similar to: T-test to check equality, unable to interpret the results.

I am receiving the following error while executing KLdiv method: kl<-KLdiv(y) Error in function (classes, fdef, mtable) : unable to find an inherited method for function "KLdiv", for signature "data.frame" the code is as follows: require(flexmix) KLdiv(y) the object y (snippet, actual object contains 188 entries) is as follows: s1p5 s2p5 1 0.6 0.8 2 0.8

Hi, I have a question about the computation of confidence intervals in the zyp package, in particular using the functions zyp.sen and confint.zyp, or zyp.yuepilon. (1) I'm a bit confused about the confidence intervals given by zyp.sen and confint.zyp. When I request a certain confidence interval in the function, the R output seems to deliver another confidence interval, e.g. when I set

Hi, I am trying to interpret the coefficients in the model: RateOfMotorPlay ~ TestNumber + Sex + TestNumber * Sex where there are thee different tests and Sex is (obviously) binary. My results are: Residuals: Min 1Q Median 3Q Max -86.90 -26.28 -7.68 22.52 123.74 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 29.430 6.248

Dear R-help-list, I have a problem in which the explanatory variables are categorical, the response variable is a proportion, and experiment contains technical replicates (pseudoreplicates) as well as biological replicated. I am new to both generalized linear models and mixed- effects models and would greatly appreciate the advice of experienced analysts in this matter. I analyzed the

Hello R-help subscribers, I am analyzing a data set using a mixed logit model, and I have recently discovered some curious behavior. I am hoping you all can help. I first ran the following model in December 2012. lmer(Response.binary ~ ItemType.c * Block + (1 | Subject) + (1 | Word), data=lexdec, family="binomial") I then took a break from the data for the holidays. I returned to

Hi all, I have a large dataset with ~8600 observations that I want to compress to weekly means. There are 9 variables (columns), and I have already added a "week" column with 51 weeks. I have been looking at the functions: aggregate, tapply, apply, etc. and I am just not savvy enough with R to figure this out on my own, though I'm sure it's fairly easy. I also have the Dates

Dear list, I am trying to create a three-way table with percent occurrence instead of raw frequencies. However, I cannot get the results I expected: I have the following table: > ftable(table( mannerDF$agem, mannerDF$target, mannerDF$manner )) <snip> 50 bak 0 0 0 0 1 0 pak 0 0 0 0 3 0 sak

I cannot understand the following error printed out when I try to get the extrema of my time series. I would appreciate some suggestion as I really cannot interpret the error. I might not be using a proper set of parameters in calling such functions. I am learning by doing ... > aa.peak <- wavCWTPeaks (aa.tree) Error in `row.names<-.data.frame`(`*tmp*`, value = c("1",

Hello, I have a dataframe (tab separated file) which looks like the example below - two values separated by a comma, and tab separation between each of these. [,1] [,2] [,3] [ ,4] [1,] 0,1 1,3 40,10 0,0 [2,] 20,5 4,2 10,40 10,0 [3,] 0,11 1,2 120,10 0,0 I would like to calculate the percentage of the smallest number separated by the comma by: 1) summing the values e.g. for

Hi All, I have a function that is used with data frames having multiple id's per row and it aggregates the data down to 1 id per row. It also randomly selects one of the within-id values of a variable (mod), which often differ within-id. Assume this data frame (below) is much larger and I want to repeat this function, say 100 times, and then derive the mean values of r over those 100

Dear All, I would like to ask a couple of questions on a LME model. I tested 4 selection lines at 4 food concentrations against a standard competitor stock. I had 3 replicate cages per selection line. In each cage I have 10 vials. I counted the number of wild type flies and competitor stock emerging in each vial. My main question is: is there any difference between selection lines? I did fit

Hi, I am using package deSolve to run some ordinary differential equations (ODE) as part of a mathematical modeling project. I have solved for the following equilibrium states: Seq1<-a*(1-Neq1)/(f*Veq1+m+d) Ceq1<-(f*Seq1*Veq1+g*Ieq1+r*(1-Neq1)-b1*Veq1*Ieq1)/(b2+m+d+g) Ieq1<-(-b2*Ceq1)-r*(1-Neq1)/(b1*Veq1-g-u) Veq1<-o*(Ceq1+Ieq1)/e I want to take the differential of both sides of

Hi, I appologise if this is a rudimentary question and long winded but I just wanted to let ye know where I'm comming from. I'm new to R and I'm trying to use the 'randomForest' package to classify and predict. The Error message that is troubling me is: > pr<-predict(predictors,rf1, ext=ext) Error in x[...] <- m : NAs are not allowed in subscripted assignments In

I am caught in a mental trap. Why isn't the between groups variance estimated (0.0038) to be around the value with which I generated the data (0.0002)? Thanks Toby set.seed(76589437887) fph = 0.4 Sigh = sqrt(0.0002) Sigi = sqrt(0.04) ci = 1 fpi = matrix(,7200,3) for (i in 1:90) { fph = rnorm(1, fph, Sigh) for (k in 1:80) { fpi[ci,1:3] = matrix(c(i, k, rnorm(1, fph, Sigi)),1) ci