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partial autocorrelation function eur/usd

*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: Sat, 18 Dec 2010 10:00:27 +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/18/t1292666416z28to35b9dzs6fj.htm/, Retrieved Sat, 18 Dec 2010 11:00:16 +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/18/t1292666416z28to35b9dzs6fj.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 «

1.3031 1.3241 1.2961 1.2865 1.2305 1.2101 1.2125 1.2350 1.2014 1.1992 1.1791 1.1832 1.2159 1.1922 1.2114 1.2614 1.2812 1.2786 1.2772 1.2815 1.2679 1.2765 1.3247 1.3191 1.3029 1.3234 1.3354 1.3651 1.3453 1.3534 1.3706 1.3638 1.4268 1.4485 1.4635 1.4587 1.4876 1.5189 1.5783 1.5633 1.5554 1.5757 1.5593 1.4660 1.4065 1.2759 1.2705 1.3954 1.2793 1.2694 1.3282 1.3230 1.4135 1.4042 1.4253 1.4322 1.4632 1.4713 1.5016 1.4318

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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.00736	-0.0565	0.477555
2	-0.046861	-0.3599	0.360085
3	0.175375	1.3471	0.091552
4	-0.073287	-0.5629	0.287808
5	0.140841	1.0818	0.141867
6	0.03035	0.2331	0.408236
7	-0.311741	-2.3945	0.009919
8	-0.105666	-0.8116	0.210132
9	-0.069361	-0.5328	0.298096
10	-0.077404	-0.5946	0.277208
11	0.014603	0.1122	0.455535
12	-0.212943	-1.6356	0.053619
13	-0.145363	-1.1166	0.134356
14	0.112985	0.8679	0.194495
15	0.118018	0.9065	0.184176
16	0.016832	0.1293	0.448785
17	0.025445	0.1954	0.422857
18	-0.015263	-0.1172	0.453535
19	-0.040787	-0.3133	0.377583
20	0.151645	1.1648	0.124392
21	-0.053995	-0.4147	0.339917
22	-0.001602	-0.0123	0.495113
23	-0.091256	-0.7009	0.243046
24	-0.003428	-0.0263	0.48954
25	0.113851	0.8745	0.192695
26	-0.022642	-0.1739	0.431263
27	-0.089165	-0.6849	0.248048
28	-0.085611	-0.6576	0.25668
29	-0.085828	-0.6593	0.256147
30	-0.076842	-0.5902	0.278644
31	0.029865	0.2294	0.409677
32	0.011355	0.0872	0.465395
33	-0.096272	-0.7395	0.231275
34	-0.079135	-0.6078	0.272812
35	0.176795	1.358	0.089819
36	0.007303	0.0561	0.477727
37	0.004583	0.0352	0.486019
38	0.05079	0.3901	0.348923
39	0.011836	0.0909	0.463933
40	0.183146	1.4068	0.08237
41	0.099801	0.7666	0.223191
42	-0.034301	-0.2635	0.396554
43	-0.005527	-0.0425	0.483141
44	-0.022171	-0.1703	0.432678
45	-0.026779	-0.2057	0.41887
46	0.038433	0.2952	0.384435
47	-0.063641	-0.4888	0.313385
48	-0.085861	-0.6595	0.256067
49	0.024095	0.1851	0.426903
50	-0.043356	-0.333	0.370149
51	0.039314	0.302	0.381866
52	-0.039659	-0.3046	0.380862
53	-0.010638	-0.0817	0.467576
54	-0.007191	-0.0552	0.478068
55	0.040291	0.3095	0.379023
56	0.001215	0.0093	0.496291
57	0.024603	0.189	0.425379
58	-0.012438	-0.0955	0.462106
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.00736	-0.0565	0.477555
2	-0.046918	-0.3604	0.359923
3	0.175064	1.3447	0.091936
4	-0.076743	-0.5895	0.278896
5	0.164445	1.2631	0.105757
6	-0.014661	-0.1126	0.455361
7	-0.284616	-2.1862	0.016391
8	-0.173681	-1.3341	0.093653
9	-0.099946	-0.7677	0.222864
10	-0.012737	-0.0978	0.461198
11	0.025553	0.1963	0.422533
12	-0.13202	-1.0141	0.157346
13	-0.11756	-0.903	0.1851
14	0.0218	0.1675	0.433794
15	0.128434	0.9865	0.163954
16	-0.002402	-0.0185	0.49267
17	0.004354	0.0334	0.486718
18	-0.034291	-0.2634	0.396582
19	-0.188083	-1.4447	0.076917
20	-0.011243	-0.0864	0.465737
21	-0.092823	-0.713	0.239333
22	0.106981	0.8217	0.207268
23	-0.112382	-0.8632	0.195756
24	0.060155	0.4621	0.32287
25	0.030497	0.2343	0.407799
26	-0.009064	-0.0696	0.472364
27	-0.041255	-0.3169	0.376226
28	-0.135899	-1.0439	0.150404
29	-0.136747	-1.0504	0.148915
30	-0.242372	-1.8617	0.033815
31	-0.04659	-0.3579	0.36086
32	0.091474	0.7026	0.242526
33	-0.010172	-0.0781	0.468994
34	-0.091608	-0.7037	0.242209
35	0.1076	0.8265	0.205927
36	-0.068781	-0.5283	0.29963
37	-0.064453	-0.4951	0.311193
38	-0.065777	-0.5052	0.307635
39	0.008834	0.0679	0.473064
40	0.006816	0.0524	0.479211
41	0.010401	0.0799	0.468297
42	-0.077204	-0.593	0.277719
43	-0.010655	-0.0818	0.467523
44	0.026818	0.206	0.418754
45	-0.013836	-0.1063	0.457861
46	-0.044742	-0.3437	0.366158
47	-0.00423	-0.0325	0.487095
48	0.0133	0.1022	0.459487
49	-0.041311	-0.3173	0.376063
50	-0.097979	-0.7526	0.227345
51	0.034866	0.2678	0.39489
52	-0.057098	-0.4386	0.331285
53	0.038433	0.2952	0.384436
54	-0.012449	-0.0956	0.462073
55	-0.004973	-0.0382	0.48483
56	-0.070672	-0.5428	0.294641
57	-0.087395	-0.6713	0.252327
58	-0.01514	-0.1163	0.453909
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292666416z28to35b9dzs6fj/1txk91292666423.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292666416z28to35b9dzs6fj/1txk91292666423.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292666416z28to35b9dzs6fj/237jb1292666423.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/18/t1292666416z28to35b9dzs6fj/237jb1292666423.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; par2 = 0.0 ; 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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