similar to: surface fitting

I'm trying to find a way to fit a polynomial of degree n in x and y to a set of x, y, and z data that I have and obtain the coefficients for the terms of the fitted polynomial. However, when I try to use the surf.ls function I'm getting odd results. > x <- seq(0, 10, length=50) > y <- x > f <- function (x, y) {x^2 + y} > library(spatial) > test <-

loess() should be able to do robust 2D smoothing. There's no natural ordering in 2D, so defining running medians can be tricky. I seem to recall Prof. Koenker talked about some robust 2D smoothing method at useR! 2004, but can't remember if it's available in some packages. Andy From: Vladislav Petyuk > > Hi, > Are there any multidimenstional versions of runmed() and >

I have the following data table: [,1] [,2] [,3] [,4] [,5] [1,] 2575 1927 1754 581 354 [2,] 1156 810 730 541 237 [3,] 417 297 199 125 110 [4,] 281 132 132 47 58 [5,] 152 84 87 54 19 Each column represents a time interval expressed in nano-seconds Each row represents an energy interval expressed m=n MeV Each table value represents the average gamma rays intensity

Hello, I am looking into description of surf.ls(spatial) and see under value $beta - the coefficients. When I use polynomial of degree 2 to fit surface I expect to get 4 coefficients: z = a_1 x^2 + a_2 xy + a_3 y^2 + a_4 What do beta really stand for and why do I get $beta vector of length 6? Thakns, Mark

I have a general question about using thin plate splines in the surf and ordisurf routines. My rudimentary knowledge of a gam is that with each predictive variable there is a different smooth for each one and then they are added together with no real interaction term (because they don't handle this well?). Now, If I have two variables that have a high D^2 score and a low GCV score (I am

Hi, Is there a way to plot more than one trend surface using the functions contourplot() and wireframe(). I have found an add=T in contour(), but no equivalent argument in contourplot() and wireframe()? I have taken the example 11-2 (pages 441-451) from Design and analysis of experiments (Montgomery 2001, 5th edition) to see if this could be done in R. I have managed to plot individual

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

Dear R-helpers! What it's means "Rank failure in Choleski decomposition" by using of function surf.gls {spatial}? Sincerely Yours Branimir K. Hackenberger

I have an array of floating-point measurements on a square (5 by 5) 2d grid. The data are nominally constant, and somewhat noisy. I need to find any significant spatial trend, e.g. bigger on the left, bigger in the middle, etc. I have many thousands of these data sets that need to be scanned for 'interesting' spatial variations, selecting the datasets that are beyond some criterion of

Hello Is there any R package which can do 3-D splines (reconstruct a surface based 3-D data input) ? Thanks, Zhaoming

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Question: I have matrix (n x3) that represents discrete data. Each row of matrix is 3-D point (x,y,z). I would like to get contour map (z value) at two dimension (x,y). How can I use related contour function to do this job? I am not sure if I clarify this question. For example, we can get point (x,y) at 2 dimension according to first two columns of matrix. Then I want to connect same value

Hello all, I have two questions about anova (one is probably VERY basic...) 1 - when one asks for a summary of a trend surface created with surf.ls, he/she gets: > summary(g3r) Analysis of Variance Table Model: surf.ls(np = 3, x = gradiente$east, y = gradiente$north, z = gradiente$num1) Sum Sq Df Mean Sq F value Pr(>F) Regression 215.7182 9 23.968693976

Dear friends, When i read the R-help , i often find the following case: e.g.:surf.gls(np, covmod, x, y, z, nx = 1000, ...) #Package Spatial: Arguments: covmod: function to evaluate covariance or correlation function * ...: parameters for 'covmod'* How should i find the further information on "*...: parameters for 'covmod'*" ? I use the ?covmod, but

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 =

Am Dienstag, 25. April 2017, 08:50:34 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 14:58, G?ran Brostr?m wrote: > | hello, > | > | I just installed R-3.4.0 from scratch: > | > | $ sudo apt install r-base > | > | but when I try > | > | > library(survival, lib.loc = "/usr/lib/R/library") > | > fit <- coxph(Surv(exit, event) ~ x, data =

Good evening,I am Marta Colombo, student of "Politecnico di Milano". I'm studying Local Regression Techniques such as loess, smoothing splines and kernel smoothers. Choosing "symmetric" for the argument "family" in loess function it is possible to produce a robust estimate , in function smooth.spline and ksmooth I didn't find this possibility. Well, is there a

Hello, there, I got this error when i tried to run " data.kr <- surf.gls(2, expcov, data, d=0.7);" "Error: cannot allocate vector of size 382890 Kb Execution halted" My data is 100x100 grid. the following is the summary of "data": > summary(data); x y z Min. : 1.00 Min. : 1.00 Min. :-1.0172 1st Qu.: 26.00

Hi.., is there any funcrion in R to fit a periodic B-spline Surface Harsh --------------------------------- Brings words and photos together (easily) with [[alternative HTML version deleted]]

In an experimental setup we obtain z-data samples at equidistant grid points. The surf.gls (Kriging) algorithm produces an error under this circumstance when performing the Choleski decomposition. A workaround is to dither the grid coordinates using (x <- rnorm(length(x)) ; y<- rnowm(length(y))). Question: Is this an expected behaviour of the surf.gls function ? Regards, Berthold