similar to: weird! QDA does not depend on priors?

Dear Bert, Thank you so much for your kind and valuable feedback. I tried finding the starting values using the approach you mentioned, then did the following to fit the nonlinear regression model: nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 =

Dear All, I've been using already for a year glm.nb() from the MASS package. But today, R gave me an error message when estimating one of my usual models: > depEsf.nb <- glm.nb(depE ~ manuf00E + corps00E + lngdp00E + lngdp00sqE + > lnpop00E + indshE + scishE + mechshE + elecshE + chemshE + drugshE + > urban_dummyE + aggl_dummyE + + eE1 + eE2 + eE3 + eE4 + eE5 + eE6 + eE7 +

I think that there is a bug in the as.POSIXct function on Windows. Here is what I get on Win2000, Pentium III machine in R 1.8.1. > dd1 <- ISOdatetime(2003, 10, 26, 0, 59, 59) > dd2 <- ISOdatetime(2003, 10, 26, 1, 0, 0) > dd2 - dd1 Time difference of 1.000278 hours Now, the 26th of October was the day that change to the standard time occurred, so I suspect that this has

Hi, What does this mean when I have something like: > qda.boot <- boot(train, qda.bootstrap, R = 500) Error in qda.default(structure(data.matrix(x), class = "matrix"), ...) : Rank deficiency in group M with my qda.bootstrap() looks something like: > qda.bootstrap <- function(data, index) { + boot.qda <- qda(x = data[index, 2:9], group = data[index, 1]) + qda.pred

z <- qda(train, cl) save(z, file = "qda.dat") load("qda.dat") predict(qda.dat, test)$class I'm trying to save z where z <-qda(train, cl) and load z for later use in predict(z, test)$class. I think I successfully saved z by save(z, file = "qda.dat") but when I tried to load by load("qda.dat") and call predict(qda.dat, test)$class, it gives me error

Hello, I am Souradeep Chattopadhyay and I am a graduate student at Iowa State University Department of Statistics. Can anyone please explain the mathematical formulation behind the scaling matrix returned by the qda function in MASS package. I want to understand how this scaling matrix is derived from the inputs given to the qda function. Example Code The following example is using

Dear R user, I'm using qda (quadratic discriminant analysis) function (package MASS) to classify 58 explanatory variables (numeric type with different ranges) using a grouping variable (factor 2 levels "0" "1"). I'm using the qda method for class 'data.frame' (in this way I don't need to specify a formula). Using the function:

You need to learn how to access code for nonexported methods. See ? "::" > methods(qda) [1] qda.data.frame* qda.default* qda.formula* qda.matrix* see '?methods' for accessing help and source code Shows you that the methods are not exported from the namespace. Hence you need to use the triple colon operator to see their code: > MASS:::qda Once you have the code, I

I guess the question that is being asked here is what is the scaling matrix that is being returned in the qda object. The help file on qda() says: ... scaling: for each group ?i?, ?scaling[,,i]? is an array which transforms observations so that within-groups covariance matrix is spherical. ... This is a bit ambiguous. I tried a few cases (spectral, QR decomposition, especially given that it is an

Hi, I have been using some of the functions in r for classification purposes, chiefly lda, qda, knn and nnet. My problem is that the only one I can figure out how to represenent graphically is lda (using plot.lda). I have tried 'fooling' this function into accepting qda input for plotting but to no avail. I wonder if you have any suggestions? Thanks alot, Anne Marie Power Marine lab.

Dear All, Suppose I have a program as below: Outside is a loop for simulation (with random generated data), inside there are several sapply()'s (10~100) over the data and something else, but these sapply's have to be sequential. And each sapply do not involve very intensive calculation (a few seconds only). So the outside loop takes minutes to finish one iteration. I guess the better way

Hi all! I am Angela, an Italian researcher and I am looking for an application that allows working in team, making a shared codebook, share a text database and code it. I tried AnSWR (the CDC''s QDA application) but its installation is too complicated for students and it is not working on latest version of Windows. What about Weft? Is it possible to share a project or, at least, merge

Dear wxruby users I''ve been trying to get wxruby-based weft-qda 0.9.6 running on a linux from scratch 6.1 system (this list had a discussion about weft-qda last year and alex fenton''s also been trying to help me out - no luck so far). I get stuck with wxruby 0.60 (I think). I compiled wxruby against wxGTK 2.4.2 (without gtk2, without unicode - gtk+ version is 1.2.10) - after

Dear R Help Members, I am aware how to plot the LD1 vs LD2 from a lda in R, using the code: plot(baseline.systat.hat$x, col=baseline.systat.hat$class,pch=as.numeric(baseline.systat.hat$class)) However, I need to use the quadratic discriminant function, qda due to data properties. Is there a way to obtain the same sort of plot for from a qda object (and the output of predict qda). I have not

Buenas tardes, He construido la función “myfun” al objeto de considerar aquellas persones que a partir de una determinada fecha de Apertura tienen como mínimo 65 años. Se tiene su fecha de nacimiento, su fecha de inicio en la institución y su fecha de salida de la misma. Doy vueltas al script y no acabo se saber cómo poder aplicar de un modo eficiente las instrucciones “if” ó bien “ifelse”, y me

I need to apply a yearly inflation factor to some wages and supply some simple sums by work category. I have gone at it with a brute force "for" loop approach which seems okay as it is a small dataset. It looks a bit inelegant and given all the warnings in the Intro to R, etc, about using loops I wondered if anyone could suggest something a bit simpler or more efficent? Example:

Hi, the following strange error appears when I use qda: > qda1 <- qda(as.data.frame(mfilters[cvtrain,]),as.factor(traingroups)) Error: function is not a closure That's also strange: > qda1 <- qda(mfilters[cvtrain,],as.factor(traingroups)) Error in qda.default(mfilters[cvtrain, ], as.factor(traingroups)) : length of dimnames must match that of dims Some backgroud: >

Perhaps, I should complement my previous e-mail question: I am trying to select variables through a quadratic discriminant analysis. It seems to me that a robust criterion is the value of the discriminatory power (i.e. the ratio of the separation of the class means to within-class variance) How can I obtain this ratio from V & R's qda() output ? Thanks (I hope this question is relevant) --

Hi Alex, Hi Weft-Users! I am looking for a tool for doing a qualitative analysis of mailing-list data. This means I have a *lot* of individual documents (the typical case: around 500-5000 emails), belonging to the same "super-document" (a mailing list). I have looked at several tools and I like that Weft is public domain and written in Ruby, so I want to figure out whether it

Hi there, Problem :: When one tries to change one or some of the columns of a data.frame, R makes a copy of the whole data.frame using the '*tmp*' mechanism (this does not happen for components of a list, tracemem( ) on R-2.6.2 says so). Suggested solution :: Store the columns of the data.frame as a list inside of an environment slot of an S4 class, and define the '[',