[Vegan-commits] r1653 - pkg/vegan/tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Jun 23 17:31:32 CEST 2011
Author: jarioksa
Date: 2011-06-23 17:31:32 +0200 (Thu, 23 Jun 2011)
New Revision: 1653
Modified:
pkg/vegan/tests/Examples/vegan-Ex.Rout.save
Log:
update examples after switching to 'permute' package
Modified: pkg/vegan/tests/Examples/vegan-Ex.Rout.save
===================================================================
--- pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2011-06-23 15:30:00 UTC (rev 1652)
+++ pkg/vegan/tests/Examples/vegan-Ex.Rout.save 2011-06-23 15:31:32 UTC (rev 1653)
@@ -22,7 +22,8 @@
> source(file.path(R.home("share"), "R", "examples-header.R"))
> options(warn = 1)
> library('vegan')
-This is vegan 1.18-32
+Loading required package: permute
+This is vegan 1.90-0
>
> assign(".oldSearch", search(), pos = 'CheckExEnv')
> cleanEx()
@@ -1108,11 +1109,14 @@
Permutation test for homogeneity of multivariate dispersions
No. of permutations: 999
-Permutation type: free
+
+**** STRATA ****
Permutations are unstratified
-Mirrored permutations?: No
-Use same permutation within strata?: No
+**** SAMPLES ****
+Permutation type: free
+Mirrored permutations for Samples?: No
+
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
Groups 1 0.07931 0.079306 4.6156 999 0.05 *
@@ -1180,11 +1184,14 @@
Permutation test for homogeneity of multivariate dispersions
No. of permutations: 100
-Permutation type: free
+
+**** STRATA ****
Permutations are unstratified
-Mirrored permutations?: No
-Use same permutation within strata?: No
+**** SAMPLES ****
+Permutation type: free
+Mirrored permutations for Samples?: No
+
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
Groups 1 0.039979 0.039979 2.4237 100 0.1584
@@ -1229,11 +1236,14 @@
Permutation test for homogeneity of multivariate dispersions
No. of permutations: 100
-Permutation type: free
+
+**** STRATA ****
Permutations are unstratified
-Mirrored permutations?: No
-Use same permutation within strata?: No
+**** SAMPLES ****
+Permutation type: free
+Mirrored permutations for Samples?: No
+
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
Groups 1 0.039979 0.039979 2.4237 100 0.1287
@@ -4624,7 +4634,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x103676520>
+<environment: 0x103cf98d8>
Estimated degrees of freedom:
6.2955 total = 7.295494
@@ -4640,7 +4650,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x105814510>
+<environment: 0x10187dad0>
Estimated degrees of freedom:
4.9207 total = 5.920718
@@ -4796,7 +4806,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x1073cc078>
+<environment: 0x106523200>
Estimated degrees of freedom:
8.9275 total = 9.927492
@@ -4809,7 +4819,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x103301c30>
+<environment: 0x105decb18>
Estimated degrees of freedom:
7.7529 total = 8.75294
@@ -4822,7 +4832,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x10461d078>
+<environment: 0x10665fd78>
Estimated degrees of freedom:
8.8962 total = 9.89616
@@ -4848,319 +4858,6 @@
detaching ‘package:lattice’, ‘package:mgcv’
-> nameEx("permCheck")
-> ### * permCheck
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: permCheck
