[Vegan-commits] r2028 - in pkg/vegan: R inst man tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Dec 19 19:23:20 CET 2011
Author: jarioksa
Date: 2011-12-19 19:23:19 +0100 (Mon, 19 Dec 2011)
New Revision: 2028
Modified:
pkg/vegan/R/oecosimu.R
pkg/vegan/R/print.oecosimu.R
pkg/vegan/inst/ChangeLog
pkg/vegan/man/oecosimu.Rd
pkg/vegan/tests/Examples/vegan-Ex.Rout.save
Log:
return mean of simulation in oecosimu
Modified: pkg/vegan/R/oecosimu.R
===================================================================
--- pkg/vegan/R/oecosimu.R 2011-12-19 18:04:11 UTC (rev 2027)
+++ pkg/vegan/R/oecosimu.R 2011-12-19 18:23:19 UTC (rev 2028)
@@ -93,7 +93,8 @@
}
sd <- apply(simind, 1, sd, na.rm = TRUE)
- z <- (indstat - rowMeans(simind, na.rm = TRUE))/sd
+ means <- rowMeans(simind, na.rm = TRUE)
+ z <- (indstat - means)/sd
if (any(sd < sqrt(.Machine$double.eps)))
z[sd < sqrt(.Machine$double.eps)] <- 0
pless <- rowSums(indstat <= simind, na.rm = TRUE)
@@ -117,9 +118,9 @@
names(indstat) <- statistic
if (!is.list(ind))
ind <- list(statistic = ind)
- ind$oecosimu <- list(z = z, pval = p, simulated=simind, method=method,
- statistic = indstat, alternative = alternative,
- isSeq = attr(x, "isSeq"))
+ ind$oecosimu <- list(z = z, means = means, pval = p, simulated=simind,
+ method=method, statistic = indstat,
+ alternative = alternative, isSeq = attr(x, "isSeq"))
class(ind) <- c("oecosimu", class(ind))
ind
}
Modified: pkg/vegan/R/print.oecosimu.R
===================================================================
--- pkg/vegan/R/print.oecosimu.R 2011-12-19 18:04:11 UTC (rev 2027)
+++ pkg/vegan/R/print.oecosimu.R 2011-12-19 18:23:19 UTC (rev 2028)
@@ -27,9 +27,9 @@
greater = c(0.05, 0.5, 1))
qu <- apply(x$oecosimu$simulated, 1, quantile, probs=probs, na.rm = TRUE)
m <- cbind("statistic" = x$oecosimu$statistic,
- "z" = x$oecosimu$z, t(qu),
+ "z" = x$oecosimu$z, "mean" = x$oecosimu$means, t(qu),
"Pr(sim.)"=x$oecosimu$pval)
- printCoefmat(m, ...)
+ printCoefmat(m, cs.ind = 3:6, ...)
if (any(is.na(x$oecosimu$simulated))) {
nacount <- rowSums(is.na(x$oecosimu$simulated))
cat("\nNumber of NA cases removed from simulations:\n",
Modified: pkg/vegan/inst/ChangeLog
===================================================================
--- pkg/vegan/inst/ChangeLog 2011-12-19 18:04:11 UTC (rev 2027)
+++ pkg/vegan/inst/ChangeLog 2011-12-19 18:23:19 UTC (rev 2028)
@@ -18,7 +18,8 @@
with nestedness indices and are ready to be used with oecosimu().
* oecosimu: more informative text on 'alternative' hypotheses in
- the printed output.
+ the printed output. Return also the mean of simulations and show
+ that in the printed output.
* rarecurve: new function to draw rarefaction curves for each
plot, optionally with sample size vertical and corresponding
Modified: pkg/vegan/man/oecosimu.Rd
===================================================================
--- pkg/vegan/man/oecosimu.Rd 2011-12-19 18:04:11 UTC (rev 2027)
+++ pkg/vegan/man/oecosimu.Rd 2011-12-19 18:23:19 UTC (rev 2028)
@@ -156,13 +156,15 @@
load the \pkg{lattice} library before calling \code{densityplot}.
}
-\value{
- Function \code{oecosimu} returns the result of \code{nestfun}
- added with a component called \code{oecosimu}. The \code{oecosimu}
+\value{
+ Function \code{oecosimu} returns the result of \code{nestfun} added
+ with a component called \code{oecosimu}. The \code{oecosimu}
component contains the simulated values of the statistic (item
\code{simulated}), the name of the \code{method}, \eqn{P} value
- (with given \code{alternative}) and \eqn{z}-value of the statistic
- based on simulation. }
+ (with given \code{alternative}), \eqn{z}-value of the statistic
+ based on simulation (also known as standardized effect size), and
+ the means of simultions.
+}
\references{
Hardy, O. J. (2008)
Modified: pkg/vegan/tests/Examples/vegan-Ex.Rout.save
===================================================================
--- pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2011-12-19 18:04:11 UTC (rev 2027)
+++ pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2011-12-19 18:23:19 UTC (rev 2028)
@@ -1,8 +1,8 @@
-R Under development (unstable) (2011-12-11 r57866)
+R version 2.14.1 RC (2011-12-19 r57935)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
-Platform: x86_64-unknown-linux-gnu (64-bit)
+Platform: x86_64-apple-darwin10.8.0/x86_64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
@@ -154,14 +154,14 @@
> plot(ef)
> ordisurf(mod ~ pH, varechem, knots = 1, add = TRUE)
Loading required package: mgcv
-This is mgcv 1.7-11. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-12. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ poly(x1, 1) + poly(x2, 1)
-<environment: 0x2a7ab40>
+<environment: 0x101fd2bc8>
Total model degrees of freedom 3
GCV score: 0.0427924
@@ -3962,24 +3962,24 @@
> oecosimu(sipoo, nestedchecker, "quasiswap")
oecosimu with 99 simulations
simulation method ‘quasiswap’
-alternative hypothesis: true mean is not equal to the statistic
+alternative hypothesis: simulated median is not equal to the statistic
Checkerboard Units : 2767
C-score (species mean): 2.258776
- statistic z 2.5% 50% 97.5% Pr(sim.)
-statistic 2767.00000 0.84129 2584.40000 2676.00000 2858.1 0.39
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+statistic 2767 0.84129 2698.1 2584.4 2676.0 2858.1 0.39
> ## Another Null model and standardized checkerboard score
> oecosimu(sipoo, nestedchecker, "r00", statistic = "C.score")
oecosimu with 99 simulations
simulation method ‘r00’
-alternative hypothesis: true mean is not equal to the statistic
+alternative hypothesis: simulated median is not equal to the statistic
Checkerboard Units : 2767
C-score (species mean): 2.258776
- statistic z 2.5% 50% 97.5% Pr(sim.)
-C.score 2.2588 -28.9196 8.6935 9.2384 9.6053 0.01 **
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+C.score 2.2588 -28.92 9.2234 8.6935 9.2384 9.6053 0.01 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
@@ -4097,13 +4097,13 @@
> oecosimu(sipoo, nestedchecker, "r0")
oecosimu with 99 simulations
simulation method ‘r0’
-alternative hypothesis: true mean is not equal to the statistic
+alternative hypothesis: simulated median is not equal to the statistic
Checkerboard Units : 2767
C-score (species mean): 2.258776
- statistic z 2.5% 50% 97.5% Pr(sim.)
-statistic 2767.000 -17.768 7529.850 8052.000 8518.5 0.01 **
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+statistic 2767 -17.768 8034.6 7529.9 8052.0 8518.5 0.01 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> ## sequential model, one-sided test, a vector statistic
@@ -4112,7 +4112,7 @@
> out
oecosimu with 99 simulations
simulation method ‘swap’ with thin 10, burnin 100
-alternative hypothesis: true mean is less than the statistic
+alternative hypothesis: simulated median is less than the statistic
Call:
@@ -4127,11 +4127,11 @@
Axis lengths 2.9197 2.5442 2.7546 1.78074
- statistic z 0% 50% 95% Pr(sim.)
-DCA1 0.382249 1.865783 0.230869 0.323729 0.3726 0.02 *
-DCA2 0.261208 1.577196 0.149703 0.216169 0.2637 0.09 .
-DCA3 0.166788 0.520903 0.105269 0.155716 0.1859 0.30
-DCA4 0.087226 -1.982236 0.066742 0.126492 0.1649 0.99
+ statistic z mean 0% 50% 95% Pr(sim.)
+DCA1 0.382249 1.8658 0.324042 0.230869 0.323729 0.3726 0.02 *
+DCA2 0.261208 1.5772 0.219388 0.149703 0.216169 0.2637 0.09 .
+DCA3 0.166788 0.5209 0.155941 0.105269 0.155716 0.1859 0.30
+DCA4 0.087226 -1.9822 0.130151 0.066742 0.126492 0.1649 0.99
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> ## Inspect the swap sequence as a time series object
@@ -4150,10 +4150,10 @@
> mbc1
oecosimu with 99 simulations
simulation method ‘r2dtable’
-alternative hypothesis: true mean is not equal to the statistic
+alternative hypothesis: simulated median is not equal to the statistic
- statistic z 2.5% 50% 97.5% Pr(sim.)
-statistic 0.64565 13.06023 0.44057 0.46544 0.4924 0.01 **
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+statistic 0.64565 13.06 0.46704 0.44057 0.46544 0.4924 0.01 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
@@ -4170,10 +4170,10 @@
> oecosimu(dune, meandist, cf)
oecosimu with 99 simulations
simulation method ‘myshuffle’
-alternative hypothesis: true mean is not equal to the statistic
+alternative hypothesis: simulated median is not equal to the statistic
- statistic z 2.5% 50% 97.5% Pr(sim.)
-statistic 0.64565 3.11878 0.62983 0.63557 0.6416 0.03 *
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+statistic 0.64565 3.1188 0.63551 0.62983 0.63557 0.6416 0.03 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
@@ -4696,17 +4696,17 @@
> vare.mds <- monoMDS(vare.dist)
> with(varechem, ordisurf(vare.mds, Baresoil, bubble = 5))
Loading required package: mgcv
-This is mgcv 1.7-11. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-12. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x8ad2b48>
+<environment: 0x109aa0980>
Estimated degrees of freedom:
-6.4351 total = 7.43507
+6.4351 total = 7.435071
GCV score: 144.1236
>
@@ -4719,7 +4719,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x995d978>
+<environment: 0x10960fbf0>
Estimated degrees of freedom:
6.1039 total = 7.103853
@@ -4731,13 +4731,13 @@
> ## Get fitted values
> calibrate(fit)
1 2 3 4 5 6 7
-22.0644615 6.0132250 3.6350484 4.1019743 9.0030990 5.9202602 8.6399182
+22.0644614 6.0132251 3.6350483 4.1019742 9.0030989 5.9202601 8.6399184
8 9 10 11 12 13 14
-11.0719302 0.6561783 35.2282116 10.4346331 7.2900019 5.5710617 24.6503109
+11.0719303 0.6561781 35.2282118 10.4346331 7.2900018 5.5710617 24.6503110
15 16 17 18 19 20 21
-18.8754520 29.7286540 5.6158934 9.5869715 3.2876268 2.7111723 10.7832857
+18.8754521 29.7286543 5.6158934 9.5869716 3.2876267 2.7111721 10.7832857
22 23 24
- 3.0020415 9.8128952 7.3656934
+ 3.0020413 9.8128952 7.3656932
>
> ## Plot method
> plot(fit, what = "contour")
@@ -4868,14 +4868,14 @@
> ## Map of PCNMs in the sample plot
> ordisurf(mite.xy, scores(pcnm1, choi=1), bubble = 4, main = "PCNM 1")
Loading required package: mgcv
-This is mgcv 1.7-11. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-12. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x8dbccd8>
+<environment: 0x10b083f78>
Estimated degrees of freedom:
8.9275 total = 9.927492
@@ -4888,7 +4888,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x999e6a8>
+<environment: 0x10a09aa28>
Estimated degrees of freedom:
7.7529 total = 8.75294
@@ -4901,7 +4901,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x936c760>
+<environment: 0x10b2cb3f8>
Estimated degrees of freedom:
8.8962 total = 9.89616
@@ -5667,8 +5667,8 @@
[2,] 0.1169579 0.9931369
Translation of averages:
- [,1] [,2]
-[1,] 1.79048e-17 9.246476e-19
+ [,1] [,2]
+[1,] 1.047183e-17 -1.381645e-17
Scaling of target:
[1] 0.6736868
@@ -6509,7 +6509,7 @@
Salrep 0.7118892 8.654457e-02
Achmil 1.5948052 8.449914e-01
Poatri 0.7367577 7.099165e-01
-Chealb 1.9479718 6.661338e-16
+Chealb 1.9479718 2.220446e-16
Elyrep 0.5160932 5.135604e-01
Sagpro 1.3031750 1.019154e+00
Plalan 1.7013794 6.393173e-01
@@ -6582,29 +6582,29 @@
> oecosimu(dune, treedive, "r0", tree = cl)
oecosimu with 99 simulations
simulation method ‘r0’
-alternative hypothesis: true mean is not equal to the statistic
+alternative hypothesis: simulated median is not equal to the statistic
- statistic z 2.5% 50% 97.5% Pr(sim.)
-2 411.981567 -3.174838 462.373272 577.880184 673.73 0.01 **
-13 548.847926 -0.391605 464.447005 565.898618 664.40 0.71
-4 606.912442 -1.670683 584.493088 694.009217 791.24 0.13
-16 479.262673 -0.364249 364.516129 502.304147 591.24 0.53
-6 572.350230 -0.652353 510.253456 609.216590 717.05 0.63
-1 249.308756 -2.584802 264.700461 367.281106 435.37 0.05 *
-8 692.165899 0.891185 550.276498 643.778802 747.93 0.45
-5 640.092166 -1.331165 613.870968 724.884793 830.41 0.25
-17 341.935484 -2.279642 373.271889 441.474654 538.59 0.03 *
-15 599.539171 1.874784 395.852535 491.705069 599.54 0.09 .
-10 563.594470 -1.618219 553.801843 660.829493 723.46 0.11
-11 564.055300 0.531521 418.433180 536.405530 634.15 0.77
-9 625.806452 -1.015424 548.387097 694.009217 778.80 0.31
-18 543.317972 0.090292 411.820276 543.317972 626.68 1.00
-3 489.400922 -1.486983 460.483871 567.281106 673.73 0.15
-20 578.801843 1.595836 408.709677 495.391705 585.65 0.11
-14 547.926267 1.912479 370.967742 462.211982 544.19 0.07 .
-19 593.087558 0.978571 439.170507 527.188940 642.86 0.49
-12 572.350230 0.797098 425.460829 527.188940 642.86 0.33
-7 646.543779 -0.606963 576.152074 681.566820 770.51 0.53
+ statistic z mean 2.5% 50% 97.5% Pr(sim.)
+2 411.98 -3.174838 580.78 462.37 577.88 673.73 0.01 **
+13 548.85 -0.391605 569.18 464.45 565.90 664.40 0.71
+4 606.91 -1.670683 693.49 584.49 694.01 791.24 0.13
+16 479.26 -0.364249 500.03 364.52 502.30 591.24 0.53
+6 572.35 -0.652353 610.06 510.25 609.22 717.05 0.63
+1 249.31 -2.584802 362.63 264.70 367.28 435.37 0.05 *
+8 692.17 0.891185 646.01 550.28 643.78 747.93 0.45
+5 640.09 -1.331165 720.26 613.87 724.88 830.41 0.25
+17 341.94 -2.279642 449.35 373.27 441.47 538.59 0.03 *
+15 599.54 1.874784 494.62 395.85 491.71 599.54 0.09 .
+10 563.59 -1.618219 648.58 553.80 660.83 723.46 0.11
+11 564.06 0.531521 534.78 418.43 536.41 634.15 0.77
+9 625.81 -1.015424 685.40 548.39 694.01 778.80 0.31
+18 543.32 0.090292 538.71 411.82 543.32 626.68 1.00
+3 489.40 -1.486983 575.24 460.48 567.28 673.73 0.15
+20 578.80 1.595836 500.98 408.71 495.39 585.65 0.11
+14 547.93 1.912479 457.16 370.97 462.21 544.19 0.07 .
+19 593.09 0.978571 538.05 439.17 527.19 642.86 0.49
+12 572.35 0.797098 531.20 425.46 527.19 642.86 0.33
+7 646.54 -0.606963 678.97 576.15 681.57 770.51 0.53
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> ## Clustering of tree distances
@@ -7163,14 +7163,14 @@
> ## add fitted surface of diversity to the model
> ordisurf(mod, diversity(dune), add = TRUE)
Loading required package: mgcv
-This is mgcv 1.7-11. For overview type 'help("mgcv-package")'.
+This is mgcv 1.7-12. For overview type 'help("mgcv-package")'.
Family: gaussian
Link function: identity
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x9403288>
+<environment: 0x10b2f4d80>
Estimated degrees of freedom:
2 total = 3
@@ -7613,13 +7613,13 @@
> ## Eigevalues are numerically similar
> ca$CA$eig - ord$eig
CA1 CA2 CA3 CA4 CA5
--7.771561e-16 -2.220446e-16 6.106227e-16 -3.608225e-16 -1.110223e-16
+ 9.992007e-16 -6.106227e-16 8.881784e-16 -2.775558e-17 2.220446e-16
CA6 CA7 CA8 CA9 CA10
- 1.387779e-17 9.714451e-17 1.387779e-17 2.775558e-17 1.318390e-16
+ 9.714451e-17 9.714451e-17 4.163336e-17 -1.387779e-17 8.326673e-17
CA11 CA12 CA13 CA14 CA15
- 9.714451e-17 6.938894e-18 -6.938894e-18 3.122502e-17 0.000000e+00
+ 7.632783e-17 1.040834e-16 -2.081668e-17 4.510281e-17 1.908196e-17
CA16 CA17 CA18 CA19
--3.295975e-17 2.428613e-17 2.862294e-17 5.637851e-18
+-1.908196e-17 0.000000e+00 7.025630e-17 2.125036e-17
> ## Configurations are similar when site scores are scaled by
> ## eigenvalues in CA
> procrustes(ord, ca, choices=1:19, scaling = 1)
@@ -7628,7 +7628,7 @@
procrustes(X = ord, Y = ca, choices = 1:19, scaling = 1)
Procrustes sum of squares:
- 0
+-4.263e-14
> plot(procrustes(ord, ca, choices=1:2, scaling=1))
> ## Reconstruction of non-Euclidean distances with negative eigenvalues
@@ -7646,7 +7646,7 @@
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed: 25.593 0.132 25.82 0 0
+Time elapsed: 90.026 2.277 98.239 0 0
> grDevices::dev.off()
null device
1
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