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paper timeserie Autocorrelation 2 (trend 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: Mon, 06 Dec 2010 19:51:05 +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/06/t1291664964idr7thdx40qdh0m.htm/, Retrieved Mon, 06 Dec 2010 20:49:26 +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/06/t1291664964idr7thdx40qdh0m.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 «

194.9 195.5 196 196.2 196.2 196.2 196.2 197 197.7 198 198.2 198.5 198.6 199.5 200 201.3 202.2 202.9 203.5 203.5 204 204.1 204.3 204.5 204.8 205.1 205.7 206.5 206.9 207.1 207.8 208 208.5 208.6 209 209.1 209.7 209.8 209.9 210 210.8 211.4 211.7 212 212.2 212.4 212.9 213.4 213.7 214 214.3 214.8 215 215.9 216.4 216.9 217.2 217.5 217.9 218.1 218.6 218.9 219.3 220.4 220.9 221 221.8 222 222.2 222.5 222.9 223.1

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	0.149529	1.26	0.105906
2	0.109697	0.9243	0.179224
3	-0.100394	-0.8459	0.200216
4	-0.170159	-1.4338	0.078012
5	-0.16984	-1.4311	0.078395
6	-0.020204	-0.1702	0.432651
7	-0.02973	-0.2505	0.401459
8	-0.092451	-0.779	0.219281
9	-0.075726	-0.6381	0.262738
10	0.04371	0.3683	0.356869
11	-0.113398	-0.9555	0.171281
12	-0.018586	-0.1566	0.437999
13	0.128996	1.0869	0.140371
14	0.055069	0.464	0.322026
15	0.024335	0.205	0.419061
16	-0.032705	-0.2756	0.391838
17	0.046634	0.3929	0.347768
18	-0.158094	-1.3321	0.093539
19	0.061571	0.5188	0.302754
20	-0.057708	-0.4863	0.314141
21	-0.080332	-0.6769	0.250336
22	-0.161622	-1.3619	0.088775
23	0.086669	0.7303	0.233809
24	-0.089381	-0.7531	0.226929
25	0.028054	0.2364	0.406905
26	0.063882	0.5383	0.296035
27	0.050514	0.4256	0.335828
28	-0.042193	-0.3555	0.361624
29	-0.047717	-0.4021	0.344419
30	-0.066767	-0.5626	0.287744
31	-0.061086	-0.5147	0.304174
32	-0.017789	-0.1499	0.440637
33	0.14732	1.2413	0.109283
34	0.007312	0.0616	0.475522
35	-0.064347	-0.5422	0.294691
36	0.071817	0.6051	0.273509

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.149529	1.26	0.105906
2	0.089336	0.7528	0.227043
3	-0.132692	-1.1181	0.13365
4	-0.154538	-1.3022	0.098534
5	-0.108104	-0.9109	0.182714
6	0.043108	0.3632	0.358756
7	-0.034552	-0.2911	0.385896
8	-0.152155	-1.2821	0.101992
9	-0.092912	-0.7829	0.218148
10	0.078494	0.6614	0.255246
11	-0.147325	-1.2414	0.109275
12	-0.080087	-0.6748	0.25099
13	0.135913	1.1452	0.127981
14	0.013977	0.1178	0.453291
15	-0.068143	-0.5742	0.28383
16	-0.098925	-0.8336	0.203664
17	0.114427	0.9642	0.169114
18	-0.129741	-1.0932	0.138997
19	0.033563	0.2828	0.389075
20	-0.090594	-0.7634	0.223889
21	-0.062878	-0.5298	0.298944
22	-0.164197	-1.3835	0.085416
23	0.093661	0.7892	0.216311
24	-0.103644	-0.8733	0.192716
25	-0.045355	-0.3822	0.35174
26	-0.002027	-0.0171	0.49321
27	-0.02755	-0.2321	0.408547
28	-0.060179	-0.5071	0.306836
29	-0.167316	-1.4098	0.081478
30	-0.073965	-0.6232	0.267562
31	-0.020603	-0.1736	0.431335
32	-0.085153	-0.7175	0.237707
33	0.023172	0.1952	0.422877
34	-0.060175	-0.507	0.306848
35	-0.115711	-0.975	0.166436
36	-0.006862	-0.0578	0.477026

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291664964idr7thdx40qdh0m/12z3a1291665063.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291664964idr7thdx40qdh0m/12z3a1291665063.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291664964idr7thdx40qdh0m/22z3a1291665063.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291664964idr7thdx40qdh0m/22z3a1291665063.ps (open in new window)

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; 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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