-> ### Title: Utility functions for permutation schemes
-> ### Aliases: permCheck numPerms print.permCheck print.summary.permCheck
-> ### summary.permCheck getNumObs getNumObs.default getNumObs.integer
-> ### getNumObs.numeric allPerms print.allPerms summary.allPerms
-> ### print.summary.allPerms permuplot
-> ### Keywords: utilities design methods datagen
->
-> ### ** Examples
->
-> ## use example data from ?pyrifos
-> example(pyrifos)
-
-pyrifs> data(pyrifos)
-
-pyrifs> ditch <- gl(12, 1, length=132)
-
-pyrifs> week <- gl(11, 12, labels=c(-4, -1, 0.1, 1, 2, 4, 8, 12, 15, 19, 24))
-
-pyrifs> dose <- factor(rep(c(0.1, 0, 0, 0.9, 0, 44, 6, 0.1, 44, 0.9, 0, 6), 11))
->
-> ## Demonstrate the maximum number of permutations for the pyrifos data
-> ## under a series of permutation schemes
->
-> ## no restrictions - lots of perms
-> (check1 <- permCheck(pyrifos, control = permControl(type = "free")))
-[1] 1.118249e+224
-> summary(check1)
-Number of possible permutations: 1.11824865119614e+224
-
-No. of permutations: 199
-Permutation type: free
-Permutations are unstratified
-Mirrored permutations?: No
-Use same permutation within strata?: No
-
->
-> ## no strata but data are series with no mirroring, so 132 permutations
-> permCheck(pyrifos, control = permControl(type = "series",
-+ mirror = FALSE))
-[1] 132
->
-> ## no strata but data are series with mirroring, so 264 permutations
-> permCheck(pyrifos, control = permControl(type = "series",
-+ mirror = TRUE))
-[1] 264
->
-> ## unrestricted within strata
-> permCheck(pyrifos, control = permControl(strata = ditch,
-+ type = "free"))
-[1] 1.636321e+91
->
-> ## time series within strata, no mirroring
-> permCheck(pyrifos, control = permControl(strata = ditch,
-+ type = "series", mirror = FALSE))
-[1] 3.138428e+12
->
-> ## time series within strata, with mirroring
-> permCheck(pyrifos, control = permControl(strata = ditch,
-+ type = "series", mirror = TRUE))
-[1] 1.2855e+16
->
-> ## time series within strata, no mirroring, same permutation within strata
-> permCheck(pyrifos, control = permControl(strata = ditch,
-+ type = "series", constant = TRUE))
-[1] 11
->
-> ## time series within strata, with mirroring, same permutation within strata
-> permCheck(pyrifos, control = permControl(strata = ditch,
-+ type = "series", mirror = TRUE, constant = TRUE))
-[1] 22
->
-> ## permute strata
-> permCheck(pyrifos, permControl(strata = ditch, type = "free",
-+ permute.strata = TRUE))
-[1] 479001600
->
-> ## this should also also for arbitrary vectors
-> vec1 <- permCheck(1:100)
-> vec2 <- permCheck(1:100, permControl())
-> all.equal(vec1, vec2)
-[1] TRUE
-> vec3 <- permCheck(1:100, permControl(type = "series"))
-> all.equal(100, vec3$n)
-[1] TRUE
-> vec4 <- permCheck(1:100, permControl(type = "series", mirror = TRUE))
-> all.equal(vec4$n, 200)
-[1] TRUE
->
-> ## enumerate all possible permutations
-> fac <- gl(2,6)
-> ctrl <- permControl(type = "grid", mirror = FALSE, strata = fac,
-+ constant = TRUE, nrow = 3, ncol = 2)
-> numPerms(1:12, control = ctrl)
-[1] 6
-> (tmp <- allPerms(12, control = ctrl, observed = TRUE))
- [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
-[1,] 2 3 4 5 6 1 8 9 10 11 12 7
