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Paper DMA PACF Aandelen

*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: Wed, 15 Dec 2010 18:37:06 +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/15/t1292438443vgl26xqptby5ixk.htm/, Retrieved Wed, 15 Dec 2010 19:40:43 +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/15/t1292438443vgl26xqptby5ixk.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:

Paper DMA

Dataseries X:

» Textbox « » Textfile « » CSV «

3030.29 2803.47 2767.63 2882.6 2863.36 2897.06 3012.61 3142.95 3032.93 3045.78 3110.52 3013.24 2987.1 2995.55 2833.18 2848.96 2794.83 2845.26 2915.03 2892.63 2604.42 2641.65 2659.81 2638.53 2720.25 2745.88 2735.7 2811.7 2799.43 2555.28 2304.98 2214.95 2065.81 1940.49 2042 1995.37 1946.81 1765.9 1635.25 1833.42 1910.43 1959.67 1969.6 2061.41 2093.48 2120.88 2174.56 2196.72 2350.44 2440.25 2408.64 2472.81 2407.6 2454.62 2448.05 2497.84 2645.64 2756.76 2849.27 2921.44 2981.85 3080.58 3106.22 3119.31 3061.26 3097.31 3161.69 3257.16 3277.01 3295.32 3363.99 3494.17 3667.03 3813.06 3917.96 3895.51 3801.06 3570.12 3701.61 3862.27 3970.1 4138.52 4199.75 4290.89 4443.91 4502.64 4356.98 4591.27 4696.96 4621.4 4562.84 4202.52 4296.49 4435.23 4105.18 4116.68 3844.49 3720.98 3674.4 3857.62 3801.06 3504.37 3032.6 3047.03 2962.34 2197.82 2014.45 1862.83 1905.41

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.278097	2.8901	0.002328
2	0.082294	0.8552	0.197159
3	0.196884	2.0461	0.021589
4	0.141279	1.4682	0.072476
5	0.183257	1.9045	0.029755
6	0.089377	0.9288	0.177522
7	0.04913	0.5106	0.305345
8	0.117296	1.219	0.112754
9	0.124913	1.2981	0.098504
10	0.044369	0.4611	0.322829
11	0.171422	1.7815	0.038823
12	0.051429	0.5345	0.297058
13	-0.017154	-0.1783	0.429422
14	0.108973	1.1325	0.129971
15	0.069897	0.7264	0.234586
16	0.060634	0.6301	0.264972
17	-0.027746	-0.2883	0.386819
18	-0.078576	-0.8166	0.20798
19	0.003593	0.0373	0.48514
20	-0.071683	-0.745	0.228959
21	-0.037368	-0.3883	0.349264
22	-0.068405	-0.7109	0.239344
23	-0.128921	-1.3398	0.091563
24	-0.084839	-0.8817	0.189956
25	-0.015532	-0.1614	0.436035
26	-0.082493	-0.8573	0.196592
27	-0.056361	-0.5857	0.279642
28	-0.00393	-0.0408	0.483747
29	-0.03787	-0.3936	0.347341
30	-0.030919	-0.3213	0.374296
31	-0.061394	-0.638	0.262405
32	-0.032	-0.3326	0.370058
33	-0.085165	-0.8851	0.189046
34	-0.08998	-0.9351	0.175913
35	-0.123423	-1.2826	0.101181
36	-0.038787	-0.4031	0.34384
37	-0.058736	-0.6104	0.271439
38	-0.080605	-0.8377	0.202032
39	-0.005517	-0.0573	0.47719
40	-0.05522	-0.5739	0.283625
41	-0.059416	-0.6175	0.269113
42	-0.068735	-0.7143	0.238286
43	-0.115279	-1.198	0.116767
44	-0.044409	-0.4615	0.322682
45	-0.086227	-0.8961	0.186098
46	-0.100088	-1.0401	0.150298
47	-0.098781	-1.0266	0.153461
48	-0.080779	-0.8395	0.201526
49	-0.116814	-1.214	0.113703
50	-0.102918	-1.0696	0.143602
51	-0.090664	-0.9422	0.174094
52	-0.112006	-1.164	0.123495
53	-0.021241	-0.2207	0.412856
54	-0.053258	-0.5535	0.290543
55	-0.084202	-0.8751	0.191744
56	-0.042407	-0.4407	0.330155
57	-0.074168	-0.7708	0.221262
58	-0.074981	-0.7792	0.218775
59	-0.04073	-0.4233	0.336465
60	-0.00531	-0.0552	0.478049

