similar to: lars with weights do not match with lm output

Displaying 20 results from an estimated 2000 matches similar to: "lars with weights do not match with lm output"

2007 Nov 23
1
intercept in lars fit
I am trying to extract coefficients from lars fit and can't find how to get intercept. E.g. y = rnorm(10) x = matrix(runif(50),nrow=10) X = data.frame(y,x) fit1 = lars(as.matrix(X[,2:6]),as.matrix(X[,1])) fit2 = lm(y~.,data=X) Then, if I do: > predict(fit1,s=1,mode='fraction',type='coefficients')$coef X1 X2 X3 X4 X5 0.3447570
2011 Mar 25
2
A question on glmnet analysis
Hi, I am trying to do logistic regression for data of 104 patients, which have one outcome (yes or no) and 15 variables (9 categorical factors [yes or no] and 6 continuous variables). Number of yes outcome is 25. Twenty-five events and 15 variables mean events per variable is much less than 10. Therefore, I tried to analyze the data with penalized regression method. I would like please some of the
2004 May 07
0
rpart for CART with weights/priors
Hi, I have a technical question about rpart: according to Breiman et al. 1984, different costs for misclassification in CART can be modelled either by means of modifying the loss matrix or by means of using different prior probabilities for the classes, which again should have the same effect as using different weights for the response classes. What I tried was this: library(rpart)
2012 May 28
0
GLMNET AUC vs. MSE
Hello - I am using glmnet to generate a model for multiple cohorts i. For each i, I run 5 separate models, each with a different x variable. I want to compare the fit statistic for each i and x combination. When I use auc, the output is in some cases is < .5 (.49). In addition, if I compare mean MSE (with upper and lower bounds) ... there is no difference across my various x variables, but
2013 Mar 19
1
Lars package
Hi,   I'm using lars package to run some regression analysis and my doubt now is how can I predict my model to another dataset? Let me explain a little better: I have a dataset from which I withhold some data. With the data that wasn't withheld, I create the model. Now, what I'm not being able to do is apply the model back to the data that I withheld. Any suggestions?   Here it goes
2009 Feb 12
0
Comparing slopes in two linear models
Hi everyone, I have a data frame (d), wich has the results of mosquitoes trapping in three different places. I suspect that one of these places (Local=='Palm') is biased by low numbers and will yield slower slopes in the variance-mean regression over the areas. I wonder if these slopes are diferents. I've looked trought the support list for methods for comparing slopes and found the
2011 May 01
1
Different results of coefficients by packages penalized and glmnet
Dear R users: Recently, I learn to use penalized logistic regression. Two packages (penalized and glmnet) have the function of lasso. So I write these code. However, I got different results of coef. Can someone kindly explain. # lasso using penalized library(penalized) pena.fit2<-penalized(HRLNM,penalized=~CN+NoSus,lambda1=1,model="logistic",standardize=TRUE) pena.fit2
2020 Sep 30
0
2 KM curves on the same plot
Hi John, Brilliant solution and the best sort - when you finally solve your problem by yourself. Jim On Thu, Oct 1, 2020 at 2:52 AM array chip <arrayprofile at yahoo.com> wrote: > > Hi Jim, > > I found out why clip() does not work with lines(survfit.object)! > > If you look at code of function survival:::lines.survfit, in th middle of the code: > > do.clip <-
2017 Dec 20
0
Nonlinear regression
Should I repost the question with reply-all? On Tue, Dec 19, 2017 at 6:13 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > You also need to reply-all so the mailing list stays in the loop. > -- > Sent from my phone. Please excuse my brevity. > > On December 19, 2017 4:00:29 PM PST, Timothy Axberg < > axbergtimothy at gmail.com> wrote: > >Sorry about
2008 Jan 05
1
Likelihood ratio test for proportional odds logistic regression
Hi, I want to do a global likelihood ratio test for the proportional odds logistic regression model and am unsure how to go about it. I am using the polr() function in library(MASS). 1. Is the p-value from the likelihood ratio test obtained by anova(fit1,fit2), where fit1 is the polr model with only the intercept and fit2 is the full polr model (refer to example below)? So in the case of the
2017 Dec 20
1
Nonlinear regression
You also need to reply-all so the mailing list stays in the loop. -- Sent from my phone. Please excuse my brevity. On December 19, 2017 4:00:29 PM PST, Timothy Axberg <axbergtimothy at gmail.com> wrote: >Sorry about that. Here is the code typed directly on the email. > >qe = (Qmax * Kl * ce) / (1 + Kl * ce) > >##The data >ce <- c(15.17, 42.15, 69.12, 237.7, 419.77)
2011 Jun 29
0
Problem: Update of glm-object cannot find where the data object is located
Hi everybody, I want to ask your help to explain what is going on with my following code: > mydata <- data.frame(y=rbinom(100, 1, 0.5), x1=rnorm(100), x2=rnorm(100)) > glm.fit.method <- function(model,data,...){glm(formula=model,data=data,family="binomial",. ..)} > fit1 <- glm(y ~ x1 + x2, data=mydata, family=binomial()) > update(fit1, .~1) Call: glm(formula =
2009 Jul 28
2
A hiccup when using anova on gam() fits.
I stumbled across a mild glitch when trying to compare the result of gam() fitting with the result of lm() fitting. The following code demonstrates the problem: library(gam) x <- rep(1:10,10) set.seed(42) y <- rnorm(100) fit1 <- lm(y~x) fit2 <- gam(y~lo(x)) fit3 <- lm(y~factor(x)) print(anova(fit1,fit2)) # No worries. print(anova(fit1,fit3)) # Likewise. print(anova(fit2,fit3)) #
2004 Jun 11
1
comparing regression slopes
Dear List, I used rlm to calculate two regression models for two data sets (rlm due to two outlying values in one of the data sets). Now I want to compare the two regression slopes. I came across some R-code of Spencer Graves in reply to a similar problem: http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html The code was: > df1 <- data.frame(x=1:10, y=1:10+rnorm(10))
2010 Mar 17
1
accessing info in object slots from listed objects using loops
Hey, I have stacked a couple of garchFit objects in a list with names $fit1, $fit2, ..., $fiti assigning objects names using a loop, i.e. after running the loop modelStack = list($fit1, $fit2,...,$fiti). Thus the following apply; a = modelStack$fit2, then a is the second garchFit object of formal class 'fGarch' with 11 slots, @call, @formula... etc. I then want to extract information in
2004 Dec 21
0
Fwd: problems with limma
On Wed, December 22, 2004 12:11 am, r.ghezzo at staff.mcgill.ca said: > ----- Forwarded message from r.ghezzo at staff.mcgill.ca ----- > Date: Mon, 20 Dec 2004 15:45:11 -0500 > From: r.ghezzo at staff.mcgill.ca > Reply-To: r.ghezzo at staff.mcgill.ca > Subject: [R] problems with limma > To: r-help at stat.math.ethz.ch > > I try to send this message To Gordon
2010 Sep 21
1
package gbm, predict.gbm with offset
Dear all, the help file for predict.gbm states that "The predictions from gbm do not include the offset term. The user may add the value of the offset to the predicted value if desired." I am just not sure how exactly, especially for a Poisson model, where I believe the offset is multiplicative ? For example: library(MASS) fit1 <- glm(Claims ~ District + Group + Age +
2013 Apr 22
0
Copula fitMdvc:
Hello, I am trying to do a fit a loglikelihood function with Multivariate distribution via copulas with fitMdvc. The problem is that it doesn't recognize that my beta is a vector of km parameter and when I try to run it it say that the length of my initial values is not the same as the parameter. Can somebody guide me where my mistake is. Thanks, Elisa. #################################
2011 Oct 06
1
anova.rq {quantreg) - Why do different level of nesting changes the P values?!
Hello dear R help members. I am trying to understand the anova.rq, and I am finding something which I can not explain (is it a bug?!): The example is for when we have 3 nested models. I run the anova once on the two models, and again on the three models. I expect that the p.value for the comparison of model 1 and model 2 would remain the same, whether or not I add a third model to be compared
2003 Dec 30
1
odd results from polr vs wilcoxon test
Dear R helpers, I would like to ask why polr occasionally generates results that look very odd. I have been trying to compare the power of proportional odds logistic regression with the Wilcoxon test. I generated random samples, applied both tests and extracted and compared the p-values, thus:- library(MASS) c1=rep(NA,100); c2=c1 for (run in 1:100) { dat=c(rbinom(20,12,0.65),rbinom(20,12,0.35))