-[2,] 3 4 5 6 1 2 9 10 11 12 7 8
-[3,] 4 5 6 1 2 3 10 11 12 7 8 9
-[4,] 5 6 1 2 3 4 11 12 7 8 9 10
-[5,] 6 1 2 3 4 5 12 7 8 9 10 11
-[6,] 1 2 3 4 5 6 7 8 9 10 11 12
-> (tmp2 <- allPerms(12, control = ctrl))
- [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
-[1,] 2 3 4 5 6 1 8 9 10 11 12 7
-[2,] 3 4 5 6 1 2 9 10 11 12 7 8
-[3,] 4 5 6 1 2 3 10 11 12 7 8 9
-[4,] 5 6 1 2 3 4 11 12 7 8 9 10
-[5,] 6 1 2 3 4 5 12 7 8 9 10 11
-> ## turn on mirroring
-> ctrl$mirror <- TRUE
-> numPerms(1:12, control = ctrl)
-[1] 12
-> (tmp3 <- allPerms(12, control = ctrl, observed = TRUE))
- [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
- [1,] 2 3 4 5 6 1 8 9 10 11 12 7
- [2,] 3 4 5 6 1 2 9 10 11 12 7 8
- [3,] 4 5 6 1 2 3 10 11 12 7 8 9
- [4,] 5 6 1 2 3 4 11 12 7 8 9 10
- [5,] 6 1 2 3 4 5 12 7 8 9 10 11
- [6,] 1 2 3 4 5 6 7 8 9 10 11 12
- [7,] 1 6 5 4 3 2 7 12 11 10 9 8
- [8,] 2 1 6 5 4 3 8 7 12 11 10 9
- [9,] 3 2 1 6 5 4 9 8 7 12 11 10
-[10,] 4 3 2 1 6 5 10 9 8 7 12 11
-[11,] 5 4 3 2 1 6 11 10 9 8 7 12
-[12,] 6 5 4 3 2 1 12 11 10 9 8 7
-> (tmp4 <- allPerms(12, control = ctrl))
- [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
- [1,] 2 3 4 5 6 1 8 9 10 11 12 7
- [2,] 3 4 5 6 1 2 9 10 11 12 7 8
- [3,] 4 5 6 1 2 3 10 11 12 7 8 9
- [4,] 5 6 1 2 3 4 11 12 7 8 9 10
- [5,] 6 1 2 3 4 5 12 7 8 9 10 11
- [6,] 1 6 5 4 3 2 7 12 11 10 9 8
- [7,] 2 1 6 5 4 3 8 7 12 11 10 9
- [8,] 3 2 1 6 5 4 9 8 7 12 11 10
- [9,] 4 3 2 1 6 5 10 9 8 7 12 11
-[10,] 5 4 3 2 1 6 11 10 9 8 7 12
-[11,] 6 5 4 3 2 1 12 11 10 9 8 7
-> ## prints out details of the permutation scheme as
-> ## well as the matrix of permutations
-> summary(tmp)
-
- Complete enumeration of permutations
-
-Permutation Scheme:
-
-No. of permutations: 6 (complete enumeration)
-Permutation type: grid
-Data are spatial grid(s) of dimension 3 * 2
-Permutations stratified within 'fac'
-Mirrored permutations?: No
-Use same permutation within strata?: Yes
-
-Contains observed ordering?: Yes
-
-All permutations:
- [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
-[1,] 2 3 4 5 6 1 8 9 10 11 12 7
-[2,] 3 4 5 6 1 2 9 10 11 12 7 8
-[3,] 4 5 6 1 2 3 10 11 12 7 8 9
-[4,] 5 6 1 2 3 4 11 12 7 8 9 10
-[5,] 6 1 2 3 4 5 12 7 8 9 10 11
-[6,] 1 2 3 4 5 6 7 8 9 10 11 12
-> summary(tmp2)
-
- Complete enumeration of permutations
-
-Permutation Scheme:
-
-No. of permutations: 5 (complete enumeration)
-Permutation type: grid
-Data are spatial grid(s) of dimension 3 * 2
-Permutations stratified within 'fac'
-Mirrored permutations?: No
-Use same permutation within strata?: Yes
-
-Contains observed ordering?: No
-
-All permutations:
- [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
-[1,] 2 3 4 5 6 1 8 9 10 11 12 7
-[2,] 3 4 5 6 1 2 9 10 11 12 7 8
-[3,] 4 5 6 1 2 3 10 11 12 7 8 9
-[4,] 5 6 1 2 3 4 11 12 7 8 9 10
-[5,] 6 1 2 3 4 5 12 7 8 9 10 11
->
-> ## different numbers of observations per level of strata
-> fac <- factor(rep(1:3, times = c(3,2,2)))
-> ## free permutations in levels of strata
-> numPerms(7, permControl(type = "free", strata = fac))
-[1] 24
-> allPerms(7, permControl(type = "free", strata = fac))
- [,1] [,2] [,3] [,4] [,5] [,6] [,7]
- [1,] 1 2 3 4 5 7 6
- [2,] 1 2 3 5 4 6 7
