similar to: Need help optimizing/vectorizing nested loops

Dear arun and all R users, I will first of all try to simply define my issue.. I have data in the following format Year Discharge dd/mm/yyyy x .. … … … There are some NA values in the discharge which I would like to predict by using “predict command”. I cant figure out the way to write the coding for that. Could you please help me on that??? I have also ,written

Hi: I am using a subset of the below dataset to predict PRED_SUIT for the whole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L,

Hello, When i run the code below from Weibull distribution with 30% censoring by using optim i get an error form R, which states that Error in optim(start, fn = z, data = q, hessian = T) :? ? objective function in optim evaluates to length 25 not 1 can somebody?help me remove this error. Is my censoring approach correct. n=25;rr=1000 p=1.5;b=1.2 for (i in 1:rr){ q<-c(t,cen)

Dear list, i am a student of psychology and have to do a multilevelanalysis on some data. About that i have one general and one specific question. This is what i have copied from the help-file on lme: data(bdf) fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf, random = ~ IQ.ver.cen | schoolNR) summary(fm) after summary(fm) i get the following error:

Hi, there: It's my first time to post question in this forum, so thanks for your tolerance if my question is too naive. I am using a nonparametric smoothing procedure in sm package to generate smoothed survival curves for continuous covariate. I want to truncate the suvival curve and only display the part with covariate value between 0 and 7. The following is the code I wrote:

Hello all, I am trying to use stepwise procedure to select covariates in Cox model and use bootstrap to repeat stepwise selection, then record how many times variables are chosen by step() in bootstrap replications. When I use step() (or stepAIC) to do model selection, I got errors. Here is the part of my code for (j in 1:mm){ #<--mm=10 for (b in 1:nrow(reg.bs)){ #<--bootstrap 10

Hi all - (this is posted to r-help and R-SIG-MAC) OSX 10.3.7, R 2.0.1, lme4/Matrix/latticeExtra latest, fresh install of R. MASS loaded (or not). I am getting an error message for the print() and summary() commands with all lme models I try and run in lme4 (GLMM's work fine). Using the example from the lme help, summary and print produce the following errors, despite the model being

Hi , I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide

Dear all, I?m analyzing this dataset containing biodiversity indices, measured over time (Week), and at various contaminant concentrations (Treatment). We have two replicates (Replicate) per treatment. I?m looking for the effects of time (Week) and contaminant concentration (Treatment) on diversity indices (e.g. richness). Initial analysis with GAM models showed temporal autocorrelation of

Hi, Found this in logfiles: Jul 25 14:12:38 dovecot: pop3(cen at so.red): Error: UIDL: File name lookup failed: Message was expunged Jul 25 14:12:38 dovecot: pop3(cen at so.red): Disconnected: POP3 UIDLs couldn't be listed top=187/356348, retr=0/0, del=0/1207, size=789346199 Jul 25 14:12:38 dovecot: pop3(cen at so.red): Panic: file ioloop.c: line 39 (io_add_file): assertion failed: (fd

Dear all, I tried to use "step" function to do model selection, but I got an error massage. What I don't understand is that data as data.frame worked well for my other programs, how come I cannot make it run this time. Could you please tell me how I can fix it? ***************************************************************************************************

I want to get access to the code of an S4 method in order to possibly modify a function to accomplish my particular needs: in my case the function in is cenfit() from the package NADA Now, given my reproducible example: my.ex<-structure(list(TEC = c(0.21, 0.077, 0.06, 0.033, 0.014, 0.0072), LR = c(0L, 0L, 1L, 0L, 1L, 0L)), .Names = c("TEC", "LR"), class =

hello, I have a graph and i use qgraph package to calculate centrality parameters. Now I want to know the maximum value of shortest path for each vertex with discarding the Inf value in short pathes. For this I use the ShortestPathLengths of centrality function in qgraph. but when I want to get the maximum the result is wrong. here is my code: cen<-centrality(Q)

Hello, I have being trying to estimate the parameters of the?generalized?exponential distribution. The random number generation for the GE distribution is?x<-(-log(1-U^(1/p1))/b), where U stands for uniform dist. The data i have generated to estimate the parameters is right censored and the code is given below; The problem is that, the newton-Raphson approach isnt working and i do not know what

HI I am trying to analyse data which is left-censored (i.e. has values below the detection limit). I have been using the NADA package of R to derive summary statistics and do some regression. I am now trying to carry out regression on paired data where both my X and Y have left-censored data within them. I have tried various commands in R: rega = cenreg(Cen(conc, cens_ind) ~ Gp_ident))? with

Would someone be able to help with this question? I'm using the Gcmrec, Survrec, and Design packages to do a power analysis on simulated data. I'm receiving an error after using the Survr function that all data must have a censoring time even after using the gcmrec function: newdata<-addCenTime(olddata). My program is below. I'd greatly appreciate any help!

If anyone has a few extra CPU cycles to spare, I'd appreciate it if you could verify a problem that I have encountered. Run the code below and tell me if it crashes your R before completion. library(lme4) data(bdf) dump<-sapply( 1:50000, function(i) { fm <- lme(langPOST ~ IQ.ver.cen + avg.IQ.ver.cen, data = bdf, random = ~ IQ.ver.cen | schoolNR); cat("

Hard to follow data analysis without data. Try making your example reproducible [1][2][3] and post in plain text (a setting in your emailer). Read the Posting Guide mentioned in the footer to avoid other posting pitfalls. [1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example [2] http://adv-r.had.co.nz/Reproducibility.html [3]

I am hoping someone can help translate some WinBUGS code into R code. I would like to use R to create the C[] matrix required for a car.proper model in WinBUGS, but I am having a difficult time negotiating the coding. The C matrix provides normalized weights for each pair of spatial areas. So the WinBUGS example is as follows: # of the weight matrix with elements Cij. The first J1 elements

Hello, I'm new to R and to Spatial Analysis and got a problem trying to create a Spatial Weights Matrix. *I us the following code to create the Neighbourslist:* >library(maptools) >library(spdep) >library(rgdal) >location_County<- readShapePoly("....") >proj4string(location_County)<- CRS("+proj=longlat ellps=WGS84") >location_nbq<-