diff --git a/tests/Examples/vegan-Ex.Rout.save b/tests/Examples/vegan-Ex.Rout.save index 5ad32242..b9506afd 100644 --- a/tests/Examples/vegan-Ex.Rout.save +++ b/tests/Examples/vegan-Ex.Rout.save @@ -1,5 +1,5 @@ -R Under development (unstable) (2017-05-16 r72682) -- "Unsuffered Consequences" +R Under development (unstable) (2017-06-05 r72769) -- "Unsuffered Consequences" Copyright (C) 2017 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) @@ -813,11 +813,10 @@ detaching ‘dune.env’ > > ### ** Examples > -> data(varespec) -> data(varechem) -> vare.cca <- cca(varespec ~ Al + P + K, varechem) +> data(varespec, varechem) +> mod <- cca(varespec ~ Al + P + K, varechem) > ## overall test -> anova(vare.cca) +> anova(mod) Permutation test for cca under reduced model Permutation: free Number of permutations: 999 @@ -828,6 +827,320 @@ Model 3 0.64413 2.984 0.001 *** Residual 20 1.43906 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 +> ## tests for individual terms +> anova(mod, by="term") +Permutation test for cca under reduced model +Terms added sequentially (first to last) +Permutation: free +Number of permutations: 999 + +Model: cca(formula = varespec ~ Al + P + K, data = varechem) + Df ChiSquare F Pr(>F) +Al 1 0.29817 4.1440 0.001 *** +P 1 0.18991 2.6393 0.004 ** +K 1 0.15605 2.1688 0.025 * +Residual 20 1.43906 +--- +Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 +> anova(mod, by="margin") +Permutation test for cca under reduced model +Marginal effects of terms +Permutation: free +Number of permutations: 999 + +Model: cca(formula = varespec ~ Al + P + K, data = varechem) + Df ChiSquare F Pr(>F) +Al 1 0.31184 4.3340 0.001 *** +P 1 0.16810 2.3362 0.014 * +K 1 0.15605 2.1688 0.016 * +Residual 20 1.43906 +--- +Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 +> ## test for adding all environmental variables +> anova(mod, cca(varespec ~ ., varechem)) +Permutation tests for cca under reduced model +Permutation: free +Number of permutations: 999 + +Model 1: varespec ~ Al + P + K +Model 2: varespec ~ N + P + K + Ca + Mg + S + Al + Fe + Mn + Zn + Mo + Baresoil + Humdepth + pH + ResDf ResChiSquare Df ChiSquare F Pr(>F) +1 20 1.43906 +2 9 0.64171 11 0.79735 1.0166 0.463 +> +> +> +> cleanEx() +> nameEx("avgdist") +> ### * avgdist +> +> flush(stderr()); flush(stdout()) +> +> ### Name: avgdist +> ### Title: Averaged Subsampled Dissimilarity Matrices +> ### Aliases: avgdist +> ### Keywords: distance +> +> ### ** Examples +> +> data(BCI) +> mean.avg.dist <- avgdist(BCI, sample = 50, iterations = 10) +> mean.avg.dist + 1 2 3 4 5 6 7 8 9 10 11 12 +1 0.000 0.574 0.564 0.628 0.618 0.624 0.602 0.592 0.650 0.594 0.614 0.628 +2 0.574 0.000 0.526 0.562 0.622 0.570 0.534 0.548 0.568 0.594 0.574 0.568 +3 0.564 0.526 0.000 0.582 0.602 0.604 0.600 0.564 0.608 0.538 0.574 0.602 +4 0.628 0.562 0.582 0.000 0.646 0.642 0.608 0.562 0.594 0.586 0.582 0.606 +5 0.618 0.622 0.602 0.646 0.000 0.636 0.662 0.616 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0.706 0.680 +5 0.724 0.694 +6 0.712 0.692 +7 0.698 0.684 +8 0.666 0.668 +9 0.736 0.702 +10 0.694 0.672 +11 0.628 0.642 +12 0.696 0.708 +13 0.768 0.748 +14 0.700 0.676 +15 0.688 0.684 +16 0.654 0.628 +17 0.762 0.740 +18 0.776 0.764 +19 0.706 0.702 +20 0.694 0.682 +21 0.586 0.622 +22 0.686 0.686 +23 0.732 0.712 +24 0.650 0.642 +25 0.658 0.658 +26 0.588 0.608 +27 0.676 0.686 +28 0.676 0.688 +29 0.734 0.714 +30 0.718 0.742 +31 0.628 0.612 +32 0.688 0.660 +33 0.666 0.630 +34 0.722 0.716 +35 0.812 0.818 +36 0.668 0.638 +37 0.688 0.670 +38 0.678 0.684 +39 0.708 0.700 +40 0.706 0.732 +41 0.624 0.608 +42 0.612 0.594 +43 0.552 0.560 +44 0.562 0.526 +45 0.540 0.528 +46 0.730 0.678 +47 0.628 0.638 +48 0.568 0.588 +49 0.000 0.536 +50 0.536 0.000 > > > @@ -4098,7 +4411,7 @@ Species: expanded scores based on ‘dune’ > ### Name: model.matrix.cca > ### Title: Reconstruct Model Frame and Model Matrices of Constrained > ### Ordination -> ### Aliases: model.matrix.cca model.frame.cca +> ### Aliases: model.matrix.cca model.matrix.rda model.frame.cca > ### Keywords: models multivariate > > ### ** Examples @@ -4129,50 +4442,55 @@ Species: expanded scores based on ‘dune’ 19 -0.12106605 0.05451056 NM Hayfield 20 -0.14212101 0.10689011 NM Hayfield > model.matrix(mod) - poly(A1, 2)1 poly(A1, 2)2 ManagementHF ManagementNM ManagementSF -1 -0.21581339 0.31584574 0 0 1 -2 -0.14212101 0.10689011 0 0 0 -3 -0.05790115 -0.08310263 0 0 1 -4 -0.06842864 -0.06220100 0 0 1 -5 0.15264849 -0.33028722 1 0 0 -6 -0.05790115 -0.08310263 1 0 0 -7 -0.21581339 0.31584574 1 0 0 -8 -0.06842864 -0.06220100 1 0 0 -9 -0.12106605 0.05451056 1 0 0 -10 -0.16317598 0.16252391 0 0 0 -11 -0.14212101 0.10689011 0 0 0 -12 0.10001108 -0.29899963 0 0 1 -13 0.12106605 -0.31395535 0 0 1 -14 0.46847296 -0.09089291 0 1 0 -15 0.70007758 0.55002015 0 1 0 -16 0.08948360 -0.29030142 0 0 1 -17 -0.08948360 -0.01795706 0 1 0 -18 -0.02631871 -0.14092613 0 1 0 -19 -0.12106605 0.05451056 0 1 0 -20 -0.14212101 0.10689011 0 1 0 - Use.L Use.Q -1 -7.850462e-17 -0.8164966 -2 -7.850462e-17 -0.8164966 -3 -7.850462e-17 -0.8164966 -4 -7.850462e-17 -0.8164966 -5 -7.071068e-01 0.4082483 -6 -7.850462e-17 -0.8164966 -7 7.071068e-01 0.4082483 -8 7.071068e-01 0.4082483 -9 -7.071068e-01 0.4082483 -10 -7.071068e-01 0.4082483 -11 7.071068e-01 0.4082483 -12 -7.850462e-17 -0.8164966 -13 -7.850462e-17 -0.8164966 -14 7.071068e-01 0.4082483 -15 -7.850462e-17 -0.8164966 -16 7.071068e-01 0.4082483 -17 -7.071068e-01 0.4082483 -18 -7.071068e-01 0.4082483 -19 -7.071068e-01 0.4082483 -20 -7.071068e-01 0.4082483 + poly(A1, 2)1 poly(A1, 2)2 ManagementHF ManagementNM ManagementSF Use.L +1 -0.198439200 0.330886526 -0.3109489 -0.220438 0.7021898 0.06503318 +2 -0.124746824 0.121930900 -0.3109489 -0.220438 -0.2978102 0.06503318 +3 -0.040526965 -0.068061834 -0.3109489 -0.220438 0.7021898 0.06503318 +4 -0.051054447 -0.047160208 -0.3109489 -0.220438 0.7021898 0.06503318 +5 0.170022682 -0.315246424 0.6890511 -0.220438 -0.2978102 -0.64207360 +6 -0.040526965 -0.068061834 0.6890511 -0.220438 -0.2978102 0.06503318 +7 -0.198439200 0.330886526 0.6890511 -0.220438 -0.2978102 0.77213996 +8 -0.051054447 -0.047160208 0.6890511 -0.220438 -0.2978102 0.77213996 +9 -0.103691859 0.069551347 0.6890511 -0.220438 -0.2978102 -0.64207360 +10 -0.145801788 0.177564700 -0.3109489 -0.220438 -0.2978102 -0.64207360 +11 -0.124746824 0.121930900 -0.3109489 -0.220438 -0.2978102 0.77213996 +12 0.117385270 -0.283958836 -0.3109489 -0.220438 0.7021898 0.06503318 +13 0.138440235 -0.298914556 -0.3109489 -0.220438 0.7021898 0.06503318 +14 0.485847152 -0.075852117 -0.3109489 0.779562 -0.2978102 0.77213996 +15 0.717451763 0.565060938 -0.3109489 0.779562 -0.2978102 0.06503318 +16 0.106857788 -0.275260634 -0.3109489 -0.220438 0.7021898 0.77213996 +17 -0.072109412 -0.002916271 -0.3109489 0.779562 -0.2978102 -0.64207360 +18 -0.008944518 -0.125885343 -0.3109489 0.779562 -0.2978102 -0.64207360 +19 -0.103691859 0.069551347 -0.3109489 0.779562 -0.2978102 -0.64207360 +20 -0.124746824 0.121930900 -0.3109489 0.779562 -0.2978102 -0.64207360 + Use.Q +1 -0.7169674 +2 -0.7169674 +3 -0.7169674 +4 -0.7169674 +5 0.5077774 +6 -0.7169674 +7 0.5077774 +8 0.5077774 +9 0.5077774 +10 0.5077774 +11 0.5077774 +12 -0.7169674 +13 -0.7169674 +14 0.5077774 +15 -0.7169674 +16 0.5077774 +17 0.5077774 +18 0.5077774 +19 0.5077774 +20 0.5077774 attr(,"assign") [1] 1 1 2 2 2 3 3 +attr(,"scaled:center") +poly(A1, 2)1 poly(A1, 2)2 ManagementHF ManagementNM ManagementSF Use.L + -0.01737419 -0.01504079 0.31094891 0.22043796 0.29781022 -0.06503318 + Use.Q + -0.09952915 > > > @@ -8975,7 +9293,7 @@ Procrustes sum of squares: > ### > options(digits = 7L) > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n") -Time elapsed: 25.9 0.172 26.151 0 0 +Time elapsed: 26.54 0.156 26.773 0 0 > grDevices::dev.off() null device 1