R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(40.7819
+ ,39.5915
+ ,38.8859
+ ,39.9068
+ ,41.47
+ ,41.5613
+ ,41.6005
+ ,41.4113
+ ,41.84
+ ,42.2892
+ ,43.1521
+ ,43.5998
+ ,43.116
+ ,42.4185
+ ,42.3687
+ ,42.2975
+ ,42.8528
+ ,43.535
+ ,44.7265
+ ,45.7293
+ ,45.7585
+ ,46.1685
+ ,46.5075
+ ,46.527
+ ,46.601
+ ,46.4607
+ ,46.7135
+ ,46.4113
+ ,45.55
+ ,44.6081
+ ,44.4395
+ ,44.9847
+ ,45.7558
+ ,45.3942
+ ,45.697
+ ,45.5664
+ ,46.0205
+ ,45.9195
+ ,45.8005
+ ,45.535
+ ,45.4977
+ ,45.5782
+ ,45.7697
+ ,45.2445
+ ,45.0615
+ ,45.2865
+ ,44.791
+ ,44.7625
+ ,44.7644
+ ,44.9973
+ ,44.7265
+ ,45.1465
+ ,44.7465
+ ,45.1795
+ ,45.6515
+ ,45.492
+ ,45.2775
+ ,45.2115
+ ,45.411
+ ,45.4005
+ ,44.7692
+ ,44.8913
+ ,45.032
+ ,44.879
+ ,44.833
+ ,44.8257
+ ,44.7815
+ ,44.479
+ ,44.6317
+ ,44.5043
+ ,44.3217
+ ,44.1005
+ ,44.047
+ ,43.6835
+ ,43.7864
+ ,44.1807
+ ,43.9595
+ ,43.937
+ ,43.991
+ ,43.865
+ ,43.671
+ ,43.93
+ ,43.863
+ ,43.7095
+ ,43.9435
+ ,43.736
+ ,43.6295
+ ,43.598
+ ,43.8726
+ ,43.8935
+ ,43.5957
+ ,43.7155
+ ,43.528
+ ,43.3415
+ ,43.3374
+ ,43.332
+ ,43.3869
+ ,43.5016
+ ,43.4875
+ ,43.6023
+ ,43.3886
+ ,43.3105
+ ,43.4455
+ ,43.5185
+ ,43.5755
+ ,43.6217
+ ,43.644
+ ,43.5789
+ ,43.5215
+ ,43.5033
+ ,43.632
+ ,43.263
+ ,43.3717
+ ,43.2745
+ ,43.2647
+ ,43.324
+ ,43.4455
+ ,43.4098
+ ,43.41
+ ,43.93
+ ,43.8104
+ ,43.54
+ ,43.858
+ ,43.8375
+ ,43.881
+ ,43.887
+ ,43.8009
+ ,43.7877
+ ,43.811
+ ,44.0625
+ ,44.125
+ ,44.52
+ ,45.4005
+ ,45.89
+ ,45.189
+ ,44.9035
+ ,44.9351
+ ,44.801
+ ,43.98
+ ,44.11
+ ,44.2661
+ ,44.361
+ ,44.099
+ ,43.8435
+ ,43.8914
+ ,44.217
+ ,44.506
+ ,44.54
+ ,44.4465
+ ,44.842
+ ,44.8946
+ ,44.951
+ ,45.445
+ ,45.0035
+ ,45.769
+ ,46.09
+ ,45.412
+ ,45.12
+ ,45.48
+ ,45.105
+ ,45.056
+ ,45.22
+ ,45.39
+ ,45.041
+ ,44.9399
+ ,44.9315
+ ,45.1935
+ ,45.3466
+ ,45.4645
+ ,45.5685
+ ,45.3921
+ ,45.34
+ ,45.1308
+ ,45.1005
+ ,45.37
+ ,45.2
+ ,44.9614
+ ,44.8015
+ ,44.9152
+ ,45.095
+ ,44.9271
+ ,44.6026
+ ,44.5
+ ,44.54
+ ,44.5532
+ ,44.407
+ ,44.259
+ ,44.1365
+ ,44.112
+ ,43.8814
+ ,43.98
+ ,43.7294
+ ,43.9119
+ ,43.955
+ ,43.9
+ ,43.7065
+ ,43.6939
+ ,43.6587
+ ,43.5885
+ ,43.8885
+ ,43.8216
+ ,43.751
+ ,43.699
+ ,43.7425
+ ,43.639
+ ,43.589
+ ,43.606
+ ,43.5325
+ ,43.385
+ ,43.3745
+ ,43.236
+ ,43.1957
+ ,43.01
+ ,43.1401
+ ,43.0487
+ ,43.1972
+ ,43.2461
+ ,43.0866
+ ,43.0865
+ ,43.0194
+ ,43.08
+ ,43.007
+ ,42.9278
+ ,42.9545
+ ,42.7995
+ ,42.9048
+ ,42.9468
+ ,43.08
+ ,43.1274
+ ,43.1625
+ ,43.45
+ ,43.831
+ ,43.7769
+ ,43.98
+ ,43.92
+ ,44.11
+ ,44.03
+ ,44.1582
+ ,44.14
+ ,45.07
+ ,44.8737
+ ,44.8505
+ ,44.373
+ ,44.075
+ ,43.9725
+ ,44.094
+ ,44.191
+ ,43.9685
+ ,43.79
+ ,43.6041
+ ,43.1707
+ ,42.71
+ ,42.755
+ ,43.3316
+ ,43.5
+ ,43.154
+ ,43.16
