similar to: Problems with packages fda and splines (PR#13263)

I would like to create a functional data object where both domain and range are matrices. My erroneous attempts are below. Can you suggest corrections? library(fda) domain<-matrix(c(1,1.1,1.2,2,2.1,2.1,3,3.1,3.2,4,4.1,4.2,5,5.1,5.2), nrow = 5, ncol=3, byrow=TRUE) range<-sin(domain)+matrix(rnorm(15,sd=0.1),nrow=5, ncol=3) myfd<-Data2fd(argvals=domain, y=range) #Error in

Hello, I'm working with an array; I'm trying to make it so that an array of dim(42,2,2) has names whose length corresponds to that of the array, and am hoping someone with experience with this can see what I'm not doing correctly: data11 = array(0,c(41,2,2)) y = lsoda(x0,times,fhn$fn.ode,pars)#This is make.fhn() from colloc infer package# y = y[,2:3]

Hello , i am working in the functional time series using the multivariate time series data(hourly time series data). Sir? i am using FAR model more than one order for which no statistical package is available in R, so for this i convert my data into functional form and obtained the functional principle component and from those FPCA i extract their corresponding? FPCscores. Know i use the VAR model

Hello , i am working in the functional time series using themultivariate time series data(hourly time series data). Sir? i am usingFAR model more than one order for which no statistical package is available inR, so for this i convert my data into functional form and obtained thefunctional principle component and from those FPCA i extract theircorresponding? FPCscores. Know i use the VAR model on

Good morning,??Please help me to code this code in R. I working in the multivariate time series data, know my objective is that to one year forecast of the hourly time series data, using first five as a training set and the remaining one year as validation. For this??I transform the the data into functional data through Fourier basis functional, apply functional principle components as dimensional

I have a set of data for US t-bill returns and US stock returns frm 1980-2012. I am trying to bootstrap the data and obtain the minimum variance portfolio and repeat this portfolio 1000 times. However I am unable to get the correct code function for the minimum variance portfolio. When I tried to enter Opt(OriData+1, 1, 5, 0), I get "error:subscript out of bounds" Please help!

Good morning dear administrators, Please help me to code this code in R. I working in the multivariate time series data, know my objective is that to one year forecast of the hourly time series data, using first five as a training set and the remaining one year as validation. For this??I transform the the data into functional data through Fourier basis functional, apply functional principle

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 <-

Hello, We would like to apply the smooth monotone function to our data which correspond to a non-linear function. We follow the example posted on the web, but in our case it did not apply. We always get a straight line in response. Which parameters we should change. ind.basis = create.bspline.basis(c(min(time),max(time)),nbasis=38,norder=4) Wfdob =

Hi, I have a 7000x7000 matrix, and each element is an integer. For each element, I want to apply the function : wt <- 0 for(q in 1:count){ wt <- wt + 0.5^(q-1) } I get the value of 'count' from the elements in the matrix , and want to store the corresponding 'wt' value for that element. I suppose I could loop through the matrix, and apply the function to each

I've just encountered a segfault when using DierckxSpline::percur function. Below is the minimal example which triggers the error: --- library(DierckxSpline) x <- 1:10 y <- rep(0, 10) pspline <- percur(x, y) --- *** caught segfault *** address (nil), cause 'memory not mapped' Traceback: 1: .Fortran("percur", iopt = as.integer(iopt), m = as.integer(m), x =

I'm trying to turn some GenericValues into Constants in the interpreter using code like this, in a switch statement: case Type::IntTyID: SI = ConstantSInt::get(FB->getType(), ArgVals[i].IntVal); params.push_back(UI); UI->dump(); //for testing break; FB is a Function::ArgumentListType::iterator ArgVals is a std::vector<GenericValue> the switch

From: "Richard W.M. Jones" <rjones at redhat.com> If the parent process uses a pipe (or any fd, but pipes are a particular problem), then the recovery process would hold open the file descriptor(s) of the pipe, meaning that it could not be fully closed in the parent. Because the recovery process doesn't use exec(2), this wasn't avoidable even using FD_CLOEXEC. Avoid this

Greetings everyone, I was wondering if anyone had experience in using fda (flexible discriminant analysis) in the mda package. Specifically, I can run the model but I cant locate/produce much of anything beyond the predicted values and confusion matrix. I've been searching for more examples or documentation but cant seem to locate any specific to the program itself. I need to be able to find

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

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

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

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

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