- [3,] 1 2 3 5 4 7 6
- [4,] 1 3 2 4 5 6 7
- [5,] 1 3 2 4 5 7 6
- [6,] 1 3 2 5 4 6 7
- [7,] 1 3 2 5 4 7 6
- [8,] 2 1 3 4 5 6 7
- [9,] 2 1 3 4 5 7 6
-[10,] 2 1 3 5 4 6 7
-[11,] 2 1 3 5 4 7 6
-[12,] 2 3 1 4 5 6 7
-[13,] 2 3 1 4 5 7 6
-[14,] 2 3 1 5 4 6 7
-[15,] 2 3 1 5 4 7 6
-[16,] 3 1 2 4 5 6 7
-[17,] 3 1 2 4 5 7 6
-[18,] 3 1 2 5 4 6 7
-[19,] 3 1 2 5 4 7 6
-[20,] 3 2 1 4 5 6 7
-[21,] 3 2 1 4 5 7 6
-[22,] 3 2 1 5 4 6 7
-[23,] 3 2 1 5 4 7 6
-> ## series permutations in levels of strata
-> numPerms(7, permControl(type = "series", strata = fac))
-[1] 12
-> allPerms(7, permControl(type = "series", strata = fac))
- [,1] [,2] [,3] [,4] [,5] [,6] [,7]
- [1,] 2 3 1 5 4 7 6
- [2,] 2 3 1 5 4 6 7
- [3,] 2 3 1 4 5 7 6
- [4,] 2 3 1 4 5 6 7
- [5,] 3 1 2 5 4 7 6
- [6,] 3 1 2 5 4 6 7
- [7,] 3 1 2 4 5 7 6
- [8,] 3 1 2 4 5 6 7
- [9,] 1 2 3 5 4 7 6
-[10,] 1 2 3 5 4 6 7
-[11,] 1 2 3 4 5 7 6
->
-> ## allPerms can work with a vector
-> vec <- c(3,4,5)
-> allPerms(vec)
- [,1] [,2] [,3]
-[1,] 1 2 3
-[2,] 1 3 2
-[3,] 2 1 3
-[4,] 2 3 1
-[5,] 3 1 2
-[6,] 3 2 1
->
-> ## Tests for permuplot
-> n <- 25
-> ## standard permutation designs
-> permuplot(n, permControl(type = "free"))
-> permuplot(n, permControl(type = "series"))
-> permuplot(n, permControl(type = "grid", nrow = 5, ncol = 5))
->
-> ## restricted perms with mirroring
-> permuplot(n, permControl(type = "series", mirror = TRUE))
-> permuplot(n, permControl(type = "grid", nrow = 5, ncol = 5,
-+ mirror = TRUE))
->
-> ## perms within strata
-> fac <- gl(6, 20)
-> control <- permControl(type = "free", strata = fac)
-> permuplot(120, control = control, cex = 0.8)
-> control <- permControl(type = "series", strata = fac)
-> permuplot(120, control = control, cex = 0.8)
-> fac <- gl(6, 25)
-> control <- permControl(type = "grid", strata = fac,
-+ nrow = 5, ncol = 5)
-> permuplot(150, control = control, cex = 0.8)
->
-> ## perms within strata with mirroring
-> fac <- gl(6, 20)
-> control <- permControl(type = "series", strata = fac,
-+ mirror = TRUE)
-> permuplot(120, control = control, cex = 0.8)
-> fac <- gl(6, 25)
-> control <- permControl(type = "grid", strata = fac,
-+ nrow = 5, ncol = 5, mirror = TRUE)
-> permuplot(150, control = control, cex = 0.8)
->
-> ## same perms within strata
-> fac <- gl(6, 20)
-> control <- permControl(type = "free", strata = fac,
-+ constant = TRUE)
-> permuplot(120, control = control, cex = 0.8)
-> control <- permControl(type = "series", strata = fac,
-+ constant = TRUE)
-> permuplot(120, control = control, cex = 0.8)
-> fac <- gl(6, 25)
-> control <- permControl(type = "grid", strata = fac,
-+ nrow = 5, ncol = 5, constant = TRUE)
-> permuplot(150, control = control, cex = 0.8)
->
-> ## same perms within strata with mirroring
-> fac <- gl(6, 20)
-> control <- permControl(type = "series", strata = fac,
-+ mirror = TRUE, constant = TRUE)
-> permuplot(120, control = control, cex = 0.8)
-> fac <- gl(6, 25)
-> control <- permControl(type = "grid", strata = fac,
-+ nrow = 5, ncol = 5, mirror = TRUE,
-+ constant = TRUE)
-> permuplot(150, control = control, cex = 0.8)
->
->
->
->
-> cleanEx()
> nameEx("permatfull")
> ### * permatfull
>
@@ -5373,162 +5070,6 @@
>
> graphics::par(get("par.postscript", pos = 'CheckExEnv'))
> cleanEx()
-> nameEx("permuted.index2")
-> ### * permuted.index2
->
-> flush(stderr()); flush(stdout())
->
-> ### Name: permuted.index2
-> ### Title: Unrestricted and restricted permutations
-> ### Aliases: permuted.index2 permControl print.permControl permute
-> ### Keywords: htest design datagen
->
-> ### ** Examples
->
-> set.seed(1234)
->
-> ## unrestricted permutations
-> permuted.index2(20)
- [1] 3 12 11 18 14 10 1 4 8 6 7 5 20 15 2 9 17 16 19 13
->
-> ## observations represent a time series of line transect
-> permuted.index2(20, control = permControl(type = "series"))
- [1] 8 9 10 11 12 13 14 15 16 17 18 19 20 1 2 3 4 5 6 7
->
-> ## observations represent a time series of line transect
-> ## but with mirroring allowed
-> permuted.index2(20, control = permControl(type = "series", mirror = TRUE))
- [1] 7 6 5 4 3 2 1 20 19 18 17 16 15 14 13 12 11 10 9 8
->
-> ## observations represent a spatial grid
-> perms <- permuted.index2(20, permControl(type = "grid",
-+ ncol = 4, nrow = 5))
-> ## view the permutation as a grid
-> matrix(matrix(1:20, nrow = 5, ncol = 4)[perms], ncol = 4, nrow = 5)
- [,1] [,2] [,3] [,4]
-[1,] 7 12 17 2
-[2,] 8 13 18 3
-[3,] 9 14 19 4
-[4,] 10 15 20 5
-[5,] 6 11 16 1
->
-> ## random permutations in presence of strata
-> block <- gl(4, 5)
-> permuted.index2(20, permControl(strata = block, type = "free"))
- [1] 5 3 4 2 1 8 7 6 9 10 14 11 15 12 13 18 20 16 17 19
-> ## as above but same random permutation within strata
-> permuted.index2(20, permControl(strata = block, type = "free",
-+ constant = TRUE))
- [1] 3 5 2 1 4 6 7 8 9 10 13 12 15 11 14 20 16 19 18 17
->
-> ## time series within each level of block
-> permuted.index2(20, permControl(strata = block, type = "series"))
- [1] 5 1 2 3 4 8 9 10 6 7 14 15 11 12 13 17 18 19 20 16
-> ## as above, but with same permutation for each level
-> permuted.index2(20, permControl(strata = block, type = "series",
-+ constant = TRUE))
- [1] 3 2 1 5 4 8 7 6 10 9 13 12 11 15 14 18 17 16 20 19
->
-> ## spatial grids within each level of block
-> permuted.index2(100, permControl(strata = block, type = "grid",
-+ ncol = 5, nrow = 5))
- [1] 21 22 23 24 25 30 26 27 28 29 54 55 51 52 53 57 58 59
- [19] 60 56 41 42 43 44 45 50 46 47 48 49 74 75 71 72 73 77
- [37] 78 79 80 76 61 62 63 64 65 70 66 67 68 69 94 95 91 92
- [55] 93 97 98 99 100 96 81 82 83 84 85 90 86 87 88 89 14 15
- [73] 11 12 13 17 18 19 20 16 1 2 3 4 5 10 6 7 8 9
- [91] 34 35 31 32 33 37 38 39 40 36
-> ## as above, but with same permutation for each level
-> permuted.index2(100, permControl(strata = block, type = "grid",
-+ ncol = 5, nrow = 5, constant = TRUE))
- [1] 84 83 82 81 85 89 88 87 86 90 94 93 92 91 95 99 98 97
- [19] 96 100 64 63 62 61 65 69 68 67 66 70 74 73 72 71 75 79
- [37] 78 77 76 80 44 43 42 41 45 49 48 47 46 50 54 53 52 51
- [55] 55 59 58 57 56 60 24 23 22 21 25 29 28 27 26 30 34 33
- [73] 32 31 35 39 38 37 36 40 4 3 2 1 5 9 8 7 6 10
- [91] 14 13 12 11 15 19 18 17 16 20
->
-> ## permuting levels of block instead of observations
-> permuted.index2(20, permControl(strata = block, type = "free",
-+ permute.strata = TRUE))
- [1] 11 12 13 14 15 1 2 3 4 5 6 7 8 9 10 16 17 18 19 20