+ ,43.1
+ ,42.85
+ ,42.6175
+ ,42.5
+ ,42.6285
+ ,42.6974
+ ,43.04
+ ,42.673
+ ,42.5015
+ ,42.538
+ ,42.3735
+ ,42.014
+ ,41.8618
+ ,42.1824
+ ,42.605
+ ,42.7345
+ ,42.615
+ ,42.465
+ ,42.34
+ ,42.251
+ ,42.0475
+ ,41.86
+ ,41.685
+ ,41.735
+ ,41.706
+ ,41.764
+ ,41.58
+ ,41.373
+ ,41.088
+ ,41.137
+ ,41.1587
+ ,41.185
+ ,40.819
+ ,40.633
+ ,40.858
+ ,40.794
+ ,40.69
+ ,40.595
+ ,40.7305
+ ,40.5471
+ ,40.5145
+ ,40.7
+ ,40.7
+ ,40.522
+ ,40.6165
+ ,40.3985
+ ,40.2815
+ ,40.245
+ ,40.3055
+ ,40.2696
+ ,40.251
+ ,40.127
+ ,39.95
+ ,39.675
+ ,39.954
+ ,39.8828
+ ,39.62
+ ,39.5415
+ ,39.525
+ ,39.8145
+ ,39.6675
+ ,39.695
+ ,39.5985
+ ,39.2735
+ ,39.1435
+ ,39.1742
+ ,39.2025
+ ,39.3946
+ ,39.5025
+ ,39.4845
+ ,39.33
+ ,39.295
+ ,39.2675
+ ,39.2535
+ ,38.9845
+ ,38.9285
+ ,38.8592
+ ,38.77
+ ,38.79
+ ,38.8205
+ ,38.7577
+ ,38.839
+ ,38.78
+ ,38.54
+ ,38.511
+ ,38.615
+ ,38.898
+ ,38.8691
+ ,38.384
+ ,38.0277
+ ,37.72
+ ,37.7325
+ ,37.626
+ ,37.603
+ ,37.78
+ ,38.559
+ ,39.0459
+ ,38.45
+ ,38.505
+ ,38.2885
+ ,37.795
+ ,37.92
+ ,38.034
+ ,38.029
+ ,38.063
+ ,37.9828
+ ,37.745
+ ,37.969
+ ,38.007
+ ,38.0615
+ ,38.0912
+ ,38.091
+ ,38.431
+ ,38.48
+ ,38.35
+ ,38.214
+ ,38.384
+ ,38.1375
+ ,38.0075
+ ,38.0524
+ ,38.235
+ ,38.31
+ ,38.2615
+ ,38.13
+ ,38.282
+ ,38.581
+ ,39.0801
+ ,39.0387
+ ,39.1015
+ ,39.1503
+ ,39.14
+ ,39.0275
+ ,38.7665
+ ,38.691
+ ,38.849
+ ,39.1644
+ ,39.4907
+ ,39.5095
+ ,39.2795
+ ,39.0437
+ ,39.1355
+ ,39.143
+ ,39.185
+ ,39.355
+ ,39.297
+ ,39.4514
+ ,39.4173
+ ,39.4305
+ ,39.384
+ ,39.3261
+ ,39.301
+ ,39.35
+ ,39.64
+ ,39.4723
+ ,39.3685
+ ,39.1906
+ ,39.1183
+ ,39.1325
+ ,39.1144
+ ,39.1614
+ ,39.0908
+ ,38.9199
+ ,38.913
+ ,38.9655
+ ,39.029
+ ,39.089
+ ,39.07
+ ,39.0046
+ ,39.1038
+ ,39.3572
+ ,39.388
+ ,39.382
+ ,39.4398
+ ,39.2537
+ ,39.2301
+ ,39.2763
+ ,39.282
+ ,39.3325
+ ,39.557
+ ,40.1
+ ,40.5875
+ ,40.485
+ ,40.55
+ ,40.7955
+ ,41.456
+ ,41.3557
+ ,41.374
+ ,41.2235
+ ,41.15
+ ,41.3725
+ ,41.6923
+ ,41.8
+ ,41.8045
+ ,41.64
+ ,41.36
+ ,41.5745
+ ,41.593
+ ,41.575
+ ,41.68
+ ,42.0055
+ ,42.3188
+ ,42.565
+ ,42.3575
+ ,42.29
+ ,42.695
+ ,43.0028
+ ,42.4507
+ ,42.4705
+ ,42.2875
+ ,42.3172
+ ,42.55
+ ,42.7523
+ ,42.8993
+ ,43.1555
+ ,43.1885
+ ,43.43
+ ,43.31
+ ,42.815
+ ,42.7017
+ ,42.28
+ ,41.922
+ ,42.17
+ ,42.1962
+ ,42.3215
+ ,42.3173
+ ,42.391
+ ,42.463
+ ,42.4125
+ ,42.304
+ ,41.813
+ ,41.651
+ ,41.539
+ ,41.1575
+ ,40.9545)
> par10 = 'FALSE'
> par9 = '0'
> par8 = '0'
> par7 = '1'
> par6 = '3'
> par5 = '1'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '15'
> 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 <- 5 #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
+ 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")

Coefficients:
