Home » date » 2010 » Jul » 08 »

Kelly Janbroers - 2de zit - Stap 18/B

*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Thu, 08 Jul 2010 15:08:12 +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/Jul/08/t1278601688i1bl5u7ipdzy7kx.htm/, Retrieved Thu, 08 Jul 2010 17:08:10 +0200

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/Jul/08/t1278601688i1bl5u7ipdzy7kx.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 «

268 267 266 264 262 261 262 264 265 265 266 268 260 264 265 262 258 265 273 273 270 263 260 257 248 248 237 228 225 231 243 250 246 240 236 235 225 230 225 221 231 234 249 257 253 252 245 239 229 232 222 218 223 221 230 234 237 226 215 211 203 202 187 179 181 172 182 180 175 163 160 151 145 140 125 122 124 108 115 116 104 98 101 91

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	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.157984	1.4393	0.076912
2	0.112733	1.027	0.153692
3	0.124276	1.1322	0.130403
4	-0.17824	-1.6238	0.054101
5	-0.082657	-0.753	0.226778
6	-0.058325	-0.5314	0.298291
7	-0.074194	-0.6759	0.250478
8	-0.189863	-1.7297	0.043697
9	0.029211	0.2661	0.395402
10	0.088281	0.8043	0.211768
11	0.19395	1.767	0.040455
12	0.643099	5.8589	0
13	0.05844	0.5324	0.297932
14	0.111643	1.0171	0.156028
15	-0.011895	-0.1084	0.456983
16	-0.234532	-2.1367	0.017784
17	-0.113779	-1.0366	0.151473
18	-0.147667	-1.3453	0.091094
19	-0.134376	-1.2242	0.112165
20	-0.173246	-1.5783	0.059145
21	-0.008712	-0.0794	0.468466
22	0.016317	0.1487	0.441094
23	0.15992	1.4569	0.074453
24	0.381518	3.4758	0.000406
25	0.036453	0.3321	0.370323
26	0.098959	0.9016	0.184949
27	-0.024104	-0.2196	0.413361
28	-0.255914	-2.3315	0.011076
29	-0.051008	-0.4647	0.321679
30	-0.072758	-0.6629	0.25463
31	-0.113279	-1.032	0.152531
32	-0.133418	-1.2155	0.113811
33	0.010982	0.1	0.460274
34	-0.034806	-0.3171	0.375985
35	0.089481	0.8152	0.208644
36	0.248505	2.264	0.013092
37	0.011034	0.1005	0.460086
38	0.037545	0.3421	0.366588
39	-0.030522	-0.2781	0.390825
40	-0.224377	-2.0442	0.022053
41	0.0295	0.2688	0.39439
42	-0.039319	-0.3582	0.360548
43	-0.098587	-0.8982	0.185846
44	-0.067342	-0.6135	0.270607
45	-0.004338	-0.0395	0.484285
46	-0.021992	-0.2004	0.420846
47	0.061376	0.5592	0.288777
48	0.094744	0.8632	0.19527
49	0.003902	0.0355	0.485864
50	-0.004559	-0.0415	0.483486
51	-0.051067	-0.4652	0.321489
52	-0.114517	-1.0433	0.14992
53	0.044133	0.4021	0.344331
54	-0.067656	-0.6164	0.269666
55	-0.063346	-0.5771	0.282714
56	-0.033584	-0.306	0.3802
57	-0.009335	-0.085	0.466216
58	-0.035729	-0.3255	0.372809
59	0.005867	0.0535	0.478751
60	-0.023851	-0.2173	0.414258

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.157984	1.4393	0.076912
2	0.09002	0.8201	0.207247
3	0.097036	0.884	0.189614
4	-0.228516	-2.0819	0.020217
5	-0.049082	-0.4472	0.327962
6	-0.01358	-0.1237	0.450918
7	0.001036	0.0094	0.496248
8	-0.214439	-1.9536	0.027057
9	0.086949	0.7921	0.215268
10	0.120227	1.0953	0.138272
11	0.221816	2.0208	0.02326
12	0.576996	5.2567	1e-06
13	-0.177563	-1.6177	0.054764
14	-0.026799	-0.2442	0.403858
15	-0.224254	-2.0431	0.02211
16	-0.0803	-0.7316	0.233247
17	-0.079821	-0.7272	0.234573
18	-0.074386	-0.6777	0.249927
19	-0.02237	-0.2038	0.419506
20	0.056341	0.5133	0.304556
21	0.030812	0.2807	0.389814
22	-0.094804	-0.8637	0.195118
23	-0.055152	-0.5025	0.308338
24	-0.086764	-0.7905	0.215758
25	0.071018	0.647	0.259706
26	0.01446	0.1317	0.447756
27	0.140394	1.2791	0.102222
28	-0.110379	-1.0056	0.158765
29	0.166863	1.5202	0.066131
30	0.119672	1.0903	0.139376
31	0.031344	0.2856	0.387963
32	-0.15886	-1.4473	0.075793
33	-0.055073	-0.5017	0.308591
34	-0.082517	-0.7518	0.227159
35	-0.056669	-0.5163	0.303517
36	-0.035214	-0.3208	0.37458
37	-0.077596	-0.7069	0.240795
38	0.012275	0.1118	0.455614
39	0.033524	0.3054	0.380405
40	-0.007564	-0.0689	0.472612
41	0.033007	0.3007	0.382195
42	-0.005308	-0.0484	0.480775
43	-0.04108	-0.3743	0.354583
44	0.042247	0.3849	0.350654
45	0.018757	0.1709	0.432364
46	0.118017	1.0752	0.142704
47	0.013742	0.1252	0.450335
48	-0.115731	-1.0544	0.147389
49	0.028701	0.2615	0.397184
50	-0.073842	-0.6727	0.251494
51	-0.0251	-0.2287	0.409842
52	-0.013637	-0.1242	0.450713
53	-0.08346	-0.7604	0.224597
54	-0.068242	-0.6217	0.267918
55	-0.013776	-0.1255	0.450212
56	-0.076529	-0.6972	0.243808
57	0.06634	0.6044	0.273618
58	-0.054882	-0.5	0.309201
59	0.002885	0.0263	0.489547
60	-0.08559	-0.7798	0.218875

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jul/08/t1278601688i1bl5u7ipdzy7kx/1qxka1278601689.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/08/t1278601688i1bl5u7ipdzy7kx/1qxka1278601689.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/08/t1278601688i1bl5u7ipdzy7kx/2qxka1278601689.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/08/t1278601688i1bl5u7ipdzy7kx/2qxka1278601689.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 60 ; par2 = 1 ; 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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