similar to: variable values

Hi all, I am wondering whether there is a small bug in the binom.test function of the ctest library (I'm using R 1.6.0 on windows 2000, but Splus 2000 seems to have the same behaviour). Or perhaps I've misunderstood something. the command binom.test(11,100,p=0.1) and binom.test(9,100,p=0.1) give different p-values (see below). As 9 and 11 are equidistant from 10, the mean of the

Hi, In continuation of the discussion of melange comments,about negative value returned in matcher due to logarithm of probabilities. *I**f we make K suitably large, we could clamp each log(K.Pi) to be >= 0, and this change will only affect really low probability terms (those with Pi < 1/K, so you can adjust K to suit):* *W' = sum(i=1,...,n, max(log(K.Pi), 0))* Did you mean for low

When I was computing some joint probabilities, I found that R reported most of the results to to -Inf and thus didn't record the value. I guess it is b/c the joint log(probability) can be extremely small. Is there a way in R to keep the values even if they are small?

Hello, I am trying to run a linear regression analysis on my data set. For some reason most variables are removed due to singularities. My linear regression looks this way (I am using only partial data, which is selected by flags): fm<-lm(log(cplex6.time..sec..[flags]) ~ cplex6.cities[flags] + log(1/features.meanOver.frust[flags]) + log(1/features.meanOver.minDist[flags]) + [...]

lrm does some binning to make the calculations faster. The exact calculation is obtained by running f <- lrm(...) rcorr.cens(predict(f), DA), which results in: C Index Dxy S.D. n missing 0.96814404 0.93628809 0.03808336 32.00000000 0.00000000 uncensored Relevant Pairs Concordant Uncertain 32.00000000

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

Hello I want to calculate natural logarithm of sum of combinations as follow: (R code) { com_sum=choose(2000000,482)*choose(1000000,118)+choose(2000000,483)*choose(1000000,117)+...+choose(2000000,i)*choose(1000000,600-i)+...+choose(2000000,600)*choose(1000000,0) #calculate the sum result=log(com_sum) #calculate the log of the sum } But

Hi all, I'm using R 2.0.1. for Windows to analyze the influence of following factors on response Y: A (four levels) B (three levels) C (two levels) D (29 levels) with E (four replicates) The dataset looks like this: A B C D E Y 0 1 1 1 1 491.9 0 1 1 1 2 618.7 0 1 1 1 3 448.2 0 1 1 1 4 632.9 250 1 1 1 1 92.4 250 1 1 1 2 117 250 1 1 1 3 35.5 250 1 1 1 4 102.7 500 1 1 1 1 47 500 1 1 1 2 57.4

Hello, I've just a little problem using the function optim. Here is the function I want to optimize : test_function(x){(exp(-0.06751 + 0.25473*((x[1]-350)/150) + 0.04455*((x[2]-40)/20) + 0.09399*((x[3]-400)/100) - 0.17238*((x[4]-250)/50)- 0.45984*((x[5]-550)/150)-0.39508*((x[1]-350)/150)* ((x[1]-350)/150) - 0.05116*((x[2]-40)/20)* ((x[2]-40)/20) - 0.27735*((x[3]-400)/100)*((x[3]-400)/100) -

I got the following warning messages when I did a binomial logit regression using glm(): Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, Can some one share your thoughts on how to

Hi everyone, I was looking at loop vectorizer code and wondered if there was any current or planned effort to introduce SIMD implementations of sin/cos/exp/log intrinsics (in particular for x86-64 backend)? Cheers, Dimitri. -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi all, I would like to draw a side by side bar plot.  How can I adjust the the font size for the x-axis?  Furthermore, I'm not sure what to write for 'at=?'.  I tried cex.axis and cex.lab but still fail.  Here is my data and code:   > t(all)            0-100 100-150  150-200 200-250 250-300 300-350 350-400 400-620 obs_data 382.000 177.000 156.0000    93.0 69.0000  45.000

After scouring the online R resources and help pages, I still need clarification on the function rmultinomial(). I would like to create a vector, say of 100 elements, where every element in the vector can take on the value of 0, 1 or 2, and where each of those values have a specific probability. ie. the probability a given element in the vector = 0 is 0.06, 1 = 0.38, 2 = 0.56 (probabilities sum

I would like to compute the MC test (rfm.test) available in the package MarkedPointProcess (for the data BITOEK for example) in order to test the dependence between the marks and their locations. Why the syntax of rfm.test is false here? I have the message : ****************************** ML WARNING! Forbidden values! -- if there are too many warnings try narrower lower and upper bounds for the

Hi everyone, I have a question for R code to merge. Say I have two dataframes: File1 is: V1 V2 V3 V4 1 100 101 name1 2 200 201 name2 2 300 301 name3 3 400 401 name4 3 500 501 name5 4 600 601 name6 4 700 701 name7 File2 is: V1 V2 V3 V4 1 50 55 p1 3 402 449 p2 4 550 650 p3 4 651 660

Hello Could someone please direct me to the correct commands for adding accents (grave and aigu) to a letter in a plot title, label, or in added text? I'm sure there's a handy list somewhere, but I've failed in coming up with the correct search words to find it. Thank you muchly! Jen

> On Apr 6, 2018, at 8:03 AM, David Winsemius <dwinsemius at comcast.net> wrote: > > >> On Apr 6, 2018, at 3:43 AM, g l <gnulinux at gmx.com> wrote: >> >>> Sent: Friday, April 06, 2018 at 5:55 AM >>> From: "David Winsemius" <dwinsemius at comcast.net> >>> >>> >>> Not correct. You already have

Hi all, I love the elegance of Markaby for HTML generation. I''d like to do something similar for SVG, e.g.: svg11 do title "Slide Title" rect({:x=>2,:y=>2,:width=>508,:height=>318,:fill=>"aqua"}) g({:style=>"fill:blue; stroke:black", :transform=>"translate(17,-38)"}) do circle({:cx=>70, :cy=>100,

Hello, R users, I have two factors (treat, section) anova design experiment where there are 3 replicates. The objective of the experiment is to test if there is significant difference of yield between top (section 9 to 11) and bottom (section 9 to 11) of the fruit tree under treatment. I found that there are interaction between two factors. I wonder if I can contrast means from levels of

Dear R users, according the help(log), the function log2(x) should give the natural logarithm of x. I expect in case of x=2 to to get 0.6931, however, R gives me 1 as a result. Similar, logb(2,2) gives 1 again. I'm wondering if I have missed something ? Yours Frank -- Frank Mattes, MD e-mail: f.mattes at ucl.ac.uk Department of Virology fax 0044(0)207 8302854 Royal Free Hospital