Displaying 20 results from an estimated 207 matches for "dissimilarities".

2004 Jun 29

1

PAM clustering: using my own dissimilarity matrix

...triangular) as input for
pam() or /
/ > fanny() clustering algorithms. /
/ > The problem is that this algorithms can only accept a dissimilarity /
/ > matrix, normally generated by daisy(). /
/ > However, daisy only accept 'data matrix or dataframe. Dissimilarities /
/ > will be computed between the rows of x'. /
/ > Is there any way to say to that your data are already a similarity /
/ > matrix (triangular)? /
/ > In Kaufman and Rousseeuw's FORTRAN implementation (1990), they
showed an /
/ > opt...

2013 Sep 06

1

Fwd: calculating dissimilarity index of islands (vegan and betapart)

Dear List,
This is Elaine, a postgraduate studying in bird distributions in East Asia.
I want to calculate Simpson dissimilarity index,
based on a presence/absence matrix of bird species in islands in East Asia.
(matrix row: 36 islands/matrix column: species ID)
(R package vegan to make NMDS and R package betapart)
In most papers using vegan for NMDS and betapart for

2013 Dec 08

3

Why daisy() in cluster library failed to exclude NA when computing dissimilarity

...;/stat.ethz.ch/R-manual/R-devel/library/cluster/html/daisy.html
But why when I tried this code
library(cluster)
x <- c(1.115,NA,NA,0.971,NA)
y <- c(NA,1.006,NA,NA,0.645)
df <- as.data.frame(rbind(x,y))
daisy(df,metric="gower")
It gave this message:
Dissimilarities :
x
y NA
Metric : mixed ; Types = I, I, I, I, I
Number of objects : 2
Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
I welcome other alternative than gower.
I expect the dissimilarity output give...

2003 Jan 07

2

Extracting means for given strata from dissimilarity object

Is there a way of extracting mean distance or dissimilarity for a given
strata from a 'dist' or 'dissimilarity' object, e.g. extract mean distances
for each species in Anderson's iris data?
data(iris)
iris.dist<-dist(iris[,1:4])
then what?
Mikkel Grum, PhD
Genetic Diversity Scientist
International Plant Genetic Resources Institute (IPGRI)
Sub-Saharan Africa Group
***

2004 Dec 08

2

similarity matrix conversion to dissimilarity

...elated and cannot be trimmed to the same length, I am at a loss for
what to do.
For a set with so many unrelated sequences of different lengths, the
only thing I have been able to is an all-against-all BLAST to create
the matrix, but this gives high scores for similarities, not high
scores for dissimilarities. The only thought I had was to use the
reciprocal of the BLAST score as some perverse measure of distance.
I am not subscribed to the list, so can I ask for responses directly to
my email address?
Thank-you,
Tom Isenbarger
--
isen at plantpath.wisc.edu
thomas a isenbarger
(608) 265-0850

2006 Sep 26

0

cauculating dissimilarities in R

Dear All,
I?ve got a statistical question on calculating
dissimilarities in R.
I want to calculate the different types of dissimilarities
on the ?flower? dataset found in the package
?cluster?. Flower is a data frame with 18 observations
on 8 variables. Variable 1 and 2 are binary, variable 3 is
asymmetric binary, variable 4 is nominal, variable 5 and 6
are ordered and...

2011 Jun 23

0

MST dissimilarity

Dear R-helpers,
I need to quantify dissimilarity of two minimum spanning trees,
specifically dissimilarity of their topologies. (They connect the same
objects but they are calculated from different sets of variables.)
Are you aware of any R-function doing this?
Best regards
Ondrej Mikula

2013 Mar 08

0

analytical strategy for MDS/ smacof /dissimilarity matrix

Dear all,
My data includes almost three thousand people who rank ten categories into
three variables. The simple example below is almost same except I have many
missing values.
x <-
cbind(
sample( LETTERS[1:10] , 3000 , replace = TRUE ) ,
sample( LETTERS[1:10] , 3000 , replace = TRUE ) ,
sample( LETTERS[1:10] , 3000 , replace = TRUE )
)
I try to figure

2016 Apr 12

1

Dissimilarity matrix and number clusters determination

Hi,
I already have a dissimilarity matrix and I am submitting the results to
the elbow.obj method to get an optimal number of clusters. Am I reading
the below output correctly that I should have 17 clusters?
code:
top150 <- sampleset[1:150,]
{cluster1 <- daisy(top150
, metric = c("gower")
, stand = TRUE
, type = list(symm

2010 Sep 21

1

partial dbRDA or CCA with two distance objects in Vegan.

