search for: tstdf

How can I see more of the structure than displayed by 'str'? Consider the following: tstDF <- data.frame(a=1, row.names='b') > str(tstDF) 'data.frame': 1 obs. of 1 variable: $ a: num 1 The object 'tstDF' has row.names, but I have to suspect they are there -- AND know a function like 'row.names' or 'dimnames' -- to see them...

Dear R users, I have a question on using weighted.mean() while aggregating a data frame. I have a data frame with columns Sub, Length and Slope: > x[1:5,] Sub Length Slope 1 2 351.547 0.0025284969 2 2 343.738 0.0025859390 3 1 696.659 0.0015948968 4 2 5442.338 0.0026132544 5 1 209.483 0.0005304225 and I would like to calculate the weighted.mean of Slope, using Length

I am encountering an error with plot.lm: > tstdf <- data.frame( y=c(1.01,1.98,3.02,3.99),x=c(1,2,3,4)) > plot(lm(I(y) ~ x, data=tstdf)) Hit <Return> to see next plot: Hit <Return> to see next plot: Error in object$coefficients : $ operator is invalid for atomic vectors Obviously I don't need the I() in this example, but I h...

How can I extract K (number of parameters) from an AIC calculation, both to report K itself and to calculate AICc? I'm aware of the conversion from AIC -> AICc, where AICc = AIC + 2K(K+1)/(n-K-1), but not sure of how K is calculated or how to extract that value from either an AIC or logLik calculation. This is probably more of a basic statistics question than an R question, but I thank

What are the functions available for use with “aggregate”? Where can a reference to them be found? --------------------------------- [[alternative HTML version deleted]]

Hi, To obtain estimates for some missing values in my data I fitted a linear regression and then used the command fitted(model) to get the fitted values from the model, but R doesn't return any values for the NA's. I can calculate the fitted values from the estimates obtained from the summary of model, but that's not very handy. Is there a way to include the missing values in the

Hi, Does anyone know how to compute the confidence prediction intervals for a nonlinear least squares models (nls)? I was trying to use the function 'predict' as I usually do for other models fitting (glm, lm, gams...), but it seems that se.fit, and interval computation is not implemented for the nls... Cheers Enrique ~~~~~~~~~~~~~~~~~~~~~~~~~~~ Fisheries Research Services, Marine

Hi All I have been fitting regression models and would now like to produce some contour & image plots from the predictors. Is there an easy way to do this? My current (newbie) experience with R would suggest there is but that it's not always easy to find it! f3 <- lm( fc ~ poly( speed, 2 ) + poly( torque, 2 ) + poly( sonl, 2 ) + poly( p_rail, 2 ) + poly( pil_sep, 2 ) + poly( maf, 2

Moved from r-help: On Thu, 14 Aug 2003 09:08:26 -0700, Spencer Graves <spencer.graves@pdf.com> wrote : >p.s. The following command in S-Plus 6.1 seems to work fine but >produces an error in R 1.7.1: > >nls(y~a, data=tstDf, start=list(a=1)) >Error in nlsModel(formula, mf, start) : singular gradient matrix at >initial parameter estimates This looks like a bug in numericDeriv, which finds a derivative of 0 rather than 1 for da/da. I've cc'd the author. Duncan