Time series analysis verkochte ton koffie per maand

*Unverified author*

R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Mon, 25 Apr 2011 14:34:40 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/Apr/25/t1303741893yue794amonln2r0.htm/, Retrieved Mon, 25 Apr 2011 16:31:34 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

600 425 398 582 458 455 621 635 589 220 351 379 683 524 536 598 581 632 645 722 689 645 354 486 423 479 684 601 608 463 602 485 563 645 486 435 479 579 563 202 389 467 466 706 546 689 531 528 579 684 651 637 548 496 582 467 693 615 708 648 899 852 745 689 582 674 684 542 489 472 398 486 549 766 654 628 689 648 578 536 548 496 475 687 642 584 596 609 678 694 485 489 537 706 489 598

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 0.3458 3.1693 0.001066 2 0.301304 2.7615 0.003533 3 0.044943 0.4119 0.340726 4 0.060063 0.5505 0.291722 5 0.033692 0.3088 0.379123 6 0.008692 0.0797 0.468347 7 0.108508 0.9945 0.16142 8 -0.016293 -0.1493 0.440825 9 0.029241 0.268 0.39468 10 -0.135056 -1.2378 0.109618 11 -0.131629 -1.2064 0.115525 12 -0.354437 -3.2485 0.000834 13 -0.018262 -0.1674 0.433738 14 -0.068029 -0.6235 0.267323 15 0.145474 1.3333 0.093021 16 0.031083 0.2849 0.388218 17 0.042981 0.3939 0.347316 18 -0.182742 -1.6749 0.04884 19 -0.327501 -3.0016 0.001768 20 -0.213724 -1.9588 0.026726 21 -0.353516 -3.24 0.000857 22 -0.126103 -1.1558 0.125529 23 -0.133782 -1.2261 0.111788 24 -0.039248 -0.3597 0.359983 25 -0.14975 -1.3725 0.086784 26 -0.077574 -0.711 0.239534 27 -0.199391 -1.8275 0.035591 28 -0.005792 -0.0531 0.478895 29 -0.030852 -0.2828 0.389026 30 0.176136 1.6143 0.055105 31 0.173026 1.5858 0.05827 32 0.13691 1.2548 0.106516 33 0.202723 1.858 0.033337 34 -0.059599 -0.5462 0.293176 35 0.054476 0.4993 0.309443 36 -0.080823 -0.7408 0.230453 37 0.090258 0.8272 0.205226 38 0.03736 0.3424 0.366448 39 0.191763 1.7575 0.041234 40 0.146759 1.3451 0.091111 41 0.074055 0.6787 0.24959 42 0.062382 0.5717 0.284512 43 0.046554 0.4267 0.335353 44 0.036388 0.3335 0.369794 45 0.064785 0.5938 0.277134 46 0.169812 1.5564 0.061692 47 0.041484 0.3802 0.352375 48 0.05479 0.5022 0.308434 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.3458 3.1693 0.001066 2 0.206408 1.8918 0.030984 3 -0.129453 -1.1865 0.119393 4 0.022199 0.2035 0.419634 5 0.046044 0.422 0.337051 6 -0.033736 -0.3092 0.37897 7 0.122051 1.1186 0.133247 8 -0.087027 -0.7976 0.213671 9 -0.004691 -0.043 0.482905 10 -0.12537 -1.149 0.126901 11 -0.090433 -0.8288 0.204774 12 -0.282244 -2.5868 0.005705 13 0.271699 2.4902 0.00737 14 -0.010304 -0.0944 0.462494 15 0.14493 1.3283 0.093838 16 -0.0544 -0.4986 0.309687 17 0.01745 0.1599 0.436661 18 -0.324462 -2.9737 0.001919 19 -0.184088 -1.6872 0.047638 20 -0.087606 -0.8029 0.212142 21 -0.215427 -1.9744 0.02581 22 -0.04073 -0.3733 0.354936 23 0.076881 0.7046 0.241496 24 -0.139906 -1.2823 0.101639 25 0.078858 0.7227 0.235921 26 0.046229 0.4237 0.336436 27 -0.131847 -1.2084 0.115143 28 0.136389 1.25 0.10738 29 -0.062564 -0.5734 0.28395 30 -0.083301 -0.7635 0.223663 31 -0.041354 -0.379 0.352816 32 -0.009959 -0.0913 0.463747 33 -0.028424 -0.2605 0.397553 34 -0.055441 -0.5081 0.306349 35 0.099302 0.9101 0.182682 36 -0.04687 -0.4296 0.334304 37 -0.014038 -0.1287 0.448967 38 0.04958 0.4544 0.325354 39 -0.010686 -0.0979 0.461106 40 0.025513 0.2338 0.407843 41 -0.056081 -0.514 0.304304 42 0.015632 0.1433 0.443209 43 -0.048417 -0.4437 0.329183 44 -0.033584 -0.3078 0.379498 45 -0.008583 -0.0787 0.468743 46 0.000235 0.0022 0.499142 47 -0.035638 -0.3266 0.37238 48 -0.112201 -1.0283 0.153371

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Apr/25/t1303741893yue794amonln2r0/15o1e1303742076.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/25/t1303741893yue794amonln2r0/15o1e1303742076.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/25/t1303741893yue794amonln2r0/2ukvi1303742076.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/25/t1303741893yue794amonln2r0/2ukvi1303742076.ps (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/25/t1303741893yue794amonln2r0/3r2291303742076.png (open in new window) http://www.freestatistics.org/blog/date/2011/Apr/25/t1303741893yue794amonln2r0/3r2291303742076.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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')

Copyright

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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