similar to: significance of coefficients in Constrained regression

Dear researchers I wish to plot a box plot without the mean line (the black line) and plot only the mean (red square). Futhermore, is it possible to add standard error and/or stadard deviation? This is an example mytest <- c(2.1,2.6,2.7,3.2,4.1,4.3,5.2,5.1,4.8,1.8,1.4,2.5,2.7,3.1,2.6,2.8) boxplot(mytest,lty = "solid") means <- mean(mytest,na.rm=TRUE) points(means, pch = 22, col

Dear all, how can i do the calculate the C-statistics 95% confidences interval for the cox regression model. Thanks very much for your any help. Paaveenthan _________________________________________________________________ [[elided Hotmail spam]] [[alternative HTML version deleted]]

Dear R users, i am using locfit package developed by loader in R software, my problem is that as i am doing independont forecast using locfit object , i am able to do independont forecast for more than one years simultaniously. But when i am doing one year forecast(single) this code is giving following error... "Warning message: 'newdata' had 1 rows but variable(s) found have 24

Hi. I am trying to use EXTLINUX 3.08 to boot a Soekris net4801 from a CompaqFlash card. BIOS reports the CF card as the first master harddisk. During boot/load the loader hangs after this output: EXTLINUX 3.08 2005-05-19 PXELINUX and LILO works fine on the same setup It this a general problem with Soekris/net4801 and EXTLINUX? Regards Johan Linn?r

Hi all, I am trying to estimate few parameters using the constained maximum likelihood in R and more specifically the constOptim() from the stata package in R. I am programming in Python and using R via the RPy2. In my model, I am assuming that the data follow the Beta-distribution, so I created a simulated dataset by using prespecified values for the parameters and now I am trying to estimate

hi there, can anyone help me on the topic of frag polynoms? i just heard of a friend of mine, that i could build in a functioon called fragpoly (he was talking of such a function in the 'stata' language) in order to improve my process of finding an optimal linear model. instead of trying a vast amount of transformed inputdata to find the best fit and then step backwards down to e.g.

Hi, I read section 5, oop, of the R lang doc, and I am still not sure I understand how to build a class in R for oop. I thought that since I understand the oop syntex of Java and VB, I am wondering if the R programmig experts could help me out by comparing and contrasting the oop syntex in R with that of Java. For example, the basic class structure in Java is like this: public class Bicycle {

Has anyone got Xen working with say, SELinux? Or vserver? Wesley Parish -- Clinesterton Beademung - in all of love. Mau e ki, "He aha te mea nui?" You ask, "What is the most important thing?" Maku e ki, "He tangata, he tangata, he tangata." I reply, "It is people, it is people, it is people." ------------------------------------------------------- This

Hello, I am analyzing some climate time series data using the Mann Kendall package and was wondering if there was a way to calculate the trend using Sen's nonparametric estimator slope in R? Thank you in advance, Barry _________________________ Barry Baker, Ph.D. Global Climate Change Initiative The Nature Conservancy 2424 Spruce St., Suite 100 Boulder, CO 80302 Tel: (303)-541-0322 Fax:

I have an optimization question that I was hoping to get some suggestions on how best to go about sovling it. I would think there is probably a package that addresses this problem. This is an ordering optimzation problem. Best to describe it with a simple example. Say I have 100 "bins" each with a ball in it numbered from 1 to 100. Each bin can only hold one ball. This optimization is

Hello I?m need fitt growth curve with data length-age. I want to evaluate which is the function that best predicts my data, to do so I compare the Akaikes of different models. I'm now need to evaluate if changing the initial values changes the parameters and which do not allow to estimate the model. To do this I use the function nls(); and I randomize the initial values (real positive number).

Dear all,  Who will bail me out. Iam using R with S-Splancs. Anytime i typed in the syntex, an error will appear eg setwd("C:\\TEMP) >dat <- read.table(cheshire_fmd.cvs",header=TRUE, sep=",") > dat.<-read.table(''chesire_fmd.cvs'',header=TRUE,sep='',) Error: unexpected symbol in "dat.<-read.table(''chesire_fmd.cvs" >

I've been working on some basic library call optimizations, the SimplifyLibCalls pass (lib/Transforms/IPO/SimplifyLibCalls.cpp). Tonight I conjured up a list of the potential libcall simplifications that could be done. There's a lot of them. I could use some help if anyone wants to pitch in. The individual optimizations are self-contained and fairly straight forward to write. They range

Bugs item #15025, was opened at 2007-10-24 15:47 You can respond by visiting: http://rubyforge.org/tracker/?func=detail&atid=218&aid=15025&group_id=35 Category: Incorrect behavior Group: None Status: Open Resolution: None Priority: 3 Submitted By: Nobody (None) Assigned to: Nobody (None) Summary: TextCtrl method get_insertion_point() return is constrained to a 16 bit number Initial

Dear helpers, I am using the function "constrOptim" to estimate a model with ML with an inequality constraint using the option method='Nelder-Mead'. When I specify the option: hessian = TRUE I obtain the response: Error in f(theta, ...) : unused argument(s) (hessian = TRUE) I guess the function "constrOptim" does not allow this argument which, on the other hand, is

Hi, Does anybody have experience to solve an quadratic programming problem with quadratic constraints in R? It seems that the package "quadprog" only handles the quadratic programming with linear constraint. My probelm is to maximze x^T\Sigma_{xy} y, subject to x^Tx=1, y^T\Sigma_{yy} y=1, and sum(y)<t, or sum(y)=t, where x and y are the variable, and the Sigma's and t are

I'm curious to find out if there is an example of R code for optimization of two variable function, with contraints, using lagrange multiplier (using optim/nlm?). I have a problem that contains one discrete variable, but need a simple problem/example to start with. I haven't been able to find any examples and thought I should ask here before I plunged into writing a few miles of R code.

Hi, I'm trying to do some constrained non-linear optimisation, but my function does not have second order derivatives everywhere. To be a little more specific (the actual function is huge and horrible, so it would probably be better to just describe it) my model has four variables and I'm using optim to minimise an error term. My data is split into discreet days and I have two types of

Hello. I have searched the archives but have not found anything. I need to solve a constrained optimisation problem for a nonlinear function (“maximum entropy formalism”). Specifically, Optimise: -1*SUM(p_ilog(p_i)) for a vector p_i of probabilities, conditional on a series of constraints of the form: SUM(T_i*p_i)=k_i for given values of T_i and k_i (these are constraints on

Dear R Helpers, At the moment I'm working on the project to implement "optimal binning" function. It will be primarily used as a tool for logistic regression..... something very similar to http://www2.sas.com/proceedings/forum2008/153-2008.pdf* *but applied in diferent problem space...* *The problem might be descibed as finding optimal binning which will satisfy all of the rules