          ar1     ar2      ar3     ma1
      -0.4702  0.0534  -0.1944  0.7503
s.e.   0.1406  0.0616   0.0470  0.1358

sigma^2 estimated as 0.06918:  log likelihood = -39.69,  aic = 89.37
> (forecast <- predict(arima.out,par1))
$pred
Time Series:
Start = 477 
End = 491 
Frequency = 1 
 [1] 42.77910 42.83289 42.83375 42.82117 42.81668 42.81795 42.81956 42.81974
 [9] 42.81949 42.81931 42.81935 42.81937 42.81940 42.81938 42.81938

$se
Time Series:
Start = 477 
End = 491 
Frequency = 1 
 [1] 0.2630116 0.4272308 0.5314453 0.6000289 0.6624777 0.7199007 0.7756342
 [8] 0.8263555 0.8747614 0.9198668 0.9634429 1.0047270 1.0447220 1.0829657
[15] 1.1201170

> (lb <- forecast$pred - 1.96 * forecast$se)
Time Series:
Start = 477 
End = 491 
Frequency = 1 
 [1] 42.26360 41.99551 41.79212 41.64511 41.51822 41.40694 41.29931 41.20009
 [9] 41.10496 41.01637 40.93100 40.85010 40.77174 40.69676 40.62395
> (ub <- forecast$pred + 1.96 * forecast$se)
Time Series:
Start = 477 
End = 491 
Frequency = 1 
 [1] 43.29460 43.67026 43.87539 43.99723 44.11513 44.22895 44.33980 44.43940
 [9] 44.53403 44.62225 44.70769 44.78863 44.86705 44.94199 45.01481
> 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] 40.78190 39.59150 38.88590 39.90680 41.47000 41.56130 41.60050 41.41130
  [9] 41.84000 42.28920 43.15210 43.59980 43.11600 42.41850 42.36870 42.29750
 [17] 42.85280 43.53500 44.72650 45.72930 45.75850 46.16850 46.50750 46.52700
 [25] 46.60100 46.46070 46.71350 46.41130 45.55000 44.60810 44.43950 44.98470
 [33] 45.75580 45.39420 45.69700 45.56640 46.02050 45.91950 45.80050 45.53500
 [41] 45.49770 45.57820 45.76970 45.24450 45.06150 45.28650 44.79100 44.76250
 [49] 44.76440 44.99730 44.72650 45.14650 44.74650 45.17950 45.65150 45.49200
 [57] 45.27750 45.21150 45.41100 45.40050 44.76920 44.89130 45.03200 44.87900
 [65] 44.83300 44.82570 44.78150 44.47900 44.63170 44.50430 44.32170 44.10050
 [73] 44.04700 43.68350 43.78640 44.18070 43.95950 43.93700 43.99100 43.86500
 [81] 43.67100 43.93000 43.86300 43.70950 43.94350 43.73600 43.62950 43.59800
 [89] 43.87260 43.89350 43.59570 43.71550 43.52800 43.34150 43.33740 43.33200
 [97] 43.38690 43.50160 43.48750 43.60230 43.38860 43.31050 43.44550 43.51850
[105] 43.57550 43.62170 43.64400 43.57890 43.52150 43.50330 43.63200 43.26300
[113] 43.37170 43.27450 43.26470 43.32400 43.44550 43.40980 43.41000 43.93000
[121] 43.81040 43.54000 43.85800 43.83750 43.88100 43.88700 43.80090 43.78770
[129] 43.81100 44.06250 44.12500 44.52000 45.40050 45.89000 45.18900 44.90350
[137] 44.93510 44.80100 43.98000 44.11000 44.26610 44.36100 44.09900 43.84350
[145] 43.89140 44.21700 44.50600 44.54000 44.44650 44.84200 44.89460 44.95100
[153] 45.44500 45.00350 45.76900 46.09000 45.41200 45.12000 45.48000 45.10500
