search for: weigth

Here is my dataframe with 1000 rows: employee_id weigth p-value 100 150 101 200 102 300 103 180 ..... My question: how can I calculate the p-value in R for each employee? the distribution of the weigth will be established from the above 1000 samples. -...

Potential bug: I mistyped weights in the call ('weigths') and it did not produce any error= message. The coefs were exactly the same like without weights, so I was su= spicious and when weights(nls1) gave NULL, I saw my typo. Usually the function will say "Unused arguments", which shows you the error= , but not nls. Regards Stephen [...

...length(spmib)-1)])) x <- cbind(f.mi.rets, eng.mi.rets, tis.mi.rets, spmib.rets) res <- portfolio.optim(x); res$pw x2 <- cbind(f.mi.rets, eng.mi.rets, spmib.rets) res <- portfolio.optim(x2); res$pw -- View this message in context: http://www.nabble.com/portfolio.optim-and-assets-with-weigth-equals-to-zero...-tp19289567p19289567.html Sent from the R help mailing list archive at Nabble.com.

Hi everyone, I admit I am a bit of an R novice, and I was hoping someone could help me with this error message: Warning message: In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : extra arguments weigths are just disregarded. My equation is: lm( Y ~ X1 + X2 + X3, weigths = seq(0.1, 1, by = 0.1)) -- View this message in context: http://r.789695.n4.nabble.com/Weighted-least-squares-tp4650292.html Sent from the R help mailing list archive at Nabble.com.

...an't work it out from the documentation that is available. I've got a list of data I would like to plot (the weights of a single neuron that was trained using the neural package). The problem I'm encountering is that this set of weights, are in the form of a list. > network$weigth[1] [[1]] [,1] [1,] -0.04687623 [2,] -0.54087443 [3,] -1.68130221 [4,] -0.82295266 [5,] 1.60848361 [6,] 1.55903277 [7,] 0.29005900 [8,] 1.24387657 [9,] -0.05129092 [10,] -1.22469042 [11,] -2.64470326 [12,] 0.10517494 [13,] 1.87561741 [14,] 1.93962447 [15,] 0.99212323 [16,] 0.4...

Dear R-friends, I have to simple questions. First I would like to exclude some columns from a dataframe and after I need select rows that satisfy some conditions. My data frame looks like Region Species Bodysize Weigth Age Africa Sp1 10.2 20 2 Africa Sp2 12.2 12 2 Africa Sp3 15.3 18 3 Africa Sp4 11.5 40 4 Brazil Sp1 10.2 40 3 Brazil Sp2 22.2 32 2 Brazil Sp3 12.3 28 3 Brazil Sp4 21.5 30 5 And I need for example only "columns" Bodysize Weigth and Age when Region=="Brazil...

...mething like c(10+0.10*10,9+0.089*9,8+0.075*8.....,1+0.05*1) c(10-0.10*10,9-0.09*9,8-0.075*8.....,1-0.05*1) What I?m looking for is a function tu calculate de "values, weights" so that including the 10% and 5% and the nunmber of decreasing values, in this case n=10, calculates de smotth weigths. I don?t know if I have expalined well so thar finally putting initial value final and periods I can find a matrix like g(0.1,0.89,0.79,0.075,...,0.05) Exists something like that? [[alternative HTML version deleted]]

....00 11.9 0.45 6.00 C 2.00 11.84 0.44 2.00 C 3.00 11.43 0.32 3.00 C 4.00 10.24 0.84 4.00 D 1.00 14.2 0.54 2.00 D 2.00 15.67 0.67 7.00 D 3.00 15.11 0.81 7.00 Now, how can I calculate the mean for each condition (heigth, weigth, age) in each sample, considering the samples have different number of replicates? The final matrix should look like: sample height weight age A 12.20 0.50 6.00 B 12.75 0.72 4.50 C 11.35 0.51 3.75 D 14.99 0.67 5.33 This is a simplified...

...(dispersions), there should be corresponding non-vanishing ``errors'' associated to the best fit coefficients, right? When I try: > fit_mod <- lm(y~x,weights=1/error^2) I get Warning message: In lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : extra arguments weigths are just disregarded. Keeping on, despite the warning message, which I did not quite understand, when I type: > summary(fit_mod) I get Call: lm(formula = y ~ x, weigths = 1/error^2) Residuals: 1 2 3 4 -5.067e-17 8.445e-17 -1.689e-17 -1.689e-17 Coeff...

