search for: 0.0125

Dear R help, I have some readings in three dimensions (x, y, z) and an amplitude for each. I'd like to visualize the data using ggplot, using tile plots, as I have some additional point data I would like to eventually overlay on the tile plots. I would like to subset the data by sections, slices if you will, in the z dimension, and plot the data for that slice. I can do all of this, but am

Hi all: Can someone advice me on how to hold the residuals Mean sq value on a string so it can be used in other calculations. I was trying something like this: Msquare<-dfr$Mean sq but fails..Thanks dfr <- read.table(textConnection("percentQ Efficiency 1.565 0.0125 1.94 0.0213 0.876 0.003736 1.027 0.006 1.536 0.0148 1.536 0.0162 2.607 0.02 1.456 0.0157 2.16 0.0103

Dear All I am trying to find a uniroot of a function within another function (see example) but I am getting an error message (f()values at end points not of opposite sign). I was wondering if you would be able to advise how redefine my function so that I can find the solution. In short my first function calculates the intergrale which is function of "t" , I need to find the uniroot of

Hi, I am analyzing a repeated-measures Greco-Latin Square with the aov command. I am using aov to calculate the MSs and then picking by hand the appropriate neumerator and denominator terms for the F tests. The data are the following: responseFinger mapping.code Subject.n index middle ring little ---------------------------------------------------------------------------- 1 1

Dear R-listers, I have a very strange problem. I made a package (under Windows and Linux). The package passed the R CMD Check without problem. Then, I installed the package and executed a function which calls to a 'dll' mod<-frailtyPenal(Surv(time,status)~sex+age+cluster(id), + n.knots=8,kappa1=10000,data=kidney) mod Call: frailtyPenal(formula = Surv(time, status)

I have a fairly large set of data with the following attributes: >str(raw.data) `data.frame': 1429 obs. of 16 variables: $ TStamp :`POSIXlt', format: chr "2001-11-25 02:00:00" "2001-11-25 01:55:00" "2001-11-25 01:50:00" "2001-11-25 01:45:00" ... $ iPDT.AHU14.14: num 0.0122 0.0125 0.0120 0.0120 0.0122 ... $ iPDT.AHU14.15: num 0.0121

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

Hi, In Splus7 this statement xlrmN1 <- sample(c(0,1,2),400 ,prob=c(0.02 ,0.93 ,0.05 )) worked fine, but in R the interpreter reports that the length of the vector to chose c(0,1,2) is shorter than the size of many times I want to be selected from the vector c(0,1,2). Any good reason? See below the error. > xlrmN1 <- sample(c(0,1,2),400 ,prob=c(0.02 ,0.93 ,0.05 )) Error in

Hi, I have a seemingly simple proportional test. ?here is the question I am trying to answer: ? There is a test running each day in the lab, the test comes out as either positive or negative. So at the end of each month, we can calculate a positive rate in that month as the proportion of positive test results. The data look like: ? Month??? ??# positive?????? # total tests??? positive rate

After rx vq was enabled, we never stop polling its socket. This is sub optimal when may lead unnecessary wake-ups after the rx net work has already been queued. This could be optimized by stopping polling the rx net sock when processing both rx and tx and restart it afterward. This could save unnecessary wake-ups and even unnecessary spin locks acquiring with the help of commit

After rx vq was enabled, we never stop polling its socket. This is sub optimal when may lead unnecessary wake-ups after the rx net work has already been queued. This could be optimized by stopping polling the rx net sock when processing both rx and tx and restart it afterward. This could save unnecessary wake-ups and even unnecessary spin locks acquiring with the help of commit

Hi, Let say I have below vector of data-points : Dat = c(-0.444444444444444, -0.25, -0.237449799196787, -0.227467046669042, -0.227454464682363, -0.22, -0.214876033057851, -0.211781206171108, -0.199891067538126, -0.192920353982301, -0.192307692307692, -0.186046511627907, -0.184418145956608, -0.181818181818182, -0.181818181818182, -0.181266261925412, -0.181003118503119, -0.179064587973274,

You need to re-read ?density and perhaps think again -- or do some study -- about how a (kernel) density estimate works. The points at which the estimate is calculated are *not* the values given, nor should they be! Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his

But for my reporting purpose, I need to generate a bell curve like plot based on empirical PDF, that also contains original points. Any idea would be helpful. Thanks, On Mon, Mar 12, 2018 at 3:49 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > You need to re-read ?density and perhaps think again -- or do some study -- > about how a (kernel) density estimate works. The points at

Dear all I have the following data (a shortened extract shown; some replictates of time deleted) to which I fitted the linear model given below: time group mass 11 control 0.019 11 control 0.014 14 control 0.0306 14 control 0.0289 14 control 0.0236 17 control 0.0469 17 control 0.0709 11 five 0.0077 11 five

Dear r-users, I want to use the Cox's ph model to analyze survival data set. How can I extract the model coefs. and Wald test p-value or Score? For example: I use the data set melanom in iSwR package. > library(survival) > data(melanom) > attach(melanom) > cox.model <- coxph(Surv(days,status==1)~sex) > summary(cox.model) Call: coxph(formula = Surv(days, status == 1) ~

Hi all: I have always used SPSS to estimate weekly covariance based on a linear regression model but have to hard code the model Std. Error and the Mean-Square and then execute one week a the time. I was wondering if someone could give me an idea on how to estimate weekly(WK) covariance using the summary and anova of "dfr"(lineal model below). I have to do this for 52

Hello all, I am fitting a Gamma distribution to some data I have using nls(). The function obviously runs into issues when using a 0 as a parameter value. I understand the line alg = "port" can be used to set the lower bounds to prevent this from happening. When I run the code I get the following: Algorithm "port", convergence message: relative convergence (4). I have

Hello, I will try to explain the problem, sorry if it will be a little long... I'm using R to analyze results of cyclic mechanical testing, like this: - apply quasi-sinusoidal load - measure quasi-sinusoidal vertical and horizontal deformations (quasi-sinusoidal load means that load "should be" sinusoidal, but testing machine puts in some noise...) I enclose a sample of data at

Hello, I'm trying to fit experimental data with a model and nls. For some experiments, I have data with x from 0 to 1.2 and the fit is quite good. But it can happen that I have data only the [0,0.8] range (see the example below) and, then, the fit is not correct. I would like to add a constraint, for example : the second derivative must be positive. But I don't know how to add this to