similar to: Cleaning database: grep()? apply()?

Hey all, I am getting this error: NoMethodError (undefined method `gsub!'' for 2012-01-22 17:00:00 -0500..2012-01-23 00:00:00 -0500:Chronic::Span): in this code: date_range = Chronic.parse(the_date, :guess => false) reports.sum_distance_by_date(date_range).each do |d| u[:m] << d end def

I wonder how one in R can fit a 3rd degree polynomial to some data? Say the data is: y <- c(15.51, 12.44, 31.5, 21.5, 17.89, 27.09, 15.02, 13.43, 18.18, 11.32) x <- seq(3.75, 6, 0.25) And resulting degrees of polynomial are: 5.8007 -91.6339 472.1726 -774.2584 THanks in advance! -- Jonas Malmros Stockholm University Stockholm, Sweden

I''m running into an issue undefined local variable or method `directoryid'' for #<EditorialsController:0x23f1bf8> I have two Models on a legacy database and only one controller called editorials with two actions index and display. I''m trying to pass in a parameter from the results of my search and getting the above error. Example: two tables one is editorial the

Hello, I have written a simple Metropolis-Hastings MCMC algorithm for a binomial parameter: MHastings = function(n,p0,d){ theta = c() theta[1] = p0 t =1 while(t<=n){ phi = log(theta[t]/(1-theta[t])) phisim = phi + rnorm(1,0,d) thetasim = exp(phisim)/(1+exp(phisim)) r = (thetasim)^4*(1-thetasim)^8/(theta[t]^4*(1-theta[t])^8) if(runif(1,0,1)<r){ theta[t+1] = thetasim }

Hello everyone. I use double for loops to fill in matrices, but there are surely better (and computationally faster) ways to perform that task. Could someone show me, given the following example of a double for loop, how this could be done? It is much easier to learn by examples. Val <- matrix(0, nrow=n+1, ncol=n+1) for( i in 0:n){ for(j in 0:i){ Val[j+1, i+1] <- u^j*d^(i-j)

I have a data frame named "database" with panel data, a little piece of which looks like this: Symbol Name Trial Factor1 Factor2 External 1 548140 A 1 -3.87 -0.32 0.01 2 547400 B 1 12.11 -0.68 0.40 3 547173 C 1

I prefer to use R on a linux box and ultimately need things to end up there to serve things up using David Firth's excellent CGIwithR and apache, but one step at a time and I've installed 1.8.1 under win2k. Another question that I'm sure is simple: is there a simple way to find the list of installed libraries I had in my 1.7.1 installation and use that to drive install.packages?

I am trying to sample a subset from a matrix using sample. The size of the matrix is 20X 1532. It works fine with this, but when I transpose the matrix and try to sample it, it returns null. pick.set<-sample(tissue.exp.t,5,replace=FALSE,prob=NULL) Is there something that I am missing here ? Thanks ../Murli

Bill, Alberto, Gabor, Thank you for answering my question. Now I learned about outer() function. That was a straightforward example. But what if I had a matrix, where the last column was filled with values first (again, a for loop), and the rest was filled by using a double loop? OVal <- matrix(0, n+1, n+1) for(i in 0:n){ OVal[i+1, n+1] <- max(Val[i+1, n+1]-K, 0) } for(i in seq(n,1,

Hello, I'm using aov() to analyse changes in brain volume between males and females. For every subject (there are 331 in total) I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). The data looks like this: Subject Sex Lobe Tissue Volume subect1 1 F g 262374 subect1 1 F w 173758 subect1 1 O g 67155 subect1 1 O w 30067 subect1 1 P g 117981

I'm working with a nested model (mixed). I have four factors: Patients, Tissue, sex, and tissue_stage. Totally I have 10 patients, for each patient, there are 2 tissues (Cancer vs. Normal). I think Tissue and sex are fixed. Patient is nested in sex,Tissue is nested in patient, and tissue_stage is nested in Tissue. I tried aov and lme as the following, > aov(gene ~ tissue + gender +

Hi, I am doing an analysis to see if these is tissue specific effects on the gene expression data . Our data were collected from 6 different labs (batch effects). lab 1 has tissue type 1 and tissue type 2, lab 2 has tissue 3, 4,5,6. The other labs has one tissue type each. The 'sample' data is as below:

Hello, I've used this command to analyse changes in brain volume: mod1<-aov(Volume~Sex*Lobe*Tissue+Error(Subject/(Lobe*Tissue)),data.vslt) I'm comparing males/females. For every subject I have 8 volume measurements (4 different brain lobes and 2 different tissues (grey/white matter)). As aov() provides only type I anovas, I would like to use lmer() with type II, however, I have

Dear fellow R-help members, I hope to seek your advice on how to parse/manage a dataset with hundreds of columns. Two examples of these columns, 'cancer.problems', and 'neuro.problems' are depicted below. Essentially, I need to parse this into a useful dataset, and unfortunately, I am not familiar with perl or any such language. data <- data.frame(id=c(1:10))

Dear R users, I have a data frame in the form below, on which I would like to make normality tests on the values in the ExpressionLevel column. > head(df) ID Plant Tissue Gene ExpressionLevel 1 1 p1 t1 g1 366.53 2 2 p1 t1 g2 0.57 3 3 p1 t1 g3 11.81 4 4 p1 t2 g1 498.43 5 5 p1 t2 g2 2.14 6 6 p1 t2 g3 7.85 I

Dear list members, I have written a function, called say Analysis. I supply an Excel file name as an argument, it does analysis on this file and returns a pdf file with specific plots, and a text file with several statistical models' output (I extract certain values from the output and create my own custom dataframe with output). As of now I have to open the script file and load the function

My small brain is having trouble getting to grips with lme() I wonder if anyone can help me correctly set the random = argument to lme() for this kind of setup with (I think) 9 variance/covariance components ... Study.1 Study.2 ... Study.10 Treatment.A: subject: 1 2 3 4 5 6 etc. 28 29 30 Treatment.B: subject: 31

Hi I have to create a json date like {"startDate":"\/Date(1291145744713-0700)\/","endDate":"\/Date(1293824144713-0700)\/"} This is just an example. My case startdate = Time.now-2.day enddate = Time.now I dont know how to convert this to the above format. Please help Thanks -- Posted via http://www.ruby-forum.com/. -- You

Hi, There are 20 subjects grouped by Gender, each subject has 2 tissues (normal vs. cancer). In fact, it is a 2-way anova (factors: Gender and tissue) with tissue nested in subject. I've tried the following: Model 1: lme(response ~ tissue*Gender, random = ~1|subject) Model 2: response ~ tissue*Gender + subject Model 3: response ~ tissue*Gender It seems like Model 1 is the correct one

Dear all, I would like to know if it is possible to fit in R a Cox ph model with time-dependent covariates and to account for hierarchical effects at the same time. Additionally, I'd like also to know if it would be possible to perform any feature selection on this model fit. I have a data set that is composed by multiple marker measurements (and hundreds of covariates) at different time