->
-> ## Simple function using permute() to assess significance
-> ## of a t.test
-> pt.test <- function(x, group, control) {
-+ ## function to calculate t
-+ t.statistic <- function(x, y) {
-+ m <- length(x)
-+ n <- length(y)
-+ ## means and variances, but for speed
-+ xbar <- .Internal(mean(x))
-+ ybar <- .Internal(mean(y))
-+ xvar <- .Internal(cov(x, NULL, 1, FALSE))
-+ yvar <- .Internal(cov(y, NULL, 1, FALSE))
-+ pooled <- sqrt(((m-1)*xvar + (n-1)*yvar) / (m+n-2))
-+ (xbar - ybar) / (pooled * sqrt(1/m + 1/n))
-+ }
-+ ## check the control object
-+ control <- permCheck(x, control)$control
-+ ## number of observations
-+ nobs <- getNumObs(x)
-+ ## group names
-+ lev <- names(table(group))
-+ ## vector to hold results, +1 because of observed t
-+ t.permu <- numeric(length = control$nperm) + 1
-+ ## calculate observed t
-+ t.permu[1] <- t.statistic(x[group == lev[1]], x[group == lev[2]])
-+ ## generate randomisation distribution of t
-+ for(i in seq_along(t.permu)) {
-+ ## return a permutation
-+ want <- permute(i, nobs, control)
-+ ## calculate permuted t
-+ t.permu[i+1] <- t.statistic(x[want][group == lev[1]],
-+ x[want][group == lev[2]])
-+ }
-+ ## pval from permutation test
-+ pval <- sum(abs(t.permu) >= abs(t.permu[1])) / (control$nperm + 1)
-+ ## return value
-+ return(list(t.stat = t.permu[1], pval = pval))
-+ }
->
-> ## generate some data with slightly different means
-> set.seed(1234)
-> gr1 <- rnorm(20, mean = 9)
-> gr2 <- rnorm(20, mean = 10)
-> dat <- c(gr1, gr2)
-> ## grouping variable
-> grp <- gl(2, 20, labels = paste("Group", 1:2))
-> ## create the permutation design
-> control <- permControl(type = "free", nperm = 999)
-> ## perform permutation t test
-> perm.val <- pt.test(dat, grp, control)
-> perm.val
-$t.stat
-[1] -2.342064
-
-$pval
-[1] 0.024
-
->
-> ## compare perm.val with the p-value from t.test()
-> t.test(dat ~ grp, var.equal = TRUE)
-
- Two Sample t-test
-
-data: dat by grp
-t = -2.3421, df = 38, p-value = 0.02452
-alternative hypothesis: true difference in means is not equal to 0
-95 percent confidence interval:
- -1.25582408 -0.09136416
-sample estimates:
-mean in group Group 1 mean in group Group 2
- 8.749336 9.422930
-
->
->
->
-> cleanEx()
> nameEx("permutest.betadisper")
> ### * permutest.betadisper
>
@@ -5590,11 +5131,14 @@
Permutation test for homogeneity of multivariate dispersions
No. of permutations: 999
-Permutation type: free
+
+**** STRATA ****
Permutations are unstratified
-Mirrored permutations?: No
-Use same permutation within strata?: No
+**** SAMPLES ****
+Permutation type: free
+Mirrored permutations for Samples?: No
+
Response: Distances
Df Sum Sq Mean Sq F N.Perm Pr(>F)
Groups 1 0.07931 0.079306 4.6156 999 0.05 *
@@ -7520,7 +7064,7 @@
Formula:
y ~ s(x1, x2, k = knots)
-<environment: 0x107bd3e60>
+<environment: 0x1081c2098>
Estimated degrees of freedom:
2 total = 3
@@ -7997,7 +7541,7 @@
> ### * <FOOTER>
> ###
> cat("Time elapsed: ", proc.time() - get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed: 103.883 1.212 107.845 0 0
+Time elapsed: 101.713 1.044 103.58 0 0
> grDevices::dev.off()
null device
1
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