diff --git a/man/wa.Rd b/man/wa.Rd index 3aa4143..ac420d3 100644 --- a/man/wa.Rd +++ b/man/wa.Rd @@ -162,7 +162,7 @@ waFit(x, y, tol.dw, useN2, deshrink, na.tol, small.tol, \author{Gavin L. Simpson and Jari Oksanen} \seealso{\code{\link{mat}} for an alternative transfer function method.} \examples{ -\testonly{od <- options(digits = 5)} +\testonly{od <- options(digits = 4)} data(ImbrieKipp) data(SumSST) diff --git a/tests/Examples/analogue-Ex.Rout.save b/tests/Examples/analogue-Ex.Rout.save index 15788bf..0fbf5d0 100644 --- a/tests/Examples/analogue-Ex.Rout.save +++ b/tests/Examples/analogue-Ex.Rout.save @@ -7212,7 +7212,7 @@ Eigenvalues for unconstrained axes: > ### ** Examples > > ## Don't show: -> od <- options(digits = 5) +> od <- options(digits = 4) > ## End(Don't show) > data(ImbrieKipp) > data(SumSST) @@ -7239,44 +7239,44 @@ Performance: > ## extract the fitted values > fitted(mod) V14.61 V17.196 V18.110 V16.227 V14.47 V23.22 V2.12 V23.29 - 3.7310 3.8599 4.1077 4.2939 8.2876 9.2444 4.0761 13.8155 + 3.731 3.860 4.108 4.294 8.288 9.244 4.076 13.815 V12.43 R9.7 A157.3 V23.81 V23.82 V12.53 V23.83 V12.56 - 14.3345 16.5213 15.8044 18.7365 18.2896 18.4587 17.3886 20.4020 + 14.335 16.521 15.804 18.737 18.290 18.459 17.389 20.402 A152.84 V16.50 V22.122 V16.41 V4.32 V12.66 V19.245 V4.8 - 19.9694 19.7086 18.7815 22.7892 22.4079 20.7855 22.4544 22.1814 + 19.969 19.709 18.782 22.789 22.408 20.785 22.454 22.181 A180.15 V18.34 V20.213 V19.222 A180.39 V16.189 V12.18 V7.67 - 21.5623 23.3379 23.3608 22.8445 24.2193 25.6257 25.4988 23.3779 + 21.562 23.338 23.361 22.845 24.219 25.626 25.499 23.378 V17.165 V19.310 V16.190 A153.154 V19.308 V22.172 V10.98 V22.219 - 23.7472 23.1125 24.5166 25.3837 25.7968 26.2585 24.1625 25.4644 + 23.747 23.112 24.517 25.384 25.797 26.258 24.162 25.464 V16.33 V22.204 V20.167 V10.89 V12.79 V19.216 V14.90 A180.72 - 26.2402 25.8240 26.6780 26.3945 26.0913 25.7191 25.8627 26.3385 + 26.240 25.824 26.678 26.395 26.091 25.719 25.863 26.339 V16.21 A180.76 V15.164 A180.78 V14.5 V3.128 A179.13 V9.31 - 26.7898 26.6969 26.8217 25.9874 26.8824 26.9062 26.5153 26.0680 + 26.790 26.697 26.822 25.987 26.882 26.906 26.515 26.068 V20.230 V20.7 V20.234 V18.21 V12.122 - 26.6088 27.2316 26.7654 26.9459 26.8330 + 26.609 27.232 26.765 26.946 26.833 > > ## residuals for the training set > residuals(mod) - V14.61 V17.196 V18.110 V16.227 V14.47 V23.22 V2.12 V23.29 --1.730960 1.140079 1.392336 2.706094 -1.287580 1.255591 6.923869 -3.815481 - V12.43 R9.7 A157.3 V23.81 V23.82 V12.53 V23.83 V12.56 --1.334514 -4.521301 -1.804396 -4.236542 -3.289596 -3.958708 -1.388560 -2.401983 - A152.84 V16.50 V22.122 V16.41 V4.32 V12.66 V19.245 V4.8 - 0.030579 -1.708591 0.218460 -4.289225 -0.907882 0.214508 -1.454368 1.818595 - A180.15 V18.34 V20.213 V19.222 A180.39 V16.189 V12.18 V7.67 - 2.437667 -0.337938 0.639214 0.155458 -1.219277 -1.625657 -0.498810 2.622087 - V17.165 V19.310 V16.190 A153.154 V19.308 V22.172 V10.98 V22.219 - 2.252766 2.887535 0.483422 0.616261 0.203160 -1.758495 2.837538 0.735556 - V16.33 V22.204 V20.167 V10.89 V12.79 V19.216 V14.90 A180.72 --1.240175 0.675969 -0.477965 -0.394526 -0.091336 1.280861 1.137318 1.161456 - V16.21 A180.76 V15.164 A180.78 V14.5 V3.128 A179.13 V9.31 - 0.210242 0.303094 0.178331 