search for: 0.35

Dear R Users, Could you please help me on the following issue? I have a real large yearly data set. For each year I have 365 flow values. Some of the flow values are not known and that’s why you will see NA written in those slots. I wanted to know, is there a way that I can estimate those values? I tried approx command but it seems least helpful for the kind of issue I am up against.

#Hello, #I have three data frames, X,Y and Z with two columns each and different numbers of rows. # creation of data frame X X.alleles <- c(1,5,6,7,8) X.Freq <- c(0.35, 0.15, 0.05 , 0.10, 0.35) Loc1 <- cbind( X.alleles,X.Freq) X <- data.frame(Loc1) #creation of data frame Y Y.alleles <- c(1,4,6,8) Y.Freq <- c(0.35, 0.35, 0.10, 0.20 )

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 group, I am trying to right a code to do the following This is how the test file looks like: Chr start end sample1 sample2 chr2 9896633 9896683 0 0 chr2 9896639 9896690 0 0 chr2 14314039 14314098 0 -0.35 chr2 14404467 14404502 0 -0.35 chr2 14421718 14421777 -0.43 -0.35 chr2 16031710 16031769 -0.43 -0.35 chr2 16036178 16036237 -0.43 -0.35 chr2 16048665 16048724 -0.43 -0.35 chr2 37491676 37491735

Hello everyone, I'm trying to plot 3600 points and my idea is if this value is higher than 0.35 then this point must appear in green colour, if it's smaller than -0.35 then values must appear in red and if values are between -0.35 and 0.35 they must be in yellow. I'm thinking and I'm trying many things but I don't achieve it. Any idea?. Thanks so much Carlos Morales Diego

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

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd

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"

Hi, I like to generate two normal densities such that the overlapping area between them is 0.35. Is there any code/package available in R to do that?? Regards, Lavan -- View this message in context: http://www.nabble.com/densities-with-overlapping-area-of-0.35-tp19384741p19384741.html Sent from the R help mailing list archive at Nabble.com.

Hi group, This is how my test file looks like: Chr start end sample1 sample2 chr2 9896633 9896683 0 0 chr2 9896639 9896690 0 0 chr2 14314039 14314098 0 -0.35 chr2 14404467 14404502 0 -0.35 chr2 14421718 14421777 -0.43 -0.35 chr2 16031710 16031769 -0.43 -0.35 chr2 16036178 16036237 -0.43 -0.35 chr2 16048665 16048724 -0.43 -0.35 chr2 37491676 37491735 0 0 chr2 37702947 37703009 0 0

Folks, A few days ago, I had asked a question on this mailing list about making a contour plot where a function z(x,y) is evaluated on a grid of (x,y) points, and the data structure at hand is a simple table of (x,y,z) points. As usual, R has wonderful resources (and subtle complexity) in doing this, and the gurus of the list showed me the way. Here's a complete working example. One might

Hello, I have two data frames, X and Y, with two columns each and different numbers of rows. # creation of data frame X Loc1.alleles <- c(1,5,6,7,8) Loc1.Freq <- c(0.35, 0.15, 0.05, 0.10, 0.35) Loc1 <- cbind( Loc1.alleles,Loc1.Freq) X <- data.frame(Loc1) #creation of data frame Y Loc2.alleles <- c(1,4,6,8) Loc2.Freq <- c(0.35, 0.35,

Greetings all, I am having difficulty transposing, reshaping, flipping (not sure which) a data frame which is read from a DBF file. I have tried using t(), reshape() and other approaches without success. Can anyone please suggest an way (elegant or not) of flipping this data around ? The initial data is like propsum (defined below), and I want it to look like tpropsum once reformed. >

Hello: I would like to be able to do a 3D scatter plot from 3 variables, 2 independent and 1 dependent. The closest R function I could find for this is "cloud". However cloud uses, as input, a matrix where the value of each matrix element is the dependent variable value at that matrix coordinate. My problem is that the independent variable values are floating point and can be of

Hi, I have two data sets look like below: ========================== state count1 percent1 CA 19 0.34 TX 22 0.35 FL 11 0.24 OR 34 0.42 GA 52 0.62 MN 12 0.17 NC 19 0.34 state count2 percent2 FL 22 0.35 MN 22 0.35 CA 11 0.24 TX 52 0.62 ========================== How to combine these two data set and make it look like below?

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd

CentOS Errata and Security Advisory 2012:0332 Critical Upstream details at : https://rhn.redhat.com/errata/RHSA-2012-0332.html The following updated files have been uploaded and are currently syncing to the mirrors: ( sha256sum Filename ) i386: eef838fd9f66259aafeea6ed7376d513e6250ee62a390fd83190a90d7b8f6f87 samba-3.0.33-0.35.el4.i386.rpm

Dear R Users,i am very new to R. I want your help on an issue regarding distance matrix and cluster analysis i had discharge data of 4 rivers(a,b,c,d) in 4 vectors each having 364 values > dput(qmu)structure(list(a = c(0.26, 0.25, 0.25, 0.25, 0.24, 0.23, 0.22, 0.21, 0.21, 0.21, 0.2, 0.19, 0.19, 0.19, 0.19, 0.18, 0.18, 0.18, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17,

> 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"

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