similar to: barplot with lines instead of bars

I have a dataset which contains some missing values, and I need to replace them with zeros. I tried using the following: x <- matrix(data=rep(c(1,2,3,NA),6), ncol=6, nrow=6) y <- matrix(data=0, ncol=ncol(x), nrow=nrow(x)) for(i in 1:nrow(x)) { for(j in 1:ncol(x)) { y[i,j] <- ifelse(x[i,j]==NA, 0, x[i,j]) }} But y returns an NA matrix. I'd appreciate any help. -- View this

I need to store each matrix generated in a loop. I've been working with the CUSUM algorithm and I've been trying to implement it in R. What I need to do with my dataset is to create 1000 randomized datasets and cumulative sum them all and store all of those randomized CUSUMed datasets for further analysis and creation of the simulation envelope in the CUSUM chart. But I can't manage

Hi R-help, I have a dataframe consisting of a time-series [t, v]. The timestamps aren't at all evenly spaced. The values are continuous. I've been able to graph this as a step function (which is what it should be) in ggplot2, using the 'step' geom. Now I would like to take the integral of the step function. For this and other reasons, is there a way to convert this into an evenly

Below are the results for the Polyhedron 2005 benchmarks compiled with llvm/compiler-rt/dragonegg 3.3svn at r182439 against current FSF gcc 4.7.3svn and 4.8.1svn. The only major bug remaining in the dragonegg 3.3svn support for gcc 4.8.x is http://llvm.org/bugs/show_bug.cgi?id=15980 which results in unresolved symbols for _iround and _iroundf in the aermod and rnflow testcases. Note that this

is there a way to use the actual index value for plotting zoo objects this is the way that the index is set up and a sample range of what I would like to plot 01/01/06 00:00:00 - 01/01/06 23:45:00 { library(zoo) # chron library(chron) fmt.chron <- function(x) { chron(sub(" .*", "", x), gsub(".* (.*)", "\\1:00", x)) }} x <- structure(c(15.57, 15.5,

Let's say I have a variable, day, which is saved as a factor with 7 levels, and I use it in a logistic regression model. I ran the model using the car package in R and printed out the results. mod1 = glm(factor(status1) ~ factor(day), data=mydat, family=binomial(link="logit")) print(summary(mod1)) The result I get is: Coefficients: Estimate Std. Error z value

I have a series of numbers I'm wanting to plot. They come from a nanodrop machine, which graphs with a specific x and y indices. X goes from 220nm to 350nm, which I can set. But the y axis should go from -5 to 65, but I'm finding it impossible to hardcode that. I've looked. I've typed ?plot at the R prompt. Google has not been my friend. _R Graphics_, if it holds the key, has not

I am using the randomForest package. I have found that multiple runs of precisely the same command can generate drastically different run times. Can anyone with knowledge of this package provide some insight as to why this would happen and whether there's anything I can do about it? Here are some details of what I'm doing: - Data: ~80,000 rows, with 10 columns (one of which is the

Hi Chris, >> PS: With -fplugin-arg-dragonegg-enable-gcc-optzns the LLVM optimizers are run at >> the following levels: >> >> Command line option LLVM optimizers run at >> ------------------- ---------------------- >> -O1 tiny amount of optimization >> -O2 or -O3 -O1 >> -O4 or -O5

Hi all, I have been trying to reproduce an analysis from Douglas Montgomery?s book on design and analysis of experiments. Table 6.10 of example 6.2 on page 246, gives a table as follows: > NPK <- expand.grid(A=mp,B=mp,C=mp,D=mp) > Rate <- c(45,71,48,65,68,60,80,65,43,100,45,104,75,86,70,96) > filtration <- cbind(NPK,Rate) > filtration A B C D Rate 1 - - - - 45 2

On Oct 8, 2011, at 12:05 PM, Duncan Sands wrote: > PS: With -fplugin-arg-dragonegg-enable-gcc-optzns the LLVM optimizers are run at > the following levels: > > Command line option LLVM optimizers run at > ------------------- ---------------------- > -O1 tiny amount of optimization > -O2 or -O3 -O1 > -O4 or -O5

I've got a list of 5 matrices that are each 5 x 6. I'd like to end up with a 5 x 6 matrix that contains the mean value of the 5 original matrices. I can do this by brute force, but there must be a better way than making each matrix into a vector and then remaking a matrix thanks very much for any help david freedman ll=list(structure(c(9.7, 17.6, 20.8, 24.1, 33.8, 14.5, 25.7, 29.8,

On Wed, May 29, 2013 at 03:25:30PM +0200, Duncan Sands wrote: > Hi Jack, I pulled the loop vectorizer and fast math changes into the 3.3 branch, > so hopefully they will be part of 3.3 rc3 (and 3.3 final!). It would be great > if you could redo the benchmarks rc3. > Duncan, As requested, appended are the updated Polyhedron 2005 benchmark results with both RC1 and RC3 llvm 3.3

Dear all I am a BEGINNER and have R on my Mac. I saved my excel file as .txt file, I have just one column with first row as the column name. My file when read by R looks like this. After reading the table I try to make a histogram by hist(dbh), it says object dbh not found. What am I doing wrong? thanks dbh 1 11.53 2 16.05 3 7.36 4 16.05 5 8.66 6 12.74 7 22.93 8 7.55 9

Dear R users I get different F-statistic results for a "within" model, when using "time" or "twoways" effects in plm() [1] and when manually specifying the time control dummies [2]. [1] vignette("plm") [2] http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf Two examples below: library("AER") data("Grunfeld", package =

R Help- I have a list of 102 vectors all of the same type and length called time.by.orig. I can't data.frame(time.by.orig) but I can data.frame(time.by.orig[1:length(time.by.orig)]). Why is this? Thanks for your help. str(time.by.orig) List of 102 $ 1 : num [1:102] 1.34 17.39 14.36 14.22 7.56 ... $ 2 : num [1:102] 17.5 0.7 17.7 12.4 10.4 ... $ 3 : num [1:102] 14.063 17.568

Hello, I am doing simulations, and I generate a list at each iteration (with three component matrices in the example below), saving the results in a list. For example, after two iterations, I have something like > str(sim.theta) List of 2 $ :List of 3 ..$ : num [1:6, 1:4] -3.67 -1.07 -2.99 -18.38 -3.26 ... ..$ : num [1:6, 1:6] -7.56 -3.14 -4.99 1.03 2.79 ... ..$ : num [1:6, 1:4]

Hello everyone! I have a data frame of 136 variables with 270 observations. I would like to create a new data frame such that each element of that data frame contains the maximum value of the 6 prior lags of the initial data frame. So for example, if my original data frame, A, were A1=c(7.72, 7.94, 7.56, 7.54, 0.93, 0.59, 7.21, 8.00, 7.19, 7.57)A2=c(4.27, 3.70, 3.80, 3.67, 3.83, 3.95, 4.02, 2.06,

Dear R developers, I have encountered strange behaviour of fitdistr for gamma in recent R build i.e. 2.2.0. I have attached the code for data at the end of this mail so you can reproduce the problem. In short, I am able to run fitdistr under 2.1.0 without problems, while I get the following error under 2.2.0 (Version 2.2.0 Patched (2005-11-15 r36348)) > fitdistr(otm, "gamma") Error

Hello All, This might seem elementary to everyone, but please bear with me. I've just spent some time fitting poly functions to time series data in R using lm() and predict(). I want to analyze the functions once I've fit them to the various data I'm studying. However, after pulling the first function into Octave (just by plotting the polynomial function using fplot() over