search for: coeficient

...orm(n = 6, mean = 10) dat <- data.frame(vals = c(ctrl, ttd), group = c(rep("ctrl", 6), rep("ttd", 6)), ind = factor(rep(1:6, 2))) fit <- lm(vals ~ ind + group, data = dat) model.matrix(~ ind + group, data = dat) I am puzzled on how the coeficients are calculated. For example, according to the model matrix, I thought the intercept would be individual 1 control. But that is clearly not the case. For the last coeficient, I understand it as the mean of all differences between treated vs control at each individual. I would greatly appreciate if...

I am trying to write a function that will run a linear model and plot the regression coeficients with their corresponding means. I am having two problems. I can get the plot with the function below, but I am having trouble labeling the points. function(y,x1,x2,x3,x4){ outlm<-lm(y~x1+x2+x3+x4) imp<-as.data.frame(outlm$coef[-1]) meanvec<-c(mean(x1),mean(x2),mean(x3),mean(x4)) out&...

Hi! I am trying to calculate HPD for the coeficients of regression models fitted with lm or lmrob in R, pretty much in the same way that can be accomplished by the association of mcmcsamp and HPDinterval functions for multilevel models fitted with lmer. Can anyone point me in the right direction on which packages/how to implement this? Thanks for y...

Hi, What I'm trying to achieve is very fast algorithm for fitting logistic regression model. I have to estimate regression coeficients using about 10k observations. Once I have coefficients estimated, new 100 rows of data becomes available.... Now I need to reestimate coeficients using 100 newly arrived observations and removing 100 oldest observations. So, my question is would it be possible to somehow reuse pre iusly calculate...

I am still fairly new to R and have a fairly rudimentary question. I am trying to name a vector of coefficients retrieved from a multilevel model using the coef function. I guess the default name is "Intercept" and I cannot figure out how to rename it. I have tried the using the code below to name the column of coefficients ind.y derived from an lme model. Unfortunately, the

Dear listers, I can't find the variance or se of the coefficients in a multilevel model using lme. I want to calculate a Chi square test statistics for the variability of the coefficients across levels. I have a simple 2-level problem, where I want to check weather a certain covariate varies across level 2 units. Pinheiro Bates suggest just looking at the intervals or doing a rather

Hi, is there an easy way to get the calculated weights in a regression equation? for e.g. if my model has 2 variables 1 and 2 with coefficient .05 and .6 how can I get the computed values for a test dataset for each coefficient? data var1,var2 10,100 so I want to get .5, 60 back in a vector. This is a one row example but I would want to get a matrix of multiplied out coefficients

Dear list, i'm trying to test if a linear combination of coefficients of glm is equal to 0. For example : class 'cl' has 3 levels (1,2,3) and 'y' is a response variable. We want to test H0: mu1 + mu2 - mu3 =0 where mu1,mu2, and mu3 are the means for each level. for me, the question is how to get the covariance matrix of the estimated parameters from glm. but perhaps there

...is actually normalized too something, because it's discrete integral is not well above the SS amplitude of the signal it computed the periodogram for. In other words, the powers are not in units of around 4,000, which the peak would be if the units were merely the modulus squared of the Fourier coeficients of the data I presented. Alas, the modulus squared of the Fourier coeficients IS the TWO SIDED unnormalized periodogram, ranging from [-fc, fc] | fc=nyquist critical frequency. The definition of the ONE SIDED periodogram IS the modulus squared of the Fourier coeficients ranging over [0, fc], but s...

Hi! I am using the fft() function the base package to transform some 1d signal. If I use this standar fucntion I get a very huge first fourier coeficient. I think this dues to the handling of the borders of the signal. Usually in fft especially in image processing the signal is simulated to be continuous by adding the signal several times periodically. My question is, is there some function implemented in R handling this or do I have to combine my d...

Hi, I have been dabbling with str() to extract values from outputs such as lmer etc and have found it very helpful sometimes. but only seem to manage to extract the values when the output is one simple table, any more complicated and I'm stumped :-( take this example of the extracted coeficients from a lmer analysis... using str(coef(lmer(resp3~b$age+b$size+b$pcfat+(1|sex), data=b))) yields Formal class 'lmer.coef' [package "Matrix"] with 3 slots ..@ .Data :List of 1 .. ..$ :`data.frame': 2 obs. of 4 variables: .. .. ..$ (Intercept): num [1:2] 1.07 1.13 .....

Hello! I would like to use constrain to sum coeficients of a factor to 0 instead of classical corner contraint i.e. I would like to fit a model like lm(y ~ 1 + effectA + effectB) and say get parameters intercept effectA_1 effectA_2 effectB_1 effectB_2 effectB_3 where effectA_1 represents deviation of level A_1 from intercept and sum(effectA_1, eff...

hello, i am a bit of a statistical neophyte and currently trying to make some sense of confidence intervals for correlation coefficients. i am using the cor.test() function. the documentation is quite terse and i am having trouble tieing up the output from this function with stuff that i have read in the literature. so, for example, i make two sequences and calculate the correlation coefficient:

Hi I'm using boot package for some analysis on linear regression coeficients. My problem is that I can not compute bca intervals, I get an error message > bca.ci(blm8901,index=1) Error in if (!all(rk > 1 & rk < R)) warning("Extreme Order Statistics used as Endpoints") : missing value where logical needed The problem is the empinf.reg funct...

Hi everyone, I've been trying to find a function that outputs the Pearson and/or Spearman correlation coefficients for several variables with the associated statistics in one single table/matrix. For what I've been able to understand the Stats package is only able to compute these coeficients/statistics only in defined pairs. This becomes time consuming when we want to determine these measures with, say, 10 variables or more. Does anyone knows a solution to this? Kind regards, Nuno

Hi, I noticed that when I was conducting some calculation involving finding correlation coeficients, R stopped abnormally. So I did some research, and find out that 0/0 was the culprit. For sure 0/0 is not a valid expression, but R should give a warning, an error msg or NaN instead of segmentation fault. I am using R 2.1.0 under Gentoo Linux. My GCC version is 3.3.5. Xing

I like what smooth.spline does but I am unclear on the output. I can see from the documentation that there are fit.coef but I am unclear what those coeficients are applied to.With spline I understand the "noraml" coefficients applied to a cubic polynomial. But these coefficients I am not sure how to interpret. If I had a description of the algorithm maybe I could figure it out but as it is I have this question. Any help? Kevin

..... but I get the following error Error in replace.substring.wild(s, old, new, test = test, front = front, : does not handle > 1 * in old I think that this might have something to do with the fact that I fit the model with GLS. (?) I am looking for a simple way to get a table of estimated coeficients without hand-making a table in a text editor for inclusion within a LATEX document. Thanks! -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341

Hi all. This is my first post in this forum. Finally I find a forum in the web about R, although is not in my language. Now I'm working with Bootstrap CI. I'd like to know how I can calculate a Bootstrap CI for any statistic, in particular, for Kurtosis Coeficient. I have done the following code lines: > library(boot) > x=rnorm(20) > kurtosis=function(x) (mean((x-mean(x))^4))/(sd(x)^4) > z <- numeric(10000) > for(i in 1:10000) > z[i]=kurtosis(sample(x, replace=TRUE)) > boot.ci(z, conf = 0.95,type = c("norm","basic&quot...

Hi everyone, I have been using REML to derive intercepts and coeficients for each individual in a growth study. So the code is m2 <- lmer(change.wt ~ newwt+(newwt|id), data = grow) Calling coef(model.lmer) gives a matrix with this information which is what I want. However, as a test I looked at each individual on its own and used a simple linear regression to obtai...