similar to: multivariate splines

Hello, I am trying to estimate a multivariate regression of Y on X with regression splines. Y is (nx1), and X is (nxd), with d>1. I assume the data is generated by some unknown regression function f(X), as in Y = f(X) + u, where u is some well-behaved regression error. I want to estimate f(X) via regression splines (tensor product splines). Then, I want to get the predicted values for some new

I like what smooth.spline does but I am unclear on the output. I can see from the documentation that there are fit.coef but I am unclear what those coeficients are applied to.With spline I understand the "noraml" coefficients applied to a cubic polynomial. But these coefficients I am not sure how to interpret. If I had a description of the algorithm maybe I could figure it out but as it

I've written a series of functions that evaluates an integral from -inf to a or b to +inf using equally spaced quadrature points along a normal distribution from -10 to +10 moving in increments of .01. These functions are working and give very good approximations, but I think they are computationally wasteful as I am evaluating the function at *many* points. Instead, I would prefer to use

Hi, there. I have two questions about the diagnostics in multivarite statistics. 1. Is there any diagnostics tool to check if a multivariate sample is from multivariate normal distribution? If there is one, is there any function doing it in R? 2. Is there any function of testing if two multivariate distribution are same, i.e. the multivariate extension of Kolomogrov-Smirnov test? Thanks for

Hi, I would like to fit an (interpolating) spline to data where the derivatives at the endpoints of the interval are nonzero, thus the natural spline endpoint-specification does not make sense. Books (de Boor, etc) suggest that in this case I use not-a-knot splines. I know what not-a-knot splines are (so if I were solving for the coefficients directly I knew how to do this), but I don't

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 =

Hi, I am trying to find an elegant way to compute and store some frequently used matrices "on demand". The Matrix package already uses something like this for storing decompositions, but I don't know how to do it. The actual context is the following: A list has information about a basis of a B-spline space (nodes, order) and gridpoints at which the basis functions would be

Hi, I am approximation a value function (in dynamic programming) V: R^n->R. In different versions of the problem, n is between 2 and 5. I would like to use splines to use this, I checked the mailing list and CRAN but couldn't find anything that would help me (Tps in fields is too slow, cobs would be really nice but seems to be one-dimensional). Is there any package that would at least

Dear all, I need to compute tensor product of B-spline defined over equi-spaced break-points. I wrote my own program (it works in a 2-dimensional setting) library(splines) # set the break-points Knots = seq(-1,1,length=10) # number of splines M = (length(Knots)-4)^2 # short cut to splineDesign function bspline = function(x) splineDesign(Knots,x,outer.ok = T) # bivariate tensor product of

Dear list, I am trying to use the 'mvrnorm' function from the MASS package for simulating multivariate Gaussian data with given covariance matrix. The diagonal elements of my covariance matrix should be the same, i.e., all variables have the same marginal variance. Also all correlations between all pair of variables should be identical, but could be any value in [-1,1]. The problem I am

Hi all, Could anybody recommend some easy-to-understand and example based notes/tutorials on how to use cubic splines to do filtering on multi-dimension data? I am confused by the 1-dimensional case, and more confused by multi-dimensional case. I found all the books suddenly become very abstract when it comes to this subject. They don't provide examples in R or Splus at all. Specifically,

Dear "R" users, I have a question about the Package DierckxSpline. I have tried to find the answer by myself but it didn't worked out. I wondered if Dierckxspline can use different sets of y values in one time to fit a line with knot. I have different sets of Y values representing the same thing for different voxels (in an fmri image). I have already fitted the data in different

Hi, is there a way in R to generate a polynomial spline with multiple predictor variables? I have one response and two predictors and I'm trying to fit a spline model for this... Please cc me on the reply.. Thanks, nirmal

Hi, If I set df=2 in my smooth.spline function, is that equivalent to running a linear regression through my data? It appears that df=# of data points gives the interpolating spline and that df = 2 gives the linear regression, but I just want to confirm this. Thank you, Steven

Hi Can any one inform me an r package used to fit Cubic M-splines or r functions used to have design and penalty matrices in fitting cubic  M-splines please? Thanks, Tigist [[alternative HTML version deleted]]

Hola a todos, Llevo unos días buscando en Internet alguna librería de R que me permita el cálculo de NURBS a partir de ficheros de texto con coordenadas X Y Z de puntos. No he encontrado nada que me convenza y finalmente, hoy, he empezado a trabajar este asunto en MATLAB (la última vez que había usado este programa fue en 1999). ¿Alguno de vosotros ha trabajado en R? ¿Podríais hacerme alguna

Suppose I have two var x and y,now I want to fits a natural cubic spline in x to y,at the same time create new var containing the smoothed values of y. How can I get it?

Hai everbody,  Is there anyone have simple application b-spline in r language? I need it for make me understanding about b-spline for polynomial spline. thank u Arif  New Email addresses available on Yahoo! Get the Email name you&#39;ve always wanted on the new @ymail and @rocketmail. Hurry before someone else does! [[alternative HTML version deleted]]

hola soy nuevo usuario de R y necesito crear un objeto p tal que, p=lambda*integral[f´´(x)^2 dx ] donde "lambda" es uno de los parametros que resultan de la funcion "smooth.spline()" y la integral es sobre la derivada 2 de esa misma funcion... dos cuestiones: 1) como extraigo lambda de los resultados de smooth.spline() para usarlo como objeto cuando lo requiera y 2) como

Hello group! Is there a package that allows to fit smooth *periodic* splines to data? I'm interested in a function which combines the functionality of smooth.spline and splines::periodicSpline. Thanks, Andrey