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taak 8 werklozen vlaams gewest d=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: Wed, 03 Dec 2008 09:37:45 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/03/t1228322332j1k240yllgok6ow.htm/, Retrieved Wed, 03 Dec 2008 16:38:54 +0000
 
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/2008/Dec/03/t1228322332j1k240yllgok6ow.htm/},
    year = {2008},
}
@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 = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
Feedback Forum:
2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc] [reply
test

Post a new message
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
189917 184128 175335 179566 181140 177876 175041 169292 166070 166972 206348 215706 202108 195411 193111 195198 198770 194163 190420 189733 186029 191531 232571 243477 227247 217859 208679 213188 216234 213587 209465 204045 200237 203666 241476 260307 243324 244460 233575 237217 235243 230354 227184 221678 217142 219452 256446 265845 248624 241114 229245 231805 219277 219313 212610 214771 211142 211457 240048 240636 230580
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.207741.60910.056417
2-0.289975-2.24610.014195
3-0.252559-1.95630.027544
4-0.161321-1.24960.108151
50.0243750.18880.425442
60.036680.28410.388647
70.058380.45220.326373
8-0.185596-1.43760.077868
9-0.238892-1.85050.034587
10-0.255327-1.97780.026277
110.2204821.70780.046418
120.7782336.02820
130.1610761.24770.108497
14-0.253194-1.96120.027249
15-0.223245-1.72920.044453
16-0.125451-0.97170.167541
17-0.011971-0.09270.463214
180.0500970.3880.349678
190.054870.4250.336172
20-0.151849-1.17620.122078
21-0.184405-1.42840.079182
22-0.197956-1.53340.065221
230.1655981.28270.102262
240.5599064.3372.8e-05
250.1223280.94760.173579
26-0.182345-1.41240.081494
27-0.115082-0.89140.188132
28-0.092937-0.71990.237194
29-0.007482-0.0580.476988
300.0069160.05360.478727
310.0374080.28980.386499
32-0.094734-0.73380.232961
33-0.132377-1.02540.154648
34-0.114439-0.88640.189459
350.0994890.77060.221972
360.3408412.64010.005273
370.0537530.41640.339314
38-0.126559-0.98030.165432
39-0.063813-0.49430.311452
40-0.041998-0.32530.373038
41-0.008649-0.0670.473405
42-0.002325-0.0180.492845
430.0347480.26920.394366
44-0.055346-0.42870.334836
45-0.046084-0.3570.361184
46-0.039541-0.30630.380225
470.0560780.43440.332785
480.1452261.12490.132552
49-0.002186-0.01690.493274
50-0.041358-0.32040.374905
51-0.009779-0.07570.469937
520.0021530.01670.493374
53-0.002295-0.01780.492938
540.0094110.07290.471066
550.0174790.13540.446379
56-0.027524-0.21320.415947
57-0.022043-0.17070.432499
580.0103470.08010.468193
590.0070250.05440.478392
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.207741.60910.056417
2-0.348156-2.69680.004537
3-0.117761-0.91220.182664
4-0.20245-1.56820.06105
5-0.018456-0.1430.4434
6-0.129347-1.00190.160204
70.0173930.13470.44664
8-0.331323-2.56640.006395
9-0.196528-1.52230.066593
10-0.548198-4.24633.8e-05
110.1004010.77770.219901
120.5291694.09896.3e-05
13-0.077791-0.60260.274533
140.0147530.11430.454701
150.0305210.23640.406957
16-0.045542-0.35280.362751
17-0.050553-0.39160.348376
18-0.04536-0.35140.363275
19-0.084964-0.65810.256485
200.0391350.30310.381415
210.0457540.35440.362138
220.0007580.00590.497668
23-0.143137-1.10870.135984
24-0.121784-0.94330.174646
25-0.087659-0.6790.249874
260.0016380.01270.49496
270.1172320.90810.183736
28-0.040099-0.31060.37859
290.1251910.96970.168039
30-0.155376-1.20350.116748
310.0308760.23920.405897
32-0.048311-0.37420.354782
33-0.000397-0.00310.498779
340.0654550.5070.307001
350.0303130.23480.407579
36-0.160113-1.24020.109859
37-0.021001-0.16270.435661
38-0.192638-1.49220.070447
39-0.147769-1.14460.128457
40-0.062038-0.48050.316293
41-0.079461-0.61550.270275
420.0549540.42570.335934
43-0.007004-0.05420.478459
44-0.052518-0.40680.342801
450.0016140.01250.495033
46-0.034491-0.26720.395129
47-0.019374-0.15010.440605
48-0.116086-0.89920.186071
490.0376520.29170.385779
500.0756350.58590.280082
510.0366120.28360.388849
52-0.010899-0.08440.4665
53-0.034652-0.26840.39465
540.0066930.05180.479411
550.0157270.12180.451723
56-0.025673-0.19890.421523
57-0.027019-0.20930.417466
580.0081080.06280.475067
59-0.031686-0.24540.403476
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228322332j1k240yllgok6ow/1hmbk1228322263.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228322332j1k240yllgok6ow/1hmbk1228322263.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228322332j1k240yllgok6ow/2stkv1228322263.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/03/t1228322332j1k240yllgok6ow/2stkv1228322263.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
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 (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='lags',ylab='ACF')
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')
 





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