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Type 'q()' to quit R. > source('/home/pw/wessanet/cretab') > > > > myrfcuid = '' > > x <- c(112,118,132,129,121,135,148,148,136,119,104,118,115,126,141,135,125,149,170,170,158,133,114,140,145,150,178,163,172,178,199,199,184,162,146,166,171,180,193,181,183,218,230,242,209,191,172,194,196,196,236,235,229,243,264,272,237,211,180,201,204,188,235,227,234,264,302,293,259,229,203,229,242,233,267,269,270,315,364,347,312,274,237,278,284,277,317,313,318,374,413,405,355,306,271,306,315,301,356,348,355,422,465,467,404,347,305,336,340,318,362,348,363,435,491,505,404,359,310,337,360,342,406,396,420,472,548,559,463,407,362,405,417,391,419,461,472,535,622,606,508,461,390,432) > par10 = 'FALSE' > par9 = '0' > par8 = '0' > par7 = '0' > par6 = '0' > par5 = '1' > par4 = '0' > par3 = '0' > par2 = '1' > par1 = '0' > par10 <- 'FALSE' > par9 <- '0' > par8 <- '0' > par7 <- '0' > par6 <- '0' > par5 <- '1' > par4 <- '0' > par3 <- '0' > par2 <- '1' > par1 <- '0' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Wed, 16 Nov 2016 12:47:20 +0100) > #Author: root > #To cite this work: Wessa P., (2016), ARIMA Forecasting (v1.0.10) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_arimaforecasting.wasp/ > #Source of accompanying publication: > # > par1 <- as.numeric(par1) #cut off periods > par2 <- as.numeric(par2) #lambda > par3 <- as.numeric(par3) #degree of non-seasonal differencing > par4 <- as.numeric(par4) #degree of seasonal differencing > par5 <- as.numeric(par5) #seasonal period > par6 <- as.numeric(par6) #p > par7 <- as.numeric(par7) #q > par8 <- as.numeric(par8) #P > par9 <- as.numeric(par9) #Q > if (par10 == 'TRUE') par10 <- TRUE > if (par10 == 'FALSE') par10 <- FALSE > if (par2 == 0) x <- log(x) > if (par2 != 0) x <- x^par2 > lx <- length(x) > first <- lx - 2*par1 > nx <- lx - par1 > nx1 <- nx + 1 > fx <- lx - nx > if (fx < 1) { + fx <- par5*2 + nx1 <- lx + fx - 1 + first <- lx - 2*fx + } > first <- 1 > if (fx < 3) fx <- round(lx/10,0) > (arima.out <- arima(x[1:nx], order=c(par6,par3,par7), seasonal=list(order=c(par8,par4,par9), period=par5), include.mean=par10, method='ML')) Call: arima(x = x[1:nx], order = c(par6, par3, par7), seasonal = list(order = c(par8, par4, par9), period = par5), include.mean = par10, method = "ML") sigma^2 estimated as 92859: log likelihood = -1027.92, aic = 2057.85 > (forecast <- predict(arima.out,fx)) $pred Time Series: Start = 145 End = 158 Frequency = 1 [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 $se Time Series: Start = 145 End = 158 Frequency = 1 [1] 304.7282 304.7282 304.7282 304.7282 304.7282 304.7282 304.7282 304.7282 [9] 304.7282 304.7282 304.7282 304.7282 304.7282 304.7282 > (lb <- forecast$pred - 1.96 * forecast$se) Time Series: Start = 145 End = 158 Frequency = 1 [1] -597.2673 -597.2673 -597.2673 -597.2673 -597.2673 -597.2673 -597.2673 [8] -597.2673 -597.2673 -597.2673 -597.2673 -597.2673 -597.2673 -597.2673 > (ub <- forecast$pred + 1.96 * forecast$se) Time Series: Start = 145 End = 158 Frequency = 1 [1] 597.2673 597.2673 597.2673 597.2673 597.2673 597.2673 597.2673 597.2673 [9] 597.2673 597.2673 597.2673 597.2673 597.2673 597.2673 > if (par2 == 0) { + x <- exp(x) + forecast$pred <- exp(forecast$pred) + lb <- exp(lb) + ub <- exp(ub) + } > if (par2 != 0) { + x <- x^(1/par2) + forecast$pred <- forecast$pred^(1/par2) + lb <- lb^(1/par2) + ub <- ub^(1/par2) + } > if (par2 < 0) { + olb <- lb + lb <- ub + ub <- olb + } > (actandfor <- c(x[1:nx], forecast$pred)) [1] 112 118 132 129 121 135 148 148 136 119 104 118 115 126 141 135 125 149 [19] 170 170 158 133 114 140 145 150 178 163 172 178 199 199 184 162 146 166 [37] 171 180 193 181 183 218 230 242 209 191 172 194 196 196 236 235 229 243 [55] 264 272 237 211 180 201 204 188 235 227 234 264 302 293 259 229 203 229 [73] 242 233 267 269 270 315 364 347 312 274 237 278 284 277 317 313 318 374 [91] 413 405 355 306 271 306 315 301 356 348 355 422 465 467 404 347 305 336 [109] 340 318 362 348 363 435 491 505 404 359 310 337 360 342 406 396 420 472 [127] 548 559 463 407 362 405 417 391 419 461 472 535 622 606 508 461 390 432 [145] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > (perc.se <- (ub-forecast$pred)/1.96/forecast$pred) Time Series: Start = 145 End = 158 Frequency = 1 [1] Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf Inf > postscript(file="/home/pw/wessanet/rcomp/tmp/1181f1586315480.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mar=c(4,4,2,2),las=1) > ylim <- c( min(x[first:nx],lb), max(x[first:nx],ub)) > plot(x,ylim=ylim,type='n',xlim=c(first,lx)) > usr <- par('usr') > rect(usr[1],usr[3],nx+1,usr[4],border=NA,col='lemonchiffon') > rect(nx1,usr[3],usr[2],usr[4],border=NA,col='lavender') > abline(h= (-3:3)*2 , col ='gray', lty =3) > polygon( c(nx1:lx,lx:nx1), c(lb,rev(ub)), col = 'orange', lty=2,border=NA) Error in xy.coords(x, y, setLab = FALSE) : 'x' and 'y' lengths differ Calls: polygon -> xy.coords Execution halted