[161] 45.05600 45.22000 45.39000 45.04100 44.93990 44.93150 45.19350 45.34660
[169] 45.46450 45.56850 45.39210 45.34000 45.13080 45.10050 45.37000 45.20000
[177] 44.96140 44.80150 44.91520 45.09500 44.92710 44.60260 44.50000 44.54000
[185] 44.55320 44.40700 44.25900 44.13650 44.11200 43.88140 43.98000 43.72940
[193] 43.91190 43.95500 43.90000 43.70650 43.69390 43.65870 43.58850 43.88850
[201] 43.82160 43.75100 43.69900 43.74250 43.63900 43.58900 43.60600 43.53250
[209] 43.38500 43.37450 43.23600 43.19570 43.01000 43.14010 43.04870 43.19720
[217] 43.24610 43.08660 43.08650 43.01940 43.08000 43.00700 42.92780 42.95450
[225] 42.79950 42.90480 42.94680 43.08000 43.12740 43.16250 43.45000 43.83100
[233] 43.77690 43.98000 43.92000 44.11000 44.03000 44.15820 44.14000 45.07000
[241] 44.87370 44.85050 44.37300 44.07500 43.97250 44.09400 44.19100 43.96850
[249] 43.79000 43.60410 43.17070 42.71000 42.75500 43.33160 43.50000 43.15400
[257] 43.16000 43.10000 42.85000 42.61750 42.50000 42.62850 42.69740 43.04000
[265] 42.67300 42.50150 42.53800 42.37350 42.01400 41.86180 42.18240 42.60500
[273] 42.73450 42.61500 42.46500 42.34000 42.25100 42.04750 41.86000 41.68500
[281] 41.73500 41.70600 41.76400 41.58000 41.37300 41.08800 41.13700 41.15870
[289] 41.18500 40.81900 40.63300 40.85800 40.79400 40.69000 40.59500 40.73050
[297] 40.54710 40.51450 40.70000 40.70000 40.52200 40.61650 40.39850 40.28150
[305] 40.24500 40.30550 40.26960 40.25100 40.12700 39.95000 39.67500 39.95400
[313] 39.88280 39.62000 39.54150 39.52500 39.81450 39.66750 39.69500 39.59850
[321] 39.27350 39.14350 39.17420 39.20250 39.39460 39.50250 39.48450 39.33000
[329] 39.29500 39.26750 39.25350 38.98450 38.92850 38.85920 38.77000 38.79000
[337] 38.82050 38.75770 38.83900 38.78000 38.54000 38.51100 38.61500 38.89800
[345] 38.86910 38.38400 38.02770 37.72000 37.73250 37.62600 37.60300 37.78000
[353] 38.55900 39.04590 38.45000 38.50500 38.28850 37.79500 37.92000 38.03400
[361] 38.02900 38.06300 37.98280 37.74500 37.96900 38.00700 38.06150 38.09120
[369] 38.09100 38.43100 38.48000 38.35000 38.21400 38.38400 38.13750 38.00750
[377] 38.05240 38.23500 38.31000 38.26150 38.13000 38.28200 38.58100 39.08010
[385] 39.03870 39.10150 39.15030 39.14000 39.02750 38.76650 38.69100 38.84900
[393] 39.16440 39.49070 39.50950 39.27950 39.04370 39.13550 39.14300 39.18500
[401] 39.35500 39.29700 39.45140 39.41730 39.43050 39.38400 39.32610 39.30100
[409] 39.35000 39.64000 39.47230 39.36850 39.19060 39.11830 39.13250 39.11440
[417] 39.16140 39.09080 38.91990 38.91300 38.96550 39.02900 39.08900 39.07000
[425] 39.00460 39.10380 39.35720 39.38800 39.38200 39.43980 39.25370 39.23010
[433] 39.27630 39.28200 39.33250 39.55700 40.10000 40.58750 40.48500 40.55000
