similar to: Integration and Loop in R

R help list subscribers, I am a new user of R. I am attempting to use R to explore a set of equations specifying the dynamics of a three trophic level food chain. I have put together this code for the function that is to be evaluted by LSODA. My equations Rprime, Cprime, and Pprime are meant to describe the actual equation of the derivative. When I run LSODA, I do not get the output that

Full_Name: Jonathan Lees Version: 1.8.1 OS: GNU/Linux 2.4.20-20.8smp #1 SMP Submission from: (NULL) (152.2.75.114) I am having trouble with the postscript output of images. They have lines on them that are not supposed to be there. I have noticed this on numerous trials of printing various images. I looked at the postscript and I see that it appears to plot each individual block - so perhaps

Hi list I have a data frame I would like to loop over. To begin with I would like crosstabulations using the first variabel in the data frame, which is called "meriter". > table(meriter[[1]], meriter[[3]]) ja nej Annan 0

Hi, there I am a graduate student new to coding in S who is hitting a bit of a wall at present using an "optim" function. I am running into some troubles, and was hoping someone might be able to recognize where I am going wrong. As background: I have constructed a loop that carries out a 365-day calculation for a mass-balance model. Basically, the model depends on 2 variables (p,

Hi, plot(xc, yc, type="l", ylim=c(0,50), xlim=c(0,50), lwd=2, xlab="M", ylab="seconds") abline(a=-think, b=cpustime, lty="dashed", col="red") abline( 2.2, 0, lty="dashed", col = "red") This draws a response time curve an asymptote and a horizontal line. How do I draw a line from the intersection of the asymptote and

[Env: R 2.14.2 / Win Xp] In the script below, I want to select some variables from rrcov::OsloTransect, delete cases with any missing data, and subset the data frame Oslo to remove cases for two levels of the factor litho that occur with low frequency. The checks I run on my new data frame Oslo look OK, but I when I try to fit a multivariate linear model with lm(), I am getting an error:

Dear All, I would like to be able to plot histograms/densities on a semi-log or log-log scale. I found several suggestions online http://tolstoy.newcastle.edu.au/R/help/05/09/12044.html https://stat.ethz.ch/pipermail/r-help/2002-June/022295.html http://www.harding.edu/fmccown/R/#histograms Now, consider the code snippet taken from http://www.harding.edu/fmccown/R/#histograms # Get a random

Hi Ralf, I tried the following > install.packages("RCurl") which went OK, but then same story when I tried to install tseries. > sessionInfo() R version 3.6.1 (2019-07-05) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Debian GNU/Linux 10 (buster) Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.8.0 LAPACK:

Dear All, I am far from being a guru about parallel programming. Most of the time, I rely or randomForest for data mining large datasets. I would like to give a try also to the gradient boosted methods in GBM, but I have a need for parallelization. I normally rely on gbm.fit for speed reasons, and I usually call it this way gbm_model <- gbm.fit(trainRF,prices_train, offset = NULL, misc =

Dear All, Probably a one liner, but I am banging my head against the floor. Consider the following DF <- data.frame( x=1:10, y=10:1, z=rep(5,10), a=11:20 ) mn<-names(DF) but then I cannot retrieve a column by doing e.g, DF$mn[2] I tried to play with the quotes and so on, but so far with no avail. Any suggestion is welcome. Cheers Lorenzo

Hi, all I have a large number of NetCDF files that I need to average and then put the mean in a new NetCDF file. My problem is that I do this every time for files with different variables, so I do not want to hard-code the variables in the new NetCDF file I creat. does anyone know how I can copy ALL the dimensions and variables from one NetCDF file to another, and just put the mean I calculated as

Dear All, I am struggling with the following problem: I am given a NxN symmetric matrix P ( P[i,i]=0, i=1...N and P[i,j]>0 for i!=j) which stands for the relative distances of N points. I would like use it to get the coordinates of the N points in a 2D plane. Of course, the solution is not unique (given one solution, I can translate or rotate all the points by the same amount and generate

Apologies for the previous mail (I sent it off too early by mistake). This is the correct example: rm(list=ls()) D_mean<-seq(-5,5,length=100) y<-exp(-D_mean^2/5) pdf("my.pdf") plot(D_mean,y,type="l",yaxt="n",lty=2,lwd=2,col="black", ylab = list(expression(paste(dN/dlogD[agg]," ["*cm^-3*"]"))), xlab = expression(paste(D[agg],"

Hi, What is the reason for seq.Date to require the 'by' argument and not to default it to 1 in the example below? > seq(from=as.Date("1996-01-01"), to=as.Date("1996-12-01")) Error in seq.Date(from = as.Date("1996-01-01"), to = as.Date("1996-12-01")) : exactly two of `to', `by' and `length.out' / `along.with' must be specified

Hello - I am using glmnet to generate a model for multiple cohorts i. For each i, I run 5 separate models, each with a different x variable. I want to compare the fit statistic for each i and x combination. When I use auc, the output is in some cases is < .5 (.49). In addition, if I compare mean MSE (with upper and lower bounds) ... there is no difference across my various x variables, but

Dear All, I am given some data to analyze. The data is in the form of a Stata database (.dta file). What is the best way to import it into an R dataframe? Is there any particular caveat I should be aware of? Many thanks Lorenzo

Dear All, I implemented an algorithm for (uniform) random rotations. In order to test it, I can apply it to a unit vector (0,0,1) in Cartesian coordinates. The result is supposed to be a set of random, uniformly distributed, points on a sphere (not the point of the algorithm, but a way to test it). This is what the points look like when I plot them, but other then eyeballing them, can anyone

Dear All, Probably something very easy, but I am looking for the most efficient ways to achieve this. Consider the following snippet y<-c('a','b','c','d','e','f','g') x<-rnorm(length(y)) df<-data.frame(y,x) leading to > df$y [1] a b c d e f g Levels: a b c d e f g Now, I would like to replace levels

Hello, Does anyone know how to write the files created by the call of "texi2dvi" in another directory ? Thanks, Matthieu

Dear All, I would like to use a randomForest algorithm on a dataset. The set is not particularly large/difficult to handle, but it has some missing values (both factors and numerical values). According to what I found https://stat.ethz.ch/pipermail/r-help/2005-September/078880.html https://stat.ethz.ch/pipermail/r-help/2007-January/123117.html the randomForest package has a problem with missing