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.278097	2.8901	0.002328
2	0.005372	0.0558	0.47779
3	0.187102	1.9444	0.027223
4	0.043582	0.4529	0.325758
5	0.143677	1.4931	0.069159
6	-0.028465	-0.2958	0.383971
7	0.007614	0.0791	0.46854
8	0.053645	0.5575	0.289172
9	0.05977	0.6211	0.267906
10	-0.032922	-0.3421	0.366456
11	0.159057	1.653	0.05062
12	-0.082643	-0.8589	0.196161
13	-0.03676	-0.382	0.351599
14	0.0585	0.608	0.272247
15	0.01507	0.1566	0.43792
16	0.011306	0.1175	0.453342
17	-0.086991	-0.904	0.183994
18	-0.071969	-0.7479	0.228066
19	-0.011629	-0.1208	0.452018
20	-0.113039	-1.1747	0.121341
21	0.051794	0.5383	0.295754
22	-0.091261	-0.9484	0.17252
23	-0.072058	-0.7489	0.227787
24	-0.023155	-0.2406	0.405149
25	0.031352	0.3258	0.372596
26	-0.055454	-0.5763	0.282808
27	0.038005	0.395	0.346826
28	0.052895	0.5497	0.291829
29	0.023254	0.2417	0.404748
30	-0.041351	-0.4297	0.334125
31	0.017867	0.1857	0.426523
32	0.020669	0.2148	0.415166
33	-0.080722	-0.8389	0.201691
34	0.014169	0.1473	0.441604
35	-0.099114	-1.03	0.15265
36	0.038961	0.4049	0.343179
37	-0.03858	-0.4009	0.34463
38	0.013055	0.1357	0.446166
39	0.032021	0.3328	0.369977
40	-0.056724	-0.5895	0.27838
41	-0.02005	-0.2084	0.41767
42	-0.042352	-0.4401	0.330359
43	-0.114232	-1.1871	0.118889
44	0.04121	0.4283	0.334654
45	-0.076167	-0.7915	0.21518
46	-0.012406	-0.1289	0.448828
47	-0.073663	-0.7655	0.222815
48	0.001385	0.0144	0.494271
49	-0.060046	-0.624	0.266966
50	-0.03336	-0.3467	0.364749
51	-0.013802	-0.1434	0.443105
52	-0.019165	-0.1992	0.421255
53	0.008617	0.0896	0.464405
54	0.040916	0.4252	0.335764
55	-0.078496	-0.8158	0.208218
56	0.041609	0.4324	0.33315
57	-0.060219	-0.6258	0.266379
58	-0.019281	-0.2004	0.420781
59	0.007855	0.0816	0.467545
60	0.040938	0.4254	0.33568

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292438443vgl26xqptby5ixk/1lqoj1292438222.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292438443vgl26xqptby5ixk/1lqoj1292438222.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292438443vgl26xqptby5ixk/2o8n71292438222.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292438443vgl26xqptby5ixk/2o8n71292438222.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292438443vgl26xqptby5ixk/3o8n71292438222.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292438443vgl26xqptby5ixk/3o8n71292438222.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 (par8 != '') par8 <- as.numeric(par8)

ox <- x

if (par8 == '') {

if (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

} else {

x <- log(x,base=par8)

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='picts.png')

op <- par(mfrow=c(2,1))

plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')

if (par8=='') {

mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

} else {

mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')

mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')

}

plot(x,type='l', main=mytitle,xlab='time',ylab='value')

par(op)

dev.off()

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)

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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