similar to: 'fda' 1.2.2 is now available on CRAN.

fda 1.2.3 ======================== Version 1.2.3 of the fda package has just been released. This version adds to previous versions a script to create most of the figures of chapter 6 of "Applied Functional Data Analysis" by Ramsay and Silverman. Other changes offer simpler calls to time warping / registration and functional principal component functions. The fda package supports the

Dear all, Another newbie just got attracted to this mailing list. I am a biologist currently working my way through R, had sort play around with python earlier this year. I have some data exhibiting periodicity ** my data consists of peaks and valleys, with peaks arising due to the presence of a repetitive structural unit,** with x being a reference grid (position along a chromosome) and y

Hello, All: fda_2.2.8 (functional data analysis) is now available on CRAN. This revision includes the following improvements: 1. A bug in pca.fd has been fixed. 2. Many functions have a new argument "returnMatrix", which if TRUE allows the function to use the sparse matrix representations in library(Matrix). This should allow users to solve some larger

Hi, All: What might cause "R CMD check" to report, "could not find function" for a function that has long been in the 'fda' package? Both Jim Ramsay in Ottawa, Canada, and I in San Jose, CA, get this same error. I replicated it with a fresh, anonymous checkout from R-Forge (svn checkout svn://svn.r-forge.r-project.org/svnroot/fda). With this, I did

Hi, Jim: Could you please look at svd2.Rd and see what it says? It may give an example, where it gave a better answer than svd -- i.e., a marginal case, where svd2 honestly gave a better answer than svd. If we find -- either in svd2.Rd or in one of the revdepchecks -- an example where svd2 gives a demonstrably different answer, we need to consider what to do about that. 1.

Basically all I want to do is predict a scalar response using some curves. I've got as far as doing a regression (using fRegress from the fda package) but have no idea how to apply the results to a NEW set of curves (for prediction). I have N=536 curves, and 536 scalar responses. Here's what I've done so far: * I've created a basis for the curves. * I've created a

Dear R users, I'm trying to perform flexible discriminant analysis (fda) with method bruto. I applied the fda function on my training data: bruto.fda <- fda (fda.formula,data=train.data) where fda.formula is: PRES ~ VA_D123 + VA_D124 + VA_D127 + VA_DARU + VA_DCAN + VA_DFON + VA_DLAP + VA_DRID + VA_DRIR + VA_VVEG + VA_WDIN + VA_DIF3 + VA_DIF4 + VA_DIF5 + VA_CAAC + VA_CABC +

Hello, All: ????? Roughly a decade ago, I added "matplot.Date" and "matplot.POSIXct" to the "fda" package, so we could get reasonable labeling of the horizontal axis when "x" was class "Date" or "POSIXct".? I also added a local version of "matplot.default" that just changes the defaults for "xlab" and

Dear all, I'm trying to build some fda objects using smooth.pos() from fda package. Here is what I try: >X <-c(0.4541139, 0.4802537, 0.5091228, 0.3894931, 2.1512258, >7.9301281, 62.3876109, 54.1168247, 67.8769904, 91.0670615, 20.0682440) >basis <- create.bspline.basis(c(-100, 100), 7, 5) >MDA.fdPar <- fdPar(basis, 2, 0.01) >MDA.fda.joint <-

Yesterday I just noticed the new document on R and regulatory aspects for biomedical research posted at http://www.r-project.org/doc/R-FDA.pdf Coming from an institution that performs a large number of clinical trials for FDA and being an advocate of R myself, I have found that the following issues usually come up when discussing the use of R for FDA trials: 1. Most FDA submissions come down to

I hope that Marc doesn't mind, but I felt that part of his recent post was important enough to deserve it's own subject line rather then being lost in a 60-msg-long thread... On Sun, Jan 11, 2009 at 10:08 AM, Marc Schwartz <marc_schwartz at comcast.net> wrote: ... I strongly believe that the comments regarding R and the FDA are overly negative and pessimistic. The hurdles to

Dear Dr Hornik / R help list, I am using the mda package and in particular the fda routine to classify a set of 162 neurons falling in to 11 neuronal cell types according to 17 morphological variables. I would like to use a cross-validation approach in which I split the data, train with one part amd then test the predictive accuracy of the discriminant functions with the remaining part. However

Hello R help list, I am using the mda package and in particular the fda routine to classify a set of 4409 trips. I preformed a flexible discriminant analysis (FDA) using a set of 148 trips. A total of 36 predictors were considered. the resulting FDA rule was applied to the 4409 trips and for the same predictors in order to predict to which group the trip will belong. A consistent error is

Hello, I would like to use fda library to compare sampled curves that are density profiles. But I encounter some problems to register my data : I know that I must use a registration function to align functions in order to have important features found in each curve occur at roughly the same argument value, prior to do subsequent analysis ( PCA and cluster analysis). But I do not

Full_Name: David D Degras Version: 2.8.0 OS: Mac OS X Submission from: (NULL) (128.135.239.11) I have recently installed the version 2.8.0 of R along with package fda (v 2.0.2) and its dependencies (including package splines v. 2.8.0). Here are my problems: 1) The package splines should feature functions such a predict.bs, predict.bSpline and such and it does not! I can make calls to bs, ns,

Dear friends - I am trying to understand fda and working with the 2009 book from Springer. I run the scripts directly from a new installed fda library and include sessionInfo() below. This is from the script fdarm-ch09.R - I seem to have got not fda_2.2.8 but 2.2.7 - is that the problem? Where do I get .8 as I just reinstalled? Best wishes Troels Ring, Nephrology Aalborg, Denmark >

Hi all, Has anyone tried to do k-fold cross validation for flexible discriminant analysis ( mda library), for example, using crossval() in bootstrap? The problem is that the function crossval() requires a separate matrix for predictors and another for responses, whereas the function fda(), using the formula argument only. Is there another way of doing k-fold cross validation for functions which

The Biostatistics Analytics Team at the FDA Center for Food Safety and Applied Nutrition seeks an MS/PhD in computer science (or related field) with experience in bioinformatics. The Analytics Team is responsible for computational support for projects involving large chemical and microbial hazard data sets, including bioinformatic and statistical analysis of bacterial genomic data for foodborne

UseR's- As this is slightly off-topic I will limit the discussion to only the major points; for further information feel free to reply off-line. DIA and FDA are hosting a forum to discuss (as per the Goal of the announcement--see link below) "a vendor-neutral software product to support validated analytic procedures ("tools") and make tool development a collaborative effort

This thread reveals that R has some holes in the solution of some of the linear algebra problems that may arise. It looks like Jim Ramsay used a quick and dirty approach to the generalized eigenproblem by using B^(-1) %*% A, which is usually not too successful due to issues with condition of B and making a symmetric/Hermitian problem unsymmetric. In short, the problem is stated as follows: