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paper seizoen & trend weggewerkt!

*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, 19 Dec 2009 15:05:08 -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/19/t12612603951lgt1nh27kpnt19.htm/, Retrieved Sat, 19 Dec 2009 23:06:37 +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/19/t12612603951lgt1nh27kpnt19.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:

ShwPaper seizoen & trend weggewerkt!

Dataseries X:

» Textbox « » Textfile « » CSV «

152,60 153,32 165,50 139,18 136,53 115,92 96,65 83,77 84,66 106,03 86,92 54,66 151,66 121,27 132,95 119,64 122,16 117,44 106,69 87,45 80,98 110,30 87,01 55,73 146,00 137,54 138,54 135,62 107,27 99,04 91,36 68,35 82,59 98,41 71,25 47,58 130,83 113,60 125,69 113,60 97,12 104,43 91,84 75,11 89,24 110,23 78,42 68,45 122,81 129,66 159,06 139,03 102,16 113,59 81,46 77,36 87,57 101,23 87,21 64,94 133,12 117,99 135,90 125,67 108,03 128,31 84,74 86,38 92,24 95,83 92,33 54,27

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	-0.289936	-2.227	0.014887
2	0.00448	0.0344	0.486333
3	-0.079049	-0.6072	0.273029
4	-0.165417	-1.2706	0.10443
5	0.029872	0.2294	0.409657
6	0.07499	0.576	0.283399
7	-0.065543	-0.5034	0.308264
8	-0.003795	-0.0292	0.48842
9	0.21039	1.616	0.055711
10	-0.058637	-0.4504	0.327036
11	-0.036783	-0.2825	0.389262
12	-0.244545	-1.8784	0.032636
13	-0.073556	-0.565	0.287109
14	0.015872	0.1219	0.45169
15	0.3087	2.3712	0.010508
16	-0.228834	-1.7577	0.041992
17	0.115699	0.8887	0.188886
18	0.067637	0.5195	0.302668
19	-0.175757	-1.35	0.091084
20	0.208338	1.6003	0.057439
21	-0.17768	-1.3648	0.088751
22	-0.106251	-0.8161	0.208853
23	0.137419	1.0555	0.147743
24	0.124442	0.9559	0.171523
25	-0.0242	-0.1859	0.426587
26	0.15667	1.2034	0.116813
27	-0.213191	-1.6376	0.053419
28	0.062377	0.4791	0.316809
29	-0.01087	-0.0835	0.466872
30	-0.083335	-0.6401	0.262291
31	-0.064816	-0.4979	0.310216
32	0.057349	0.4405	0.330589
33	0.139929	1.0748	0.143416
34	-0.078665	-0.6042	0.274001
35	0.137948	1.0596	0.146823
36	-0.232274	-1.7841	0.039772

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.289936	-2.227	0.014887
2	-0.086887	-0.6674	0.253562
3	-0.11312	-0.8689	0.194214
4	-0.248892	-1.9118	0.030383
5	-0.132965	-1.0213	0.155636
6	0.003357	0.0258	0.489758
7	-0.106923	-0.8213	0.207393
8	-0.125632	-0.965	0.169242
9	0.193693	1.4878	0.071066
10	0.097982	0.7526	0.227337
11	-0.040831	-0.3136	0.377456
12	-0.292893	-2.2498	0.014104
13	-0.223651	-1.7179	0.04553
14	-0.187478	-1.44	0.07757
15	0.162036	1.2446	0.109096
16	-0.258623	-1.9865	0.025813
17	-0.120742	-0.9274	0.17874
18	0.119378	0.917	0.181448
19	-0.1105	-0.8488	0.199722
20	0.059326	0.4557	0.325142
21	-0.013031	-0.1001	0.460306
22	-0.110469	-0.8485	0.199786
23	-0.039175	-0.3009	0.382272
24	-0.040884	-0.314	0.377302
25	-0.049002	-0.3764	0.353989
26	0.172814	1.3274	0.094744
27	0.002289	0.0176	0.493015
28	0.07622	0.5855	0.280236
29	0.020539	0.1578	0.437591
30	-0.064247	-0.4935	0.311748
31	-0.044135	-0.339	0.367904
32	-0.057994	-0.4455	0.328808
33	0.100139	0.7692	0.222427
34	-0.033434	-0.2568	0.399108
35	-0.049128	-0.3774	0.353631
36	0.052336	0.402	0.344568

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612603951lgt1nh27kpnt19/1kwne1261260306.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612603951lgt1nh27kpnt19/1kwne1261260306.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612603951lgt1nh27kpnt19/2i4z71261260306.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/19/t12612603951lgt1nh27kpnt19/2i4z71261260306.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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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