similar to: Randomised Block Design

As described here, "Markdown will... perform a bit of randomized decimal and hex entity-encoding to help obscure your address from address-harvesting spambots" on automatic email address links like <rwhe at ludism.org>. http://daringfireball.net/projects/markdown/syntax#autolink I have had a problem with my RSS feed for months, where certain entries would refresh every hour or

I''ve spent some time converting my website from php to RoR, and so far, I''m loving every bit of Rails. However, I''ve stumbled across a problem. On my old page, I''ve had a random quote display at a specific location, and I''d like to replicate this with RoR. Basically, I thought I would be able to add all quotes into a specific table in the database,

Hi I just started using RGui.exe under widnows. I have a text file containing date arranged in columns and rows, each column has the same format, each row with different formats. 3 of the columns are something like this 1/12/2006 3:59:45 PM I need to calculate the different in seconds between 2 selected periods using their row’s index My solution: Read the file in a data frame and

Hi I want to use order() to get the order of a vector. But I would need a different behavior when ties occur: similar to the parameter ties.method = "random" in the rank() function, I would need to randomise the ties. Is this possible? Example: x <- rep(1:10, 2) order(x) [1] 1 11 2 12 3 13 4 14 5 15 6 16 7 17 8 18 9 19 10 20 order(x) [1] 1 11 2 12 3 13 4 14 5 15

Hello :) I have two data frames, one has properties taken on a piece by piece basis and the other has performance on a lot by lot basis. I wish to combine these two data frames but the problem is that each lot has multiple pieces and hence i need to take a mean of the properties of multiple pieces and match it to the row having data about the lot. I was wondering if there is a simple commmand,

Dear R-core There is a different output for the apply function due to the change of unlist as mentioned in the R news. Newly, applying as.factor() (or factor()) in str(dat <- data.frame(x = 1:10, f1 = gl(2,5,labels = c("A", "B")))) (d1 <- apply(dat,2,as.factor)) newly returns a character matrix while in R-2.3.1 the same command resulted in an integer matrix that was

Hello everbody, i'm currently using the anova()-test for a small data.frame of 40 rows and 2 columns. It works well, but is there any preconditions for a valid variance analysis, that i should consider? Thank you for your answer, Daniel

Dear R-list I have a question concerning the argument "adjustSigma" in the function "lme" of the package "nlme". The help page says: "the residual standard error is multiplied by sqrt(nobs/(nobs - npar)), converting it to a REML-like estimate." Having a look into the code I found: stdFixed <- sqrt(diag(as.matrix(object$varFix))) if (object$method

hi list, i have to ask you again, having tried and searched for several days... i want to do a TukeyHSD after an Anova, and want to get the adjusted p-values after the Tukey Correction. i found the p.adjust function, but it can only correct for "holm", "hochberg", bonferroni", but not "Tukey". Is it not possbile to get adjusted p-values after

I have some doubts about the validity of my procedure to estimeate linear contrasts ina a factorial design. For sake of semplicity, let's imagine a one way ANOVA with three levels. I am interested to test the significance of the difference between the first and third level (called here contrast C1) and between the first and the seconda level (called here contrast C2). I used the following

hi all, I wish to draw on the same graphic device 3 functions. But i don't want them to be on different graph, i want to compare them on the same I don't need mfrow or mfcol, I need something else... 1 graph on 1 device inside this graph 3 ploted function. I saw something unsing data.frame, but i think it's overkill, and something less complicated must exist, if not why? why not

Hello Could you please suggest a way to find out the r square values for each independent variable while using "lm" for developing a multiple linear regression model. Thank you avneet "I have no data yet. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories instead of theories to suit facts." ~ Sir Arthur Conan Doyle

Hi In mixed-model with lme() How can I obtain Type II SS or Type III SS for fixed effect? Thanks Julien

Hi All. I need a bit of help extracting the residual error variance from the VarCorr structure from lmer. #Here's a 2-way random effects model lmer.1 <- lmer(rating ~ (1|person)+(1|rater), data = dat) #Get the structure vc.fit <- VarCorr(lmer.1) #results in..... $person 1 x 1 Matrix of class "dpoMatrix" (Intercept) (Intercept) 0.7755392 $rater 1 x 1 Matrix

useRs, A no doubt simple question, but I am baffled. Indeed, I think I once knew the answer, but can't recover it. The default contrasts for aov (and lm, and...) are contr.treatment and contr.poly for unordered and ordered factors, respectively. But, how does one invoke the latter? That is, in a data.frame, how does one indicate that a factor is an *ordered* factor such that

Hi all, I just want to understand how R computes p-value in a simple linear regression model? The reason is that in Matlab in the function which "evaluate standard errors for multivariate normal regression", it just provide estimates and standard errors, without giving out p-value, It computes t-statistics as follows: abs(beta_hat/std_beta_hat) how to go further to get p-value?

Hi, I have a model with differents observations Xi. Each observation belongs to a group, either A or B. I would like to minimize a fonction like : sum( Xi - Z)^2 + sum (Xi - aZ -b)^2 A B The first sum contains all observations from group A and the second all observations from group B. I want to find the Z-value wich minimize this function. a and b are predefined parameters.

Hi, I use anova() to find interaction effect and then I need to find data with main effect from those data with interaction effect. How to do that? I used : anova(lm(data~factor1*factor2)), then select data with interaction effect. Then I need to select those data also with main effect of factor1 or factor2, from previous selected data. How to do that? Many thanks for your time on my

Hey, I'm generating a .jpeg file for a web application passing parameters to R via cgi. R gets the parameters by using commandArgs, which are passed to a variable named j and z j<-commandArgs()[3] z<-commandArgs()[4] Later I want to use the characters strings of the argument which the variables are holding for my filename, e.g.: jpeg(file="d:/data/images/jz.jpeg",...)

Hi, The description of all.equal states "is.all.equal should be used for programming, typically in if expressions. It is a simple wrapper using identical as shown in the documentation there.", but is.all.equal is not explicitly defined there (although there is a hint in the comments that is.all.equal <- function(x,y) isTRUE(all.equal(x,y))). Could the documentation be corrected? (or