similar to: Cluster Analysis and PCoA (mixt variables)

Julien, I would just try your best given the journal's style guide and wait for them to change it. For what it is worth, my last paper was corrected as follows. (In text)"...one-way analysis of variance (ANOVA) in R [version 2.14.2 (R Core Team, 2012)]. (reference section) R Core Team. 2012. R: A language and environment for statistical computing. 11 Oct. 2012.

Hello R user and helper! I would like to get a 3d plot with coloured points. I did that: colors<-c(rep("2",7), rep("3",12), rep("4", 24), rep("5", 13), rep ("6", 8), rep("7", 51), rep("8", 1), rep("9", 15), rep("10", 53), rep ("11",3), rep("12",3), rep("13", 8),

Hello every one Working under Windows Xp in French, and R version 2.4.0 (and : > localeToCharset() : "ISO8859-1" ) I am trying to source a file with basic commands. source("R files/InputFile Analysis (Calculs et mises à l'échelle - gestion des pb d'unités).r") and it works fine as long as I do not use command like these ones :

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

Dear R-Helpers, I am working on a dataset containing ca. 500 specimens of 17 different species. The data is three text columns, followed by ca 70 columns of binary data. I'm trying to write a function that will allow me to interactively exclude species using the inofrmation in the third text column. My function, matrix.slicer, appears to work as I intend. However, when I pass the

I think it is an easy question but i haven´t found a solution since I am r beginner. I did this plot3d(PCoA, type="p", col=rainbow(1000),size=5) text3d(PCoA, text=Nam) How can I save it including the labels to a jpg-file? Thanks in advance. Birgit Birgit Lemcke Institut für Systematische Botanik Zollikerstrasse 107 CH-8008 Zürich Switzerland Ph: +41 (0)44 634 8351

My mistake sir. I was literally engrossed in my stupid logic, and while doing so, overlooked the simple and very effective solution you had offered. Sorry once again sir and will certainly try to be very careful in future. Thanks again and have a great weekend sir. Regards Amelia --- On Fri, 7/1/11, Petr PIKAL <petr.pikal@precheza.cz> wrote: From: Petr PIKAL

I try to perform a clustering using an existing dissimilarity matrix that I calculated using distance (analogue) I tried two different things. One of them worked and one not and I don`t understand why. Here the code: not working example library(cluster) library(analogue) iris2<-as.data.frame(iris) str(iris2) 'data.frame': 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7

Dear all, Does anyone know how to run Principal Coordinates Analysis (PCoA) from a squared euclidean dissimilarity matrix with R ? Thanks, ************************* Arnaud DOWKIW Department of Primary Industries J. Bjelke-Petersen Research Station KINGAROY, QLD 4610 Australia T : + 61 7 41 600 700 T : + 61 7 41 600 728 (direct) F : + 61 7 41 600 760 **************************

Hi , I'm currently trying to make available a few fortran subroutines and R functions (which make interface to these subroutines), as an R package. I'm doing it under linux with R 1.9.0 (but hope to do it for windows too). I have trouble for loading my fortran code. Here are the steps involved : 1) In R: # Create tree for package

I have comment the line... But now I see other warning : _WARNING: /ETC/DOVECOT/CONF.D/OLD-90-QUOTA.CONF LINE 39: GLOBAL SETTING MAIL_PLUGINS WON'T CHANGE THE SETTING INSIDE AN EARLIER FILTER AT /ETC/DOVECOT/CONF.D/15-LDA.CONF LINE 13 (IF THIS IS INTENTIONAL, AVOID THIS WARNING BY MOVING THE GLOBAL SETTING BEFORE /ETC/DOVECOT/CONF.D/15-LDA.CONF LINE 13)_ AND... I see an error message :

I am trying to replicate the SAS proc univariate in R. I got most of the stats I needed for a by grouping in a data frame using: all1 <- ddply(all,"ACT_NAME", summarise, mean=mean(COUNTS), sd=sd(COUNTS), q25=quantile(COUNTS,.25),median=quantile(COUNTS,.50), q75=quantile(COUNTS,.75), q90=quantile(COUNTS,.90), q95=quantile(COUNTS,.95), q99=quantile(COUNTS,.99) )

Hi List, I am looking for a variable selection procedure with a forward-backward selection method. Firstly, it is meant to work with the cophenetic correlation coefficient (CPCC) and intended to find the variable combination with the highest cophenetic correlation. Secondly, it is aimed at Gower metric with wards method (though this could be easily extended) aimed at categorical data. What I

I just have thus to comment on the line in the file? --- ########## Philippe - Forums Le 2018-05-16 18:52, Sami Ketola a ?crit : >> On 16 May 2018, at 19.49, forums at mehl-family.fr wrote: >> >> Hi, >> >> In my maillog I see this warning message at every reception of e-mail: >> >> _STATUS=SENT (DELIVERED VIA DOVECOT SERVICE (DOVECONF:

> On 16 May 2018, at 20.16, forums at mehl-family.fr wrote: > > I have comment the line... > > But now I see other warning : > > Warning: /etc/dovecot/conf.d/OLD-90-quota.conf line 39: Global setting mail_plugins won't change the setting inside an earlier filter at /etc/dovecot/conf.d/15-lda.conf line 13 (if this is intentional, avoid this warning by moving the global

hello sorry for my english I would like estimate density for multivariate variable,( f(x,y) , f(x,y ,z) for example) ; for calculate mutual information how is posible with R? thanks Bernard Bernard Palagos Unité Mixte de Recherche Cemagref - Agro.M - CIRAD Information et Technologie pour les Agro-Procédés Cemagref - BP 5095 34033 MONTPELLIER Cedex 1 France

Hi all, I have a dataset with numeric and factor columns of data which I developed a Gower Dissimilarity Matrix for (Daisy) and used Agglomerative Nesting (Agnes) to develop 20 clusters. I would like to use the 20 clusters to determine cluster membership for a new dataset (using predict) but cannot find a way to do this (no way to "predict" in the cluster package). I know I can use

Hi all, I'm working out some Fortran code for which I want to compute the Choleski decomposition of a covariance matrix in Fortran. I tried to do it by two methods : 1) Calling the lapack function DPOTRF. I can see the source code and check that my call is correct, but it does not compile with: system("R CMD SHLIB ~/main.f") dyn.load("~/main.so") I get: Error in

Dear All, It's Eszter from Hungary, a total beginner with R. My problem is the following: I have a dataset with binary values as a comma separated textfile. The samples are in the coloumns and the species are in the rows. I have to transpose it for the further PCoA analysis. There is no problem with reading the dataset. When I transpose the dataset, the original values become

Dear sir, I am extremely sorry for messing up the logic asking for help w.r.t. my earlier mails   I have tried to explain below what I am looking for.     I have a database (say, currency_rates) storing datewise currency exchange rates with some base currency XYZ.   currency_rates <- data.frame(date = c("12/31/2010", "12/30/2010", "12/29/2010",