[441] 40.79550 41.45600 41.35570 41.37400 41.22350 41.15000 41.37250 41.69230
[449] 41.80000 41.80450 41.64000 41.36000 41.57450 41.59300 41.57500 41.68000
[457] 42.00550 42.31880 42.56500 42.35750 42.29000 42.69500 43.00280 42.45070
[465] 42.47050 42.28750 42.31720 42.55000 42.75230 42.89930 43.15550 43.18850
[473] 43.43000 43.31000 42.81500 42.70170 42.77910 42.83289 42.83375 42.82117
[481] 42.81668 42.81795 42.81956 42.81974 42.81949 42.81931 42.81935 42.81937
[489] 42.81940 42.81938 42.81938
> (perc.se <- (ub-forecast$pred)/1.96/forecast$pred)
Time Series:
Start = 477 
End = 491 
Frequency = 1 
 [1] 0.006148134 0.009974363 0.012407161 0.014012437 0.015472423 0.016813059
 [7] 0.018114017 0.019298469 0.020429045 0.021482524 0.022500178 0.023464312
[13] 0.024398335 0.025291487 0.026159111
> postscript(file="/var/www/html/rcomp/tmp/1hac01293295238.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> opar <- par(mar=c(4,4,2,2),las=1)
> ylim <- c( min(x[first:nx],lb), max(x[first:nx],ub))
> plot(x,ylim=ylim,type='n',xlim=c(first,lx))
> usr <- par('usr')
> rect(usr[1],usr[3],nx+1,usr[4],border=NA,col='lemonchiffon')
> rect(nx1,usr[3],usr[2],usr[4],border=NA,col='lavender')
> abline(h= (-3:3)*2 , col ='gray', lty =3)
> polygon( c(nx1:lx,lx:nx1), c(lb,rev(ub)), col = 'orange', lty=2,border=NA)
> lines(nx1:lx, lb , lty=2)
> lines(nx1:lx, ub , lty=2)
> lines(x, lwd=2)
> lines(nx1:lx, forecast$pred , lwd=2 , col ='white')
> box()
> par(opar)
> dev.off()
null device 
          1 
> prob.dec <- array(NA, dim=fx)
> prob.sdec <- array(NA, dim=fx)
> prob.ldec <- array(NA, dim=fx)
> prob.pval <- array(NA, dim=fx)
> perf.pe <- array(0, dim=fx)
> perf.mape <- array(0, dim=fx)
> perf.mape1 <- array(0, dim=fx)
> perf.se <- array(0, dim=fx)
> perf.mse <- array(0, dim=fx)
> perf.mse1 <- array(0, dim=fx)
> perf.rmse <- array(0, dim=fx)
> for (i in 1:fx) {
+ locSD <- (ub[i] - forecast$pred[i]) / 1.96
+ perf.pe[i] = (x[nx+i] - forecast$pred[i]) / forecast$pred[i]
+ perf.se[i] = (x[nx+i] - forecast$pred[i])^2
+ prob.dec[i] = pnorm((x[nx+i-1] - forecast$pred[i]) / locSD)
+ prob.sdec[i] = pnorm((x[nx+i-par5] - forecast$pred[i]) / locSD)
+ prob.ldec[i] = pnorm((x[nx] - forecast$pred[i]) / locSD)
+ prob.pval[i] = pnorm(abs(x[nx+i] - forecast$pred[i]) / locSD)
+ }
> perf.mape[1] = abs(perf.pe[1])
> perf.mse[1] = abs(perf.se[1])
> for (i in 2:fx) {
+ perf.mape[i] = perf.mape[i-1] + abs(perf.pe[i])
+ perf.mape1[i] = perf.mape[i] / i
+ perf.mse[i] = perf.mse[i-1] + perf.se[i]
+ perf.mse1[i] = perf.mse[i] / i
+ }
> perf.rmse = sqrt(perf.mse1)
> postscript(file="/var/www/html/rcomp/tmp/25b9t1293295238.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(forecast$pred, pch=19, type='b',main='ARIMA Extrapolation Forecast', ylab='Forecast and 95% CI', xlab='time',ylim=c(min(lb),max(ub)))
