similar to: arima function

ESTE SCRIPT FUNCIONA PERFECTAMENTE, LA PREGUNTA QUE HACÍA SE REFERÍA A QUE SI SERÍA POSIBLE QUE EN LA PROPIA TABLA CSV PUDIERAN ESTAR LOS NOMBRES DE LOS ANTIBIOTICOS Y QUE EL ANÁLISIS PCA NO LO RECHACE POR SER CUALITATIVO, QUE DE ALGUNA MANERA SE DIERA UNA INSTRUCCIÓN PARA EVITAR TENER QE HACER LO DE rownames manualmente setwd("D:/Public/Documents/R/FactoMineR/") table1 <-

Hi list, Update: originally i wanted to post a question, but in writing i thought of things that finally led me to the solution. This i wanted to share with the community in case it can help. Sorry if this is a FAQ, but I had no luck searching for it. I have a working Samba 2.2.5 installation on SuSE8.1. I have two users on a windows client called Torge (that's me) and Ga&ediaresis;lle

Este listado de antibióticos lo tengo en una tabla csv CON DETERMINADAS MEDICIONES CUANTITATIVAS POR AñOS Ampicillin Oxacillin Peniclina Ciprofloxacina Amikacina Gentamicina Kanamicina Ceftriaxone Ceftazidima Cefotaxima Cefazolina Cefuroxima Aztreonam Cloranfenicol Vancomicina Eritromicina Clindamicina Fosfomicina Amoxicilina Imipenem Azitromicina

Hi all R users I did a logistic regression with my binary variable Y (0/1) and 2 explanatory variables. Now I try to draw my nomogram with predictive value. I visited the help of R but I have problem to understand well the example. When I use glm fonction, I have a problem, thus I use lrm. My code is: modele<-lrm(Y~L+P,data=donnee) fun<- function(x) plogis(x-modele$coef[1]+modele$coef[2])

How can I insert cross-references to odfWeave generated figures in my source odf before the graphic has been created with odfWeave? Many thanks, Chris

Signed-off-by: Chen Baozi <baozich@gmail.com> --- extras/mini-os/include/spinlock.h | 2 +- extras/mini-os/include/x86/arch_spinlock.h | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/extras/mini-os/include/spinlock.h b/extras/mini-os/include/spinlock.h index 70cf20f..6604e3c 100644 --- a/extras/mini-os/include/spinlock.h +++

R-helpers, Beginner in R language, I have a problem to install a package (multiv) in R for Windows 98 (R-Gui) First I have got the multiv.zip file from the CRAN precompiled contributed packages for Windows and put this file in C:/Program Files/rw1022. in R-Gui I tried to install it as following > install.packages("C:/Program Files/rw1022/multiv.zip") I received the following

Hi list, question regarding the result of a DB query. I have database put Agora modele/IVR/AstreinteNagios/1 ${ASTR_State} i=1 and I read the DB with exten => IVR,n,Set(__PlayMe=${DB(${ASTRSVC}/IVR/${IVR}/${i})}) exten => IVR,n,NoOp(We read ${PlayMe}) Result: -- Executing [IVR at Automates:8] Set("SIP/laotseu-00000001", "__PlayMe=${ASTR_State}") in new stack

Salut alex. J''ai une question a propos de wx::statictext(wxruby2) est-il possible de mettre les accents pour la langue française?, car pour l''instant je ne peut pas mettre l''accentuation alors que ça marche bien avec "wxruby". merci Sebastien _______________________________________________ wxruby-users mailing list wxruby-users@rubyforge.org

Hello I need a tiny peace of help. (PPC Mac Os X 10.4.10; R 2.5.1) I have a data.frame with numeric and factor variables. I would like to convert same of the factors to ordered factors. I tried with: attach (table) as.ordered (V3) but this gives me only the V3 Vector as ordred back but in the data.frame (str(Table)) it is still not ordered. How can I do that? Thanks for your help. I am

Dear all, I'm looking for how can I estimate a linear model with ar(ma) errors : y(t)=a*X(t)+e(t) with P(B)e(t)=Q(B)u(t) where u is a white noise and P, Q are some polynomes. Could you help me ? Gr?gory Benmenzer

Dear R experts,   I'm running the following stationary bootstrap programming to find the parameters estimate of a linear model:     X<-runif(10,0,10) Y<-2+3*X a<-data.frame(X,Y) coef<-function(fit){   fit <- lm(Y~X,data=a)    return(coef(fit)) }  result<- tsboot(a,statistic=coef(fit),R = 10,n.sim = NROW(a),sim = "geom",orig.t = TRUE)   Unfortunately, I got this

Hi I'm using R(2.9.0) and gstat package under Windows to plot sample variograms. When I want to fit them, I don't have the possibility to choose Cauchy functions. Under Mathematica for example, we have it and it seems to be the best one to fit the variograms I have I tested the others functions, they can fit but I would,if possible, use the Cauchy one. If anybody knows something about

I cutover to a new server which uses Postfix & Dovecot to handle emails as opposed to Postfix & Courier in the old server. Below is the contents of my global sieve script and dovecot config info. The dovecot-deliver.log does show that the email is being delivered to INBOX.spam but it ends up in the INBOX instead. If I put the exact same rule in the user script, the emails are delivered

Hello all, I use arima to fit the model with fit <- arima(y, order = c(1,0,1), xreg = list.indep, include.mean = TRUE) and would like to use predict() to forecast: chn.forecast <- rep(0,times=num.record) chn.forecast[1] <- y[1] for (j in 2:num.record){ indep <- c(aa=chn.forecast[j-1], list.indep[j,2:num.indep]) # this is the newxreg in the

Hi, I am trying to understand exactly what xreg does in arima. The documentation for xreg says:"xreg Optionally, a vector or matrix of external regressors, which must have the same number of rows as x." What does this mean with regard to the action of xreg in arima? Apparently somehow xreg made the following two arima fit equivalent in R: arima(x, order=c(1,1,1), xreg=1:length(x)) is

When I run predict.Arima in my code, I get warnings like: Warning message: In cbind(intercept = rep(1, n), xreg) : number of rows of result is not a multiple of vector length (arg 1) I think this is because I'm not running predict.Arima in the same environment that I did the fit, so the data object used in the fit is no longer present. Looking at the predict.Arima source,

Dear R-help-archive.. I am trying to figure out how to make arima prediction when I have a process involving multivariate time series input, and one output time series (output is to be predicted) .. (thus strictly speaking its an ARMAX process). I know that the arima function of R was not designed to handle multivariate analysis (there is dse but it doesnt handle arma multivariate analysis, only

I am using arima to develop a time series regression model, I am using arima b/c I have autocorrelated errors. Several of my independent variables are categorical and I have coded them as factors . When I run ARIMA I don't get any warning or error message, but I do not seem to get estimates for all the levels of the factor. Can/how does ARIMA handle factors in xreg? here is some example

Thanks a lot to everybody that helped me out with this. Conclusions: (1) In order to edit arima in R: >fix(arima) or alternatively: >arima<-edit(arima) (2) This is not contained in the "Introduction to R" manual. (3) A "productive" fix of arima is attached (arma coefficients printed out and error catched so that it doesn't halt parent loops to search for