1.012626 0.117565 2.093765 1.984665 1.432030 - V20.230 V20.7 V20.234 V18.21 V12.122 - 0.891171 0.268358 0.234590 0.054063 1.166988 + V14.61 V17.196 V18.110 V16.227 V14.47 V23.22 V2.12 V23.29 +-1.73096 1.14008 1.39234 2.70609 -1.28758 1.25559 6.92387 -3.81548 + V12.43 R9.7 A157.3 V23.81 V23.82 V12.53 V23.83 V12.56 +-1.33451 -4.52130 -1.80440 -4.23654 -3.28960 -3.95871 -1.38856 -2.40198 + A152.84 V16.50 V22.122 V16.41 V4.32 V12.66 V19.245 V4.8 + 0.03058 -1.70859 0.21846 -4.28923 -0.90788 0.21451 -1.45437 1.81859 + A180.15 V18.34 V20.213 V19.222 A180.39 V16.189 V12.18 V7.67 + 2.43767 -0.33794 0.63921 0.15546 -1.21928 -1.62566 -0.49881 2.62209 + V17.165 V19.310 V16.190 A153.154 V19.308 V22.172 V10.98 V22.219 + 2.25277 2.88753 0.48342 0.61626 0.20316 -1.75849 2.83754 0.73556 + V16.33 V22.204 V20.167 V10.89 V12.79 V19.216 V14.90 A180.72 +-1.24017 0.67597 -0.47797 -0.39453 -0.09134 1.28086 1.13732 1.16146 + V16.21 A180.76 V15.164 A180.78 V14.5 V3.128 A179.13 V9.31 + 0.21024 0.30309 0.17833 1.01263 0.11757 2.09377 1.98466 1.43203 + V20.230 V20.7 V20.234 V18.21 V12.122 + 0.89117 0.26836 0.23459 0.05406 1.16699 > > ## deshrinking coefficients > coef(mod) -[1] -5.6876 1.2659 +[1] -5.688 1.266 > > ## diagnostics plots > par(mfrow = c(1,2)) @@ -7317,17 +7317,17 @@ Performance: > ## compare actual tolerances to working values > with(mod2, rbind(tolerances, model.tol)) O.univ G.cglob G.ruber G.tenel G.saccu G.rubes G.pacL G.pacR G.bullo -tolerances 3.7464 1.8956 1.9096 2.1248 1.9797 1.9683 3.9414 5.1812 5.828 -model.tol 3.7464 2.1248 2.1248 2.1248 2.1248 2.1248 3.9414 5.1812 5.828 +tolerances 3.746 1.896 1.910 2.125 1.980 1.968 3.941 5.181 5.828 +model.tol 3.746 2.125 2.125 2.125 2.125 2.125 3.941 5.181 5.828 G.falco G.calid G.aequi G.gluti G.duter G.infla G.trnL G.trnR -tolerances 3.1092 2.9731 2.5617 5.8983 1.9983 4.7239 4.1617 3.4349 -model.tol 3.1092 2.9731 2.5617 5.8983 2.1248 4.7239 4.1617 3.4349 - G.crasf G.scitu G.mentu P.obliq C.nitid S.dehis G.digit Other -tolerances 3.354 3.9907 2.3866 1.5548 1.4617 3.8447 3.1089 5.1125 -model.tol 3.354 3.9907 2.3866 2.1248 2.1248 3.8447 3.1089 5.1125 - G.quin G.hirsu -tolerances 4.2688 3.9421 -model.tol 4.2688 3.9421 +tolerances 3.109 2.973 2.562 5.898 1.998 4.724 4.162 3.435 +model.tol 3.109 2.973 2.562 5.898 2.125 4.724 4.162 3.435 + G.crasf G.scitu G.mentu P.obliq C.nitid S.dehis G.digit Other G.quin +tolerances 3.354 3.991 2.387 1.555 1.462 3.845 3.109 5.112 4.269 +model.tol 3.354 3.991 2.387 2.125 2.125 3.845 3.109 5.112 4.269 + G.hirsu +tolerances 3.942 +model.tol 3.942 > > ## tolerance DW > mod3 <- wa(SumSST ~ ., data = ImbrieKipp, tol.dw = TRUE, @@ -7373,40 +7373,40 @@ Performance: > ## extract the fitted values > fitted(mod4) V14.61 V17.196 V18.110 V16.227 V14.47 V23.22 V2.12 V23.29 - 5.8985 5.9591 6.0758 6.1635 8.1265 8.6414 6.0609 11.5633 + 5.898 5.959 6.076 6.164 8.127 8.641 6.061 11.563 V12.43 R9.7 A157.3 V23.81 V23.82 V12.53 V23.83 V12.56 - 11.9710 14.0109 13.2762 16.8040 16.1689 16.4046 15.0028 19.3976 + 11.971 14.011 13.276 16.804 16.169 16.405 15.003 19.398 A152.84 V16.50 V22.122 V16.41 V4.32 V12.66 V19.245 V4.8 - 18.7065 18.2923 16.8700 22.9403 22.4278 20.0083 22.4915 22.1128 + 18.707 18.292 16.870 22.940 22.428 20.008 22.492 22.113 A180.15 