similar to: Comprehensive New Learning Resource for R

Dear List Members, I am working on a below piece of code: Initially have created pie charts with Enlish labels to present the data for Czech Republic, now however I need to print the label with original Czech fonts. When I copy paste from Word, certain fonts get 'simplified' distorting original spelling. How can solve this problem? Is there a package I can download which will support

I know this is not really an R question - it is a query about a recent book on R ("R In Action") by Robert Kabacoff, (Manning Publications 2011). There are many references to interesting topics in R in the book, BUT, I do not find a bibliography/list of references in the book! Does anybody know if there are errata for the book available some place? Thanks, Ravi -- View this message

Can anyone tell me how to calculate quantiles of the studentized maximum modulus distribution using R? Thanks! __________________ Rob Kabacoff, Ph.D. www.statmethods.net [[alternative HTML version deleted]]

Hi all, Since it looks like I''ll be attending FOSDEM, I now need to find some lodging, and if possible I''d like to line up a presentation or four. Someone in the community offered to let me crash with them if I came to the conference (someone with the nick of ''robk'' on IRC, I think), so I''d like to take that person up on it if possible.

I run the following code: library(rpart) data(kyphosis) fit <- rpart(Kyphosis ~ ., data=kyphosis) plot(fit) text(fit, use.n=TRUE) The text labels represent the count of each class at the leaf node. Unfortunately, the numbers are rounded and in scientific notation rather than the exact number of examples sorted by that node in each class. The plot is supposed to look like

Hi all, This is Steven with Manning Publications. I wanted to announce the launch of a new R book: R in Action by Rob Kabacoff. Rob was recently interviewed for this piece on Teradata about the growth of R into new fields and the future of R. The book gives thorough coverage of the R environment with dozens of practical examples of its uses. We're doing a one day 50% off deal on the

Hello R List, I'm trying to run a linear mixed effects analysis on fairly large datasets with lmer (from the lme4 package) on a 32-bit Windows machine running XP with 3 GB of RAM. It's not working. (details below) I've researched the ff and bigmemory packages, but it appears they won't handle the mixed mode dataset I'm analyzing. It has some character fields for the

Dear All, In a package, I want to use PCA function. The structure I used follow this page: http://www.statmethods.net/advstats/factor.html. fit<-principle(mydata, nfactors=9, rotation=TRUE) or: result<-PCA(mydata) But I don't known why R language in my computer noticed: "not found principle", "not found PCA". I download and installed

Hi, I would like to display inter-parameter scatter plots like those with the corrgram package (see upper triangle here: http://www.statmethods.net/advgraphs/images/corrgram2.png ), just that I would like to plot two datasets instead of one. Say one with black and one with red dots. Or a merged dataset where an indicator column is used to assign different colors to particular dots - with still

Hello all, I would like to compare the similarity of two cluster solutions using a validation criteria (such as Hubert's gamma coefficient, the Dunn index the corrected rand index and so on) I see (from here:http://www.statmethods.net/advstats/cluster.html) that the function cluster.stats() in the fpc package provides a mechanism for comparing 2 cluster solutions - *BUT* - it requires me to

I ran this code (several times) from the Quick-R web page ( http://www.statmethods.net/advstats/cart.html) but my cross-validation errors increase instead of decrease (same thing happens with an unrelated data set). Why does this happen? Am I doing something wrong? # Classification Tree with rpart library(rpart) # grow tree fit <- rpart(Kyphosis ~ Age + Number + Start,

Hello, I have a data frame that looks like Position, Relevance 0, 0.151531117072265 0, 0.245532564696541 0, 0.285207130323724 0, 0.302718099889669 0, 0.308213700400889 0, 0.341562706518953 0.0151515151515152, 0.368991215730364 0.0263157894736842, 0.256406702156839 0.0263157894736842, 0.344003157058329 0.0303030303030303, 0.200307950418176 0.0303030303030303, 0.558093143666938 0.04,

I am interested in applying a "classification tree" analysis where the response variable is a censored variable (survival data). I've discovered the package 'party' through this page: http://www.statmethods.net/advstats/cart.html. However, as my sample is not very big I would like to apply 'bootstrap' and use 'random forests', but with my censored response

Hello, I am trying to write a script with the end goal of graphing power (y) as a result of sample size (x) at a variety of effects sizes. I am new to loops, and I think my problem is there. Here's the script, which is modified from the script found at the bootom of http://www.statmethods.net/stats/power.html. ANy help would be much appreciated!mtesche at ualberta.ca library(pwr)

Hi, I have 6 excel files, I want to concatenate all and create one excel files, How to program that in R.(I need the code) Kind regards, SUBRAT SWAIN IMPORTANT NOTICE: The information in this email (and any attachments) is confidential. If you are not the intended recipient, you must not use or disseminate the information. If you have received this email in error, please immediately notify me

Hi, I am trying to produce a grouped bar plot from a data.frame and I'm having difficulties figuring out how to do so. My data is 500 rows by 4 columns and basically looks like so: > head(x) V1 V2 V3 V4 1 XOM 0.2317915 0.1610068 1.6941637 2 AAPL 0.6735488 0.7433611 0.1594102 3 GE 1.2554160 0.9237384 1.6767711 4 IBM 1.6296938 0.3730387 0.5858115 5 CVX

Hi! as my subject says I am struggling with the different of a two-way ANOVA and a (two-way) ANCOVA. I found the following examples from this webpage: http://www.statmethods.net/stats/anova.html # One Way Anova (Completely Randomized Design) fit <- aov(y ~ A, data=mydataframe) # Randomized Block Design (B is the blocking factor) fit <- aov(y ~ A + B, data=mydataframe) # Two Way

I am trying to create a classification tree using either tree or rpart functions but when it comes to plotting the results the formatting I get is different than what I see in all the tutorials (like http://www.youtube.com/watch?v=9XNhqO1bu0A or http://www.youtube.com/watch?v=m3mLNpeke0I&feature=related or http://www.statmethods.net/advstats/cart.html "tree for kyphosis"). I am

Hello dear R help list, I wish to compile a check-list for diagnostic measures for OLS regression. My question: Can you offer more (or newer) tests/measures for the validity of a linear model then what is given here: http://www.statmethods.net/stats/rdiagnostics.html This resource gives a list of measures to test for: OUTLIERS, INFLUENTIAL OBSERVATIONS, NON-NORMALITY, NON-CONSTANT ERROR

Hello, I have a double matrix that I want to represent in a line chart. Although I have seen some examples I still don't manage to get it. My data is this (a double matrix called mymatrix) : Blogs Wikis Redes Etiq. SPC LMS Menor de 30 57.14 28.57 14.29 28.57 57.14 28.57 de 31 a 40 63.83 61.70 29.79 17.02 59.57 70.21 de 41 a 50 72.64 70.75 47.17 20.75 55.66 75.47 Mayor de