similar to: Plotting a Quadratic...

Hi all, When running a randomForest run using the following command: forestplas=randomForest(Prev~.,data=plas,ntree=200000) print(forestplas) I get the following result: Call: randomForest(formula = Prev ~ ., data = plas, ntree = 2e+05, importance = TRUE) Type of random forest: regression Number of trees: 2e+05 No. of variables tried at each split: 5

Hi all (and Andy!), When running a randomForest run in R, I get the last part of an output (with do.trace=T) that looks like this: 1993 | 0.04606 130.43 | 1994 | 0.04605 130.40 | 1995 | 0.04605 130.43 | 1996 | 0.04605 130.43 | 1997 | 0.04606 130.44 | 1998 | 0.04607 130.47 | 1999 | 0.04606 130.46 | 2000 | 0.04605 130.42 | With the first column representing the

Dear Experts, My customer is migrating to Solaris 10 from Solaris 8 and have asked me to determine if: With Dtrace, is the user limited to probing only processes they own? The customer has a general security requirement to control user access via management of privileges. Currently, on Solaris 8, LDAP is strongly while RBAC is weakly applied. This will likely change in the Solaris 10 production

Hi all, I am using Puppet to execute an Expect script (http://expect.sourceforge.net) on a client. The Puppet recipe, test.pp, is: exec { ''/root/test.exp'': command => ''/root/test.exp'', logoutput => true } The recipe runs correctly when run using ''puppet --debug --verbose test.pp'': debug: /Stage[main]//Exec[/root/test.exp]:

Greetings all, I am running winbindd running quite nicely on a suse 7.3 system. (samba 2.2.2) One issue (until now:-): I discovered that new created files are created with the gid associated with the primary group of the particular user which is fine and desired. However: 'getent passwd' lists all users with the gid set to 10000 which happens to be mapped to the 'Domain users'

Dear Sirs, out asterisk server has multiple network cards. I want some outgoing calls (from several extensions) to use one IP address, and others to go through another address. is there a way to achive that using asterisk ? Cheers, Kate -------------- next part -------------- An HTML attachment was scrubbed... URL:

Dear Sirs, we ... 1) buy minutes from other providers 2) sell minutes to out clients some calls terminate to our equipment, others - to h323 proxies. we want calls to be routed according to costs (a route is chosen from many by lowest cost). at the end of it, we'd like to bill our clients and see how much have we earned (money we receive from client on one side, money we pay to proxies on

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

Hi all, Could anybody please point me to the solver function in R on QCQP? The quadprog package seems to be only able to handle the linear constraints... Thank you! [[alternative HTML version deleted]]

Hi there, Is it basically possible to solve a non-convex quadratic programming with optimal solution by any way? What could be the way? How can be this problem dealt with? Could you guide me to some references please? I thank you very much for eny help. Tobi --------------------------------- Boardwalk for $500? In 2007? Ha! ---------------------------------

Dear R Users , As a beginner in QP, I'm trying to solve a Support Vector Machine problem by a QP. In particulare I am using the quadprog package. My questions are here: 1- In the document for the package (The quadprog Package), the inequality constraint is mentioned with >= , however in a standard QP, this usaully is written with <= . This constraint should be multiplied by a

Hi listers, Does anybody knows if the function qda for quadratic discriminant analysis provides the coefficients of quadratic discriminants... Well, I find out that for the linear discriminant analysis lda, the fonction provides the coefficients... Thanks in advance, Marcio -- View this message in context: http://www.nabble.com/Quadratic-Discriminant-Analysis-%28qda%29-tp22747647p22747647.html

Hi, ***** First, let me apologize for the disclaimer that accompanies my mail. I don't add it and I can't take it out. **** Is there any implementation of Linear/Quadratic programming in R? Thanks. Mustaque This message contains confidential information and is intended only for the individual named. If you are not the named addressee you should not disseminate, distribute or copy

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I was thinking about my solve.qp problem on my way home tonight and I think I can fix it by making Dmat the identity matrix. I'll check this weekend to make sure but my thinking is that doing this will make all the "variances" the same so that they shouldn't come into play during the evaluation of the objective function. Thanks though for any confirmation of this or other

Hello, I am estimating the following model: so2.lme<-lme(so2~1+I(alcadakm^2)+dia,data=subjectes2,na.action=na.omit) And when I try to plot the random effects of the quadratic term with respect to a covariate (mam) I get an error: > so2.lmeRE<-ranef(so2.lme,augFrame=T) > plot(so2.lmeRE,form=I(alcadakm^2)~mam) Error in plot.ranef.lme(so2.lmeRE, form = I(alcadakm^2) ~ mam ) : Only

hi, what code in R would I use to solve the problem below? An apartment complex has 250 apartments to rent.If they rent x apartments then their monthly profit is given by: p(x)= -8^x^2 + 3200x -80000 Thanks. [[alternative HTML version deleted]]

Dear R Helpers, I need to find the root of following equation. 0.0016^2 = (0.001*x)^2 + (0.002 * (1-x))^2 + 2 * 0.7 *0.001*0.002 * x * (1-x). I had tried using "animation " package as follows. # My Code library(animation) ani.options(nmax = 500) solu = newton.method(function(x) 0.0016^2 - 0.001^2*x^2 - 0.002^2*(1-x)^2 - 2*0.7*0.001*0.002*x*(1-x), 1, c(-1,1)) solu$root #

Hello. I'm trying to solve a quadratic programming problem of the form min ||Hx - y||^2 s.t. x >= 0 and x <= t using solve.QP in the quadprog package but I'm having problems with Dmat not being positive definite, which is kinda okay since I expect it to be numerically semi-definite in most cases. As far as I'm aware the problem arises because the Goldfarb and Idnani method first

Hi All, I am a newcomer to S/R. Could you please let me know how to model quadratic trends for the mul/sigl link functions when fitting non-stationary GEV distributions using the ismev package? Thanks Best Regards, Mohammad Ashrafuz Zaman PhD Candidate School of Engineering Building XC, Room 1.02 (Kingswood Campus) University of Western Sydney Locked Bag 1797, Penrith South DC NSW 1797