similar to: SUMMARY: making contour plots using (x,y,z) data

Folks, The contour() function wants x and y to be in increasing order. I have a situation where I have a grid in x and y, and associated z values, which looks like this: x y z [1,] 0.00 20 1.000 [2,] 0.00 30 1.000 [3,] 0.00 40 1.000 [4,] 0.00 50 1.000 [5,] 0.00 60 1.000 [6,] 0.00 70 1.000 [7,] 0.00 80 0.000 [8,] 0.00 90

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need

OK, Let's try this again! Here is the reproducible script; it is long because I had to copy the panel dataset here. My question is related to systemfit; I don't know how to get the result for the entire panel. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) install.packages("systemfit")

I can't get my simultaneous equations to work using system fit. Please help. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) str(Empdata) Empdata$gnipc<-as.numeric(Empdata$gnipc) install.packages("systemfit") library("systemfit") pdata <- plm.data(Empdata,

I have a table like the following. I want to fit Cm to Vm like this: Cm ~ Cl+Q1*b1*38.67*exp(-b1*(Vm-Vp1)*0.03867)/(1+exp(-b1*(Vm-Vp1)*0.03867))^2+Q2*b2*38.67*exp(-b2*(Vm-Vp2)*0.03867)/(1+exp(-b2*(Vm-Vp2)*0.03867))^2 I use nls, with start=list(Q1=2e-3, b1=1, Vp1=-25, Q2=3e-3, b2=1, Vp2=200). But I always get 'singlular gradient' error like this. But in SigmaPlot I can get the result. How

I am trying to learn how to format Ascii data files for scan or read into R. Precisely for a quickie project, I found some code (at end of this email) to do exactly what I need: To cluster and graph a dendrogram from package (stats). I am stuck on how to format a text file to run the script. I looked at the dataset USArrests (which would be replaced by my data and labels) using UltraEdit. That

I having problem with dendrogram leaf names when I read a tab delimited file into dataframe; I have a text file, tab delimited, using read.table into a data frame as follows: > test1<-read.table("c:\\R\\data\\Tremont4.txt", header=TRUE, sep="\t") When I do this the "test1" data frame is picking up my first column names as part of the data and not the case

Hi there, I am doing multiple comparisons for data that is not normally distributed. For this purpose I tried both functions kruskal{agricolae} and kruskalmc{pgirmess}. It confuses me that these functions do not yield the same results although they are doing the same thing, don't they? Can anyone tell my why this happens and which function I can trust? kruskalmc() tells me that there are no

Hi All- This seems like such a pathetic problem to be posting about, but I have no idea why this testcase does not work. I have tried this using R 2.4.1, 2.4.0, 2.3.0, and 2.0.0 on several different computers (Mac OS 10.4.8, Windows XP, Linux). Below the signature, you will find my test case R code. My point in this folly is to take a dataframe of 300,000 rows, create a filter based on two

#is there a way to get NA in the table of descriptive statistics instead of the function stopping Thank you in advance #data x.f <- structure(list(Site = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("BC", "HC", "RM119", "RM148", "RM179", "RM185",

Recently there was a question on using lme with large data sets. As an experiment I fit a linear mixed-effects model to a data set with about 350,000 observations on 6 predictors, a numerical response, and a single grouping factor. The timings shown below were on a 1.2 GHz Athlon with 1 GB of PC133 memory and 2 GB of swap. The operating system is Debian 3.0 GNU/Linux. The kernel is 2.4.14.

Hi list, I have the following code to compute the acf of a time series acfresid <- acf(residfit), where residfit is the series when I type acfresid at the prompt the follwoing is displayed Autocorrelations of series ?residfit?, by lag 0.0000 0.0833 0.1667 0.2500 0.3333 0.4167 0.5000 0.5833 0.6667 0.7500 0.8333 1.000 -0.015 0.010 0.099 0.048 -0.014 -0.039 -0.019 0.040 0.018

Hi R user I need to read in some values from a computer program output. I can't change the output format because the developer of the program doesn't allow to change the format of output. There are two formats. First one looks like this if I have 10 variables, ------------------------------------------------------------------------------------------------------ [ 1]

Dear list I'm testing a predictor and I produced nice performance plots with ROCR package utilizing the 3 standard command pred <- prediction(predictions, labels) perf <- performance(pred, measure = "tpr", x.measure = "fpr") plot(perf, col=rainbow(10)) The pred object and the perfo object are S4 with the following slots An object of class "performance"

> as.character(seq(-.25,.95,.1)) [1] "-0.25" "-0.15" "-0.05" "0.05" "0.15" "0.25" "0.35" "0.45" "0.55" "0.65" "0.75" "0.85" "0.95" > as.character(seq(-.35,.95,.1)) [1] "-0.35" "-0.25"

You could use cut. The key calculation would be: w <- .05; eps <- 1e-5 breakpoints <- seq(min(kk), max(kk), .05) breakpoints <- floor( (breakpoints + (w/2) + eps) / w) * w values <- cut(kk, c(breakpoints, Inf), right = FALSE) values <- ordered(values) If you don't like the labels produced add lab = breakpoints as a cut arg. On 11/10/05, RenE J.V. Bertin

I have written a wrapper for heatmap.2 called heatmap.w.row.and.col.clust which auto-generates breaks using breaks<-round((c(seq(from=(-20 * stddev), to=(20 * stddev))))/20, digits = 2) #(stddev in this case = 2.5) This has always worked well in the past but now I am getting an error that non-finite breaks are being generated. Drilling down, it seems that my wrapper is generating finite

Hello, When using write.table I am getting two variables pasted together (not by choice). Has anyone else had this happen? Specifically, I have the following: d _ read.dta(paste('/montecarlo/forecast/off/',F,'.dta',sep='')) write.table(d,file=paste('/montecarlo/forecast/off/csv/',F,'.csv',sep=''), row.names=FALSE, col.names=FALSE,

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter