similar to: Log transformed values and contrasts in LME

Hi There I have a lm object with 4 parameters and I want to test wether 2 parameters are equal using a Wald test (basically b1=b2 or b1-b2 =0). In the help file from R it says that under ANOVA the optional arguments " Terms" or "L" test whether a linear combination is equal to 0. I tried; >anova(m1, Terms = Beta1-Beta2=0) but I get the error: Object " Beta1"

Using R v. 1.7.0 on Windows 2000 I would like to plot the fitted values of a model as a function of a continuous covariate, augmented with data (e.g., augPred) grouping by combinations of fixed effects. I have not been able to use augPred effectively, and am wondering if it does not handle unbalanced data (3 out of 192 missing). I include below the model and an xyplot that almost does the

Dear All, I am trying to specify the following fixed effects model for lme: y ~ constant1 - beta1*(x - beta2) where y is the response, x is the independent variable, and the operators above are real arithmetic operations of addition, subtraction, and multiplication. I realize that this model is just a reparameterization of y=beta0+beta1*x, but I am using this parameterization because I am

The PDF file on the web, which is an appendix on nonlinear regression associated with the CAR book, is very nice. When I ran through the code presented there, I found something odd. The code does a certain model in 3 ways: Vanilla NLS (using numerical differentation), Analytical derivatives (where the user supplies the derivatives) and analytical derivatives (using automatic differentiation). The

Dear All I'm attempting to speed up my model building procedure, but need some help with the loops I've created...please bear with me through the explanation! My basic model call is something like: m0sulf.nlme<-nlme(conc~beta0*exp(-beta1*day)+beta2*exp(-beta3*day), data=m0sulf, fixed=(beta0+beta1+beta2+beta3~1),

Hi, I hope somebody can help me on how to use the hypergeometric function. I did read through the R documentation on hypergeometric but not really sure what it means. I would like to evaluate the hypergeometric function as follows: F((2*alpha+1)/2, (2*alpha+2)/2 , alpha+1/2, betasq/etasq). I'm not sure which function should be used- either phyper or qhyper or dhyper Where

Dear R-users, May I seek some suggestions from you. I have a long programme written in R with several 'for' loops inside. I just want to get them out by any elegant way (if there is!) to reduce the computational time of the main programme. For instance, is there any smart way for the following programme that will lessen time?

Full_Name: Charles J. Geyer Version: 1.3.1 OS: linux-gnu-i686 Submission from: (NULL) (134.84.86.22) ltsreg gives incomprehensible (to me) warnings A homework problem for nonparametrics ########## start example ########## library(bootstrap) data(cell) names(cell) attach(cell) library(lqs) plot(V1, V2) fred <- ltsreg(V2 ~ V1 + I(V1^2)) curve(predict(fred, data.frame(V1 = x)), add = TRUE)

Hi, I conduct a panel data estimation and obtain estimators for two of the coefficients beta1 and beta2. R tells me the mean and covariance of the distribution of (beta1, beta2). Now I would like to find the distribution of the quotient beta1/beta2, and one way to do it is to simulate via the joint distribution (beta1, beta2), where both beta1 and beta2 follow t distribution. How could we

Dear all, I have the following data set. V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 alpha beta 1 11 1 11 1 11 1 11 1 11 alpha beta1 2 12 2 12 2 12 2 12 2 12 alpha beta1 3 13 3 13 3 13 3 13 3 13 alpha beta1 4 14 4 14 4 14 4 14 4 14 alpha beta1 5 15 5 15 5 15 5 15 5

Hi, I am trying to use the nls() function to closely approximate a vector of values, colC and I'm running into trouble. I am not sure how if I am asking the program to do what I think its doing, because the same minimization in Excel's Solver does not run into problems. If anyone can tell me what is going wrong, and why I'm getting a singular convergence(7) error, please tell me. I

Hi, I am trying to covert a Winbugs code into R code. Here is the winbugs code model{# model’s likelihoodfor (i in 1:n){time[i] ~ dnorm( mu[i], tau ) # stochastic componenent# link and linear predictormu[i] <- beta0 + beta1 * cases[i] + beta2 * distance[i]}# prior distributionstau ~ dgamma( 0.01, 0.01 )beta0 ~ dnorm( 0.0, 1.0E-4)beta1 ~ dnorm( 0.0, 1.0E-4)beta2 ~ dnorm( 0.0, 1.0E-4)#

Dear All, May I seek your suggestion on a simple issue. I want to draw vertical lines at some positions in the following R plot. To be more specific, I wish to draw vertical lines at d=c(5.0,5.5,6) and they should go till p=c(0.12,0.60,0.20) . I haven't found any way out, though made several attempts. Please run the following commands first if you are interested in!

Hello, I would like to use the parfm package: https://cran.r-project.org/web/packages/parfm/parfm.pdfhttps://cran.r-project.org/web/packages/parfm/parfm.pdf in my work. This package fits parametric frailty models to survival data. To ensure I was using it properly, I started by running some small simulations to generate some survival data (without any random effects), and analyse the data using

Hello, I have a question concerning fitting a cox model with a random intercept, also known as a frailty model. I am using both the coxme package, and the frailty statement in coxph. Often 'shared' frailty models are implemented in practice, to group people who are from a cluster to account for homogeneity in outcomes for people from the same cluster. I am more interested in the classic

Hi All, I'm trying to run nls on the data from the study by Marske (Biochemical Oxygen Demand Interpretation Using Sum of Squares Surface. M.S. thesis, University of Wisconsin, Madison, 1967) and was reported in Bates and Watts (1988). Data is as follows, (stored as mydata) time bod 1 1 0.47 2 2 0.74 3 3 1.17 4 4 1.42 5 5 1.60 6 7 1.84 7 9 2.19 8 11 2.17 I then

Hello, I'm EDWIN, I create (make) GUI, with call many function but I don't know why when I call function I can't. if without function, Yes I can.. can you help me ? can you make this, become true with full code? Can you help me to create data.entry with interface LM - BETA1.HAT - BETA2.HAT SD.BETA1.HAT HAT SD.BETA2.HAT RLM - BETA1.HAT - BETA2.HAT SD.BETA1.HAT HAT SD.BETA2.HAT 2 10

Hello everybody, i already searched the archieves, but i still don't know what is wrong in my implementation, mybe anybody coud give me some advice ll1<-function(rho,theta,beta1,beta2,beta3,beta4,t,Szenariosw5,Testfaellew5,X1,X2) { n<-length(t) t<-cumsum(t) tn<-t[length(t)] Szenn<-Szenariosw5[length(Szenariosw5)]

Hello, My name is Edwin, I come from INDONESIA I have problem I creating function then I have many calculation like this xx<-function(){ a<-sd(....) b<-beta1.hat c<-beta2.hat data.entry(a,b,c) } then i have function too, almost same yy<-function(){ d<-sd(....) e<-beta1.hat f<-beta2.hat data.entry(d,e,f) } I have 6 function almost same then my problem is I can't

What's up fellows... I am a begginer in R and i am trying to find the parameters of one likelihood function, but when i otimize it, always appers a error or advertisement and the solve does not occur. The problem seems like that: "lMix<-function(pars,y){ beta1<-pars[1] beta2<-pars[2] beta3<-pars[3] beta4<-pars[4] beta5<-pars[5] alfa1<-pars[6]