...ng a weighted, stratified, clustered survey data set with approximately 1 million observations and 50 variables. I am new to R (I'm a Stata user), and so far couldn't find any documentation on how to handle survey data. In other words, is there a specific package to handle a combination of weigths, clusters and strata. I am also struggling to handle such a large data set. Any suggestions and/or references regarding these two issues would be greatly appreciated. Rick Ricardo Pietrobon, MD Assistant Professor of Surgery Duke University Medical Center -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

Hi all, Again I have searched the net and so on, without finding an answer to this surely simple problem. A short bit of code would be appreciated. I have a object named `data' with the following column headings. Date, maxitemp, minitemp, admissions, d.o.w. Where d.o.w. is day of the week, written "Sun" "Mon" etc. I just need to scale the Monday admissions by

...eight1", "height2", "height3"), + c("weight1", "weight2", "weight3"), + c("bmi1", "bmi2", "bmi3")), + v.names=c("heigth","weigth", "bmi"), + timevar = "time", + times = factor(c(1, 2, 3)), + idvar = c("id", "sp"), + direction = "long") Error in `row.names<-.data.frame`(`*tmp*`, value = c("30.0.1&quot...

Hello! When I know the vector of the variance of the disturbances (i.e. the structure of heteroskedasticity), say Var(u_{i})=v_{i}, what is the weights I should use as argument to lm(): M <- lm(y~x,weigths=1/v) or M <- lm(y~x,weights=1/(v^0.5)) ??? In the help pages I did not find a clear answer to this question, so please could someone help me! Thanks, Wolfgang Koller ---------------------------------------------------------- Wolfgang Koller, koller2 at fgr.wu-wien.ac.at Forschun...

Dear list, how can I compute the inverse of the X'WX matrix ("inverse of the weighted sum of squares and crossproducts matrix") from an object of class "lm" from a weigthed linear regression? Thanks, Sven

Hi, I try to make a model using lmer, but the weigths is not accept. m1<-lmer(ocup/total~tempo+(tempo|estacao),family=binomial,weights=total) Erro em lmer(ocup/total ~ tempo + (tempo | estacao), family = binomial, : object `weights' of incorrect type I dont understand why this error, with glm this work. the total object is a vector. An...

Dear R users, I am currently analyzing a dataset using lme(). The model I use has the following structure: model<-lme(response~Covariate+TreatmentA+TreatmentB,random=~1|Block/Plot,method="ML") When I plot the residuals against the fitted values, I see a clear positive trend (meaning that the variance increases with the mean). I tried to solve this issue using weights=varPower(),

...Classes with a large number of observations (A,B,D,J), the other classes are never predicted by the model. I thougth that the option "weights" of the multinom function could be usefull but I am not sure how to use this in the above case. Is there someone with experience regarding such a weigthing approach in multinom? If someone could help me with suggestions it would be great! Nice day, Arne

Hello, I've been working with "nnet" and now I'd like to use the weigths, from the fitted model, to iterpret some of variables impornatce. I used the following command: mts <- nnet(y=Y,x=X,size =4, rang = 0.1, decay = 5e-4, maxit = 5000,linout=TRUE) X is (m x n) Y is (m x 1) And then I get the coeficients by: Wts<-coef(mts) b->h1 i1->h1...

...10,9+0.089*9,8+0.075*8.....,1+0.05*1) > c(10-0.10*10,9-0.09*9,8-0.075*8.....,1-0.05*1) > > What I?m looking for is a function tu calculate de "values, weights" so > that including the 10% and 5% and the nunmber of decreasing values, in this > case n=10, calculates de smotth weigths. > > I don?t know if I have expalined well so thar finally putting initial value > final and periods I can find a matrix like > > g(0.1,0.89,0.79,0.075,...,0.05) > > Exists something like that? > > [[alternative HTML version deleted]] > > __________________...

...10,9+0.089*9,8+0.075*8.....,1+0.05*1) > c(10-0.10*10,9-0.09*9,8-0.075*8.....,1-0.05*1) > > What I?m looking for is a function tu calculate de "values, weights" so > that including the 10% and 5% and the nunmber of decreasing values, in this > case n=10, calculates de smotth weigths. > > I don?t know if I have expalined well so thar finally putting initial > value final and periods I can find a matrix like > > g(0.1,0.89,0.79,0.075,...,0.05) > > Exists something like that? > > [[alternative HTML version deleted]]