> dum <- forecast$pred
> dum[1:par1] <- x[(nx+1):lx]
> lines(dum, lty=1)
> lines(ub,lty=3)
> lines(lb,lty=3)
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Univariate ARIMA Extrapolation Forecast',9,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'time',1,header=TRUE)
> a<-table.element(a,'Y[t]',1,header=TRUE)
> a<-table.element(a,'F[t]',1,header=TRUE)
> a<-table.element(a,'95% LB',1,header=TRUE)
> a<-table.element(a,'95% UB',1,header=TRUE)
> a<-table.element(a,'p-value<br />(H0: Y[t] = F[t])',1,header=TRUE)
> a<-table.element(a,'P(F[t]>Y[t-1])',1,header=TRUE)
> a<-table.element(a,'P(F[t]>Y[t-s])',1,header=TRUE)
> mylab <- paste('P(F[t]>Y[',nx,sep='')
> mylab <- paste(mylab,'])',sep='')
> a<-table.element(a,mylab,1,header=TRUE)
> a<-table.row.end(a)
> for (i in (nx-par5):nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,'-')
+ a<-table.element(a,'-')
+ a<-table.element(a,'-')
+ a<-table.element(a,'-')
+ a<-table.element(a,'-')
+ a<-table.element(a,'-')
+ a<-table.element(a,'-')
+ a<-table.row.end(a)
+ }
> for (i in 1:fx) {
+ a<-table.row.start(a)
+ a<-table.element(a,nx+i,header=TRUE)
+ a<-table.element(a,round(x[nx+i],4))
+ a<-table.element(a,round(forecast$pred[i],4))
+ a<-table.element(a,round(lb[i],4))
+ a<-table.element(a,round(ub[i],4))
+ a<-table.element(a,round((1-prob.pval[i]),4))
+ a<-table.element(a,round((1-prob.dec[i]),4))
+ a<-table.element(a,round((1-prob.sdec[i]),4))
+ a<-table.element(a,round((1-prob.ldec[i]),4))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3nm9i1293295239.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Univariate ARIMA Extrapolation Forecast Performance',7,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'time',1,header=TRUE)
> a<-table.element(a,'% S.E.',1,header=TRUE)
> a<-table.element(a,'PE',1,header=TRUE)
> a<-table.element(a,'MAPE',1,header=TRUE)
> a<-table.element(a,'Sq.E',1,header=TRUE)
> a<-table.element(a,'MSE',1,header=TRUE)
> a<-table.element(a,'RMSE',1,header=TRUE)
> a<-table.row.end(a)
> for (i in 1:fx) {
+ a<-table.row.start(a)
+ a<-table.element(a,nx+i,header=TRUE)
+ a<-table.element(a,round(perc.se[i],4))
+ a<-table.element(a,round(perf.pe[i],4))
+ a<-table.element(a,round(perf.mape1[i],4))
+ a<-table.element(a,round(perf.se[i],4))
+ a<-table.element(a,round(perf.mse1[i],4))
+ a<-table.element(a,round(perf.rmse[i],4))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4q4751293295239.tab") 
> 
> try(system("convert tmp/1hac01293295238.ps tmp/1hac01293295238.png",intern=TRUE))
character(0)
> try(system("convert tmp/25b9t1293295238.ps tmp/25b9t1293295238.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.998   0.349   2.133