.229664
22	-0.26001	-1.9457	0.028356
23	0.179797	1.3455	0.091947
24	-0.147713	-1.1054	0.13686
25	0.031169	0.2332	0.40821
26	-0.143657	-1.075	0.143486
27	-0.026707	-0.1999	0.421159
28	0.006038	0.0452	0.482059
29	0.096867	0.7249	0.235771
30	0.062407	0.467	0.321152
31	-0.146831	-1.0988	0.138282
32	-0.048467	-0.3627	0.359099
33	-0.024844	-0.1859	0.426591
34	0.072332	0.5413	0.29523
35	0.019487	0.1458	0.44229
36	-0.050566	-0.3784	0.353282
37	-0.011482	-0.0859	0.465917
38	-0.016918	-0.1266	0.449855
39	-0.004029	-0.0302	0.488027
40	-0.106837	-0.7995	0.213692
41	0.059175	0.4428	0.3298
42	0.010872	0.0814	0.467723
43	-0.053462	-0.4001	0.345313
44	-0.053752	-0.4022	0.344518
45	0.085002	0.6361	0.263651
46	-0.033718	-0.2523	0.400858
47	0.065164	0.4876	0.313853
48	-0.065916	-0.4933	0.311875
49	0.005481	0.041	0.483715
50	0.034479	0.258	0.398669
51	-0.084341	-0.6311	0.265256
52	-0.11858	-0.8874	0.189337
53	-0.046181	-0.3456	0.365473
54	0.015915	0.1191	0.452811
55	0.016364	0.1225	0.451487
56	NA	NA	NA
57	NA	NA	NA
58	NA	NA	NA
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/07/t1291714257q7v1s8awb5fmvub/19w1e1291714332.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/07/t1291714257q7v1s8awb5fmvub/19w1e1291714332.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/07/t1291714257q7v1s8awb5fmvub/2koi01291714332.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/07/t1291714257q7v1s8awb5fmvub/2koi01291714332.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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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