search for: weigths

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. -- View this message in context:

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 [[...

Hello. I don't understand a particular output of portfolio.optim (tseries). I have 4 assets and the portfolio.optim returns an asset with weight equals to zero. If I do a portfolio.optim with 3 assets, without the asset with weight equals to zero, it returns a completely different result. That's I would expected the same weights as the run with 4 assets. Below the code. Thanks in

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.

Hello, I know this must be a very simple problem, but I can'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,]

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

...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]]

Hello R-helpers: I have data like this: sample replicate height weight age A 1.00 12.0 0.64 6.00 A 2.00 12.2 0.38 6.00 A 3.00 12.4 0.49 6.00 B 1.00 12.7 0.65 4.00 B 2.00 12.8 0.78 5.00 C 1.00 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

...(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 Coeffi...

...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

Hi, I have a data.frame in wide format which I would like to reshape into a long format: example (nonsense) data: > dput(perus2) structure(list(id = c(30L, 38L, 21L, 12L, 22L, 28L, 31L, 44L, 8L, 47L, 23L, 20L, 41L, 42L, 29L, 50L, 5L, 33L, 4L, 17L, 11L, 1L, 18L, 6L, 9L, 32L, 16L, 14L, 39L, 48L, 37L, 43L, 25L, 27L, 35L, 40L, 45L, 49L, 2L, 34L, 10L, 15L, 24L, 26L, 46L, 7L, 13L, 3L, 19L, 36L),

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 Forschung...

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. Any...

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(),

Best R Help, I like to estimate a Multinomial Logit Model with 10 Classes. The problem is that the number of observations differs a lot over the 10 classes: Class | num. Observations A | 373 B | 631 C | 171 D | 700 E | 87 F | 249 G | 138 H | 133 I | 162 J | 407 Total: 3051 Where my data looks like: x1 x2 x3 x4 Class 1 1,02 2 1 A 2 7,2 1 5 B 3 4,2 1 4 H 1 4,1 1 8 F 2 2,4 3 7 D 1 1,2 0 4 J 2 0,9

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]]