I am trying to use the cca/rda/capscale functions in vegan to analyse
genetic distance data ( provided as a dist object calculated using
dist.genpop in package adegenet) with geographic distance partialled out
( provided as a distance object using dist function in veganthis method
is attempting to follow the method used by Geffen et al 2004 as
suggested by Legendre and . FORTIN

2005 Apr 20

4

results from sammon()

Dear all,
I'm trying to get a two dimensional embedding of some data using different
meythods, among which princomp(), cmds(), sammon() and isoMDS(). I have a
problem with sammon() because the coordinates I get are all equal to NA.
What does it mean? Why the method fails in finding the coordinates? Can I do
anything to get some meaningful results?
Thank you very much
Domenico

2011 Mar 18

1

akima::interp "scales of x and y are too dissimilar"

Dear R users,
I want to do a fitted.contour plot of selected columns of a dataframe M with
M$AM and M$Irradiance as x and y axes respectively. The level of the contour
shall be determined by M$PR.
Some words on my data first. Dataframe M looks like:
head(M$Irradiance)
[1] 293 350 412 419 477 509
head(M$AM)
[1] 2.407 2.161 1.964 1.805 1.673 1.563
head(M$PR)
[1] 70.102 72.600 75.097 80.167

2006 Aug 03

1

questions on plotting dedrograms

Hi,
i've two questions concerning the plot of a dendrogram. first, i use
hclust for clustering and if i plot the dendrogram, then the maximal
height is the maximal dissimilarity found in my data. but i want to have
a arbitary maximal height. for example if the maximal dissimilarity in
my data is 50 and i want a height of 100, the plot should be compressed
by 1/2 and the line to the

2013 Jun 22

1

metaMDS Error, Nan similar or negative values

...0 0 74 0 169
When I tried to perform metaMDS, it was not working, with the error
> ord1 <- metaMDS(
X
="bray")
Square root transformation
Wisconsin double standardization
Error in if (any(dist < -sqrt(.Machine$double.eps))) warning("some
dissimilarities are negative -- is this intentional?") :
missing value where TRUE/FALSE needed
In addition: Warning messages:
1: In distfun(comm, method = distance, ...) :
you have empty rows: their dissimilarities may be meaningless in method
“bray”
2: In distfun(comm, method = distance, ...) : missi...

2013 Jul 22

1

about mix type clust algorithm

Hi:
I have tried to find the appropriate clust algorithm for mixed type of data.
The suggested way I see is:
1. use daisy to get the dissimilarity matrix
2. use PAM/hclust by providing the dissimilarity matrix, to get the clusters
but by following this, when the data set grows bigger say 10,000 rows of data, the dissimilarity matrix will be O(n^2), and out of memory will occur.
I

2006 Jun 01

9

@model.errors.empty? => true; @model.valid? => false

Hi,
So, how can the situation described in the subject come to be?
In other words, what could be invalidating the model, yet not
generating an error?
thanks,
jh
ps.
here''s the breakpoint session paste:
irb(#<#<Class:0xb72eec00>:0xb72eeb10>):003:0> @project.errors.empty?
=> true
irb(#<#<Class:0xb72eec00>:0xb72eeb10>):004:0> @project.valid?
=> false

2017 Aug 17

0

PAM Clustering

Sorry, I never use pam. In the help, you can see that pam require a
dataframe OR a dissimilarity matrix. If diss=FALSE then "euclidean" was use.So,
I interpret that a matrix of dissimilarity is generated automatically.
Problems may be in your data. Indeed
pam(ruspini, 4)$diss
write a dissimilaty matrix
while
pam(MYdata,10)$diss
wite NULL
2017-08-17 16:03 GMT+02:00 Sema Atasever

2017 Aug 17

2

PAM Clustering

Dear Germano,
Thank you for your fast reply,
In the above code, *MYData *is the actual data set.
Do not we need to convert *MYData to *the dissimilarity matrix using
*pam(as.dist(**MYData**), k = 10, diss = TRUE*)* code line?*
*Regards.*
On Thu, Aug 17, 2017 at 2:58 PM, Germano Rossi <germano.rossi at gmail.com>
wrote:
> try this
>
> MYdata <-

2013 Apr 11

1

Ordination Plotting: Warning: Species scores not available

Hi,
I am working with a species-by-trait .csv file (columns=traits, rows=species) and get the following warning message when trying to plot results of both metaMDS and pcoa:
"Warning message:
In ordiplot(x, choices = choices, type = type, display = display, :
Species scores not available"
I am using a Gower's transformation in both procedures within the metaMDS or pcoa

2008 Sep 03

1

how to reduce stress value in isoMDS?

I apply isoMDS to my data, but the result turns out to be bad as the stress
value stays around 31! Yeah, 31 ,not 3.1... I don't know if I ignore
something before recall isoMDS.
My code as follow:
m <- read.table("e:/tsdata.txt",header=T,sep=",")
article_number <- ts(m, start = 2004,end=2008, frequency = 1
,names=colnames(m))