Home » date » 2010 » Dec » 03 »

seizoenaal diff geboortes

*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: Fri, 03 Dec 2010 12:03:37 +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/03/t1291377780tqa060mqfhxzuk9.htm/, Retrieved Fri, 03 Dec 2010 13:03:00 +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/03/t1291377780tqa060mqfhxzuk9.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 «

9769 9321 9939 9336 10195 9464 10010 10213 9563 9890 9305 9391 9928 8686 9843 9627 10074 9503 10119 10000 9313 9866 9172 9241 9659 8904 9755 9080 9435 8971 10063 9793 9454 9759 8820 9403 9676 8642 9402 9610 9294 9448 10319 9548 9801 9596 8923 9746 9829 9125 9782 9441 9162 9915 10444 10209 9985 9842 9429 10132 9849 9172 10313 9819 9955 10048 10082 10541 10208 10233 9439 9963 10158 9225 10474 9757 10490 10281 10444 10640 10695 10786 9832 9747 10411 9511 10402 9701 10540 10112 10915 11183 10384 10834 9886 10216

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	-0.630765	-6.1479	0
2	0.181732	1.7713	0.039858
3	0.102013	0.9943	0.161301
4	-0.247167	-2.4091	0.00896
5	0.190141	1.8533	0.033474
6	-0.159939	-1.5589	0.061174
7	0.128059	1.2482	0.10752
8	-0.221654	-2.1604	0.016628
9	0.17903	1.745	0.042112
10	0.043237	0.4214	0.337201
11	-0.389755	-3.7989	0.000128
12	0.684887	6.6754	0
13	-0.502303	-4.8958	2e-06
14	0.2186	2.1307	0.01785
15	0.052245	0.5092	0.30589
16	-0.213651	-2.0824	0.019996
17	0.17948	1.7494	0.04173
18	-0.125157	-1.2199	0.112765
19	0.066941	0.6525	0.257839
20	-0.137188	-1.3371	0.092184
21	0.135334	1.3191	0.095158
22	-0.040532	-0.3951	0.346844
23	-0.187645	-1.8289	0.035273
24	0.443851	4.3261	1.9e-05
25	-0.354228	-3.4526	0.000415
26	0.17595	1.7149	0.044808
27	0.032023	0.3121	0.377818
28	-0.163096	-1.5897	0.057616
29	0.13759	1.3411	0.091549
30	-0.097491	-0.9502	0.172204
31	-0.009904	-0.0965	0.461652
32	0.006463	0.063	0.474952
33	0.028155	0.2744	0.39218
34	-0.003785	-0.0369	0.485324
35	-0.139415	-1.3588	0.088706
36	0.283207	2.7604	0.003465
37	-0.19417	-1.8925	0.030732
38	0.115616	1.1269	0.131314
39	0.015749	0.1535	0.439164
40	-0.142678	-1.3907	0.08379
41	0.133063	1.2969	0.098896
42	-0.113265	-1.104	0.136197
43	0.039605	0.386	0.350172
44	0.002813	0.0274	0.489092
45	-0.058916	-0.5742	0.28358
46	0.112754	1.099	0.137274
47	-0.206945	-2.0171	0.023256
48	0.280276	2.7318	0.003755
49	-0.175984	-1.7153	0.044777
50	0.088319	0.8608	0.19575
51	0.037319	0.3637	0.35843
52	-0.140573	-1.3701	0.086937
53	0.159192	1.5516	0.06204
54	-0.183881	-1.7923	0.038138
55	0.116503	1.1355	0.129505
56	-0.048589	-0.4736	0.318439
57	-0.047759	-0.4655	0.32132
58	0.148095	1.4435	0.076091
59	-0.252309	-2.4592	0.007867
60	0.32179	3.1364	0.001138

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.630765	-6.1479	0
2	-0.358941	-3.4985	0.000357
3	0.059825	0.5831	0.280603
4	-0.130611	-1.273	0.103056
5	-0.102034	-0.9945	0.161253
6	-0.204221	-1.9905	0.024705
7	-0.019238	-0.1875	0.425831
8	-0.347714	-3.3891	0.000511
9	-0.268615	-2.6181	0.005145
10	0.034244	0.3338	0.369644
11	-0.583301	-5.6853	0
12	0.070425	0.6864	0.247062
13	0.125206	1.2204	0.112674
14	0.055972	0.5455	0.293328
15	0.04124	0.402	0.344307
16	0.079073	0.7707	0.221396
17	0.046465	0.4529	0.325832
18	0.082694	0.806	0.211126
19	0.039871	0.3886	0.349215
20	0.138996	1.3548	0.089353
21	0.076417	0.7448	0.22911
22	-0.068569	-0.6683	0.252771
23	-0.022937	-0.2236	0.41179
24	0.021681	0.2113	0.416544
25	0.113463	1.1059	0.135782
26	0.024856	0.2423	0.404549
27	0.012917	0.1259	0.450038
28	0.06984	0.6807	0.248853
29	-0.002392	-0.0233	0.490726
30	-0.072732	-0.7089	0.24006
31	-0.182695	-1.7807	0.03908
32	0.020243	0.1973	0.422004
33	-0.037201	-0.3626	0.358858
34	0.01897	0.1849	0.426853
35	-0.089819	-0.8755	0.191768
36	-0.146365	-1.4266	0.078488
37	-0.054587	-0.5321	0.297966
38	0.03904	0.3805	0.352205
39	0.001996	0.0195	0.49226
40	-0.030141	-0.2938	0.384783
41	-0.018316	-0.1785	0.429346
42	-0.142856	-1.3924	0.083528
43	0.055516	0.5411	0.294852
44	0.093608	0.9124	0.18194
45	-0.076821	-0.7488	0.227927
46	0.062308	0.6073	0.272548
47	-0.071836	-0.7002	0.242765
48	0.042928	0.4184	0.338297
49	-0.023205	-0.2262	0.410777
50	-0.045643	-0.4449	0.328713
51	-0.007017	-0.0684	0.472808
52	-0.03044	-0.2967	0.383673
53	0.038766	0.3778	0.353196
54	-0.011509	-0.1122	0.455462
55	-0.05816	-0.5669	0.286069
56	-0.099563	-0.9704	0.167152
57	-0.071802	-0.6998	0.24287
58	-0.023536	-0.2294	0.409525
59	-0.017685	-0.1724	0.431757
60	0.051692	0.5038	0.307772

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/03/t1291377780tqa060mqfhxzuk9/13phf1291377813.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/03/t1291377780tqa060mqfhxzuk9/13phf1291377813.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/03/t1291377780tqa060mqfhxzuk9/23phf1291377813.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/03/t1291377780tqa060mqfhxzuk9/23phf1291377813.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;

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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