V18.34 V20.213 V19.222 A180.39 V16.189 V12.18 V7.67 - 21.2115 23.6373 23.6652 23.0128 24.6599 26.0993 25.9754 23.6862 + 21.211 23.637 23.665 23.013 24.660 26.099 25.975 23.686 V17.165 V19.310 V16.190 A153.154 V19.308 V22.172 V10.98 V22.219 - 24.1262 23.3567 24.9810 25.8625 26.2661 26.7165 24.5973 25.9417 + 24.126 23.357 24.981 25.863 26.266 26.716 24.597 25.942 V16.33 V22.204 V20.167 V10.89 V12.79 V19.216 V14.90 A180.72 - 26.6986 26.2926 27.1273 26.8495 26.5532 26.1904 26.3303 26.7948 + 26.699 26.293 27.127 26.850 26.553 26.190 26.330 26.795 V16.21 A180.76 V15.164 A180.78 V14.5 V3.128 A179.13 V9.31 - 27.2370 27.1459 27.2683 26.4518 27.3279 27.3512 26.9679 26.5304 + 27.237 27.146 27.268 26.452 27.328 27.351 26.968 26.530 V20.230 V20.7 V20.234 V18.21 V12.122 - 27.0595 27.6704 27.2131 27.3901 27.2794 + 27.060 27.670 27.213 27.390 27.279 > > ## residuals for the training set > residuals(mod4) - V14.61 V17.196 V18.110 V16.227 V14.47 V23.22 V2.12 V23.29 --3.898451 -0.959142 -0.575776 0.836468 -1.126549 1.858557 4.939074 -1.563327 - V12.43 R9.7 A157.3 V23.81 V23.82 V12.53 V23.83 V12.56 - 1.029013 -2.010916 0.723792 -2.303976 -1.168939 -1.904646 0.997217 -1.397640 - A152.84 V16.50 V22.122 V16.41 V4.32 V12.66 V19.245 V4.8 - 1.293463 -0.292346 2.130001 -4.440318 -0.927838 0.991727 -1.491527 1.887240 - A180.15 V18.34 V20.213 V19.222 A180.39 V16.189 V12.18 V7.67 - 2.788500 -0.637275 0.334750 -0.012758 -1.659931 -2.099307 -0.975387 2.313835 - V17.165 V19.310 V16.190 A153.154 V19.308 V22.172 V10.98 V22.219 - 1.873805 2.643276 0.019001 0.137472 -0.266124 -2.216472 2.402708 0.258265 - V16.33 V22.204 V20.167 V10.89 V12.79 V19.216 V14.90 A180.72 --1.698566 0.207389 -0.927317 -0.849545 -0.553215 0.809566 0.669733 0.705244 - V16.21 A180.76 V15.164 A180.78 V14.5 V3.128 A179.13 V9.31 --0.236962 -0.145893 -0.268262 0.548197 -0.327863 1.648793 1.532122 0.969585 - V20.230 V20.7 V20.234 V18.21 V12.122 - 0.440478 -0.170385 -0.213081 -0.390149 0.720613 + V14.61 V17.196 V18.110 V16.227 V14.47 V23.22 V2.12 V23.29 +-3.89845 -0.95914 -0.57578 0.83647 -1.12655 1.85856 4.93907 -1.56333 + V12.43 R9.7 A157.3 V23.81 V23.82 V12.53 V23.83 V12.56 + 1.02901 -2.01092 0.72379 -2.30398 -1.16894 -1.90465 0.99722 -1.39764 + A152.84 V16.50 V22.122 V16.41 V4.32 V12.66 V19.245 V4.8 + 1.29346 -0.29235 2.13000 -4.44032 -0.92784 0.99173 -1.49153 1.88724 + A180.15 V18.34 V20.213 V19.222 A180.39 V16.189 V12.18 V7.67 + 2.78850 -0.63728 0.33475 -0.01276 -1.65993 -2.09931 -0.97539 2.31384 + V17.165 V19.310 V16.190 A153.154 V19.308 V22.172 V10.98 V22.219 + 1.87381 2.64328 0.01900 0.13747 -0.26612 -2.21647 2.40271 0.25827 + V16.33 V22.204 V20.167 V10.89 V12.79 V19.216 V14.90 A180.72 +-1.69857 0.20739 -0.92732 -0.84955 -0.55322 0.80957 0.66973 0.70524 + V16.21 A180.76 V15.164 A180.78 V14.5 V3.128 A179.13 V9.31 +-0.23696 -0.14589 -0.26826 0.54820 -0.32786 1.64879 1.53212 0.96958 + V20.230 V20.7 V20.234 V18.21 V12.122 + 0.44048 -0.17039 -0.21308 -0.39015 0.72061 > > ## Don't show: > options(od) @@ -7458,7 +7458,7 @@ Correlation : 0.437 (p = < 2.22e-16) > ### > options(digits = 7L) > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n") -Time elapsed: 21.898 0.295 22.177 0 0 +Time elapsed: 20.623 0.279 20.886 0 0 > grDevices::dev.off() null device 1