similar to: Strange behavior of model.frame() when given subset

Dear memberships, I'm trying to estimate the following multivariate local regression model using the "locfit" package: BMI=m1(RCC)+m2(WCC) where (m1) and (m2) are unknown smooth functions. My problem is that once I get the regression done I cannot get the fitted values of each of this smooth functions (m1) and (m2). What I write is the following library(locfit) data(ais)

Hi, I am having an issue when creating a postscript file from RGL window. It seems to cut off some of the axis labels. Here is the code I am using. I created a 3D plot using RGL_0.71 with R 2.5 on Windows XP. z1<-c(5,4,1,4.5,2,3,2,1,1) z2<-c(6,8,7,7.5,5,3.5,4,1,1) z3<-c(3,2,4,7,3,4.5,6,2,3) x1<-seq(1,9) x2<-seq(1,9) x3<-seq(10,18) y1<-seq(8,0) y2<--1*y1

Dear memberships, I'm trying to estimate the following multivariate local regression model using the "locfit" package: BMI=m1(RCC)+m2(WCC) where (m1) and (m2) are unknown smooth functions. My problem is that once I get the regression done I cannot get the fitted values of each of this smooth functions (m1) and (m2). My program is the following: library(locfit)

The locfit library is now available through CRAN, in the Contributed R Code directory. Locfit fits local regression, likelihood and density estimation models, in the spirit of loess but with many additional features. To install, unpack the locfit_19980309.tar.gz file, and R INSTALL locfit Most of the functionality and examples on my home page http://cm.bell-labs.com/stat/project/locfit/ should

The locfit library is now available through CRAN, in the Contributed R Code directory. Locfit fits local regression, likelihood and density estimation models, in the spirit of loess but with many additional features. To install, unpack the locfit_19980309.tar.gz file, and R INSTALL locfit Most of the functionality and examples on my home page http://cm.bell-labs.com/stat/project/locfit/ should

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have two matrices: > m1 <- matrix(1,4,4) > m1 [,1] [,2] [,3] [,4] [1,] 1 1 1 1 [2,] 1 1 1 1 [3,] 1 1 1 1 [4,] 1 1 1 1 > m2 <- matrix(0,3,3) > diag(m2) <- 1 > m2 [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 1 0 [3,] 0 0 1 I want to get indicies from m2

I may be missing something obvious here, but consider the following simple dataset simulating repeated measures on 5 individuals with pretty strong between-individual variance. set.seed(1003) n<-5 v<-rep(1:n,each=2) d<-data.frame(factor(v),v+rnorm(2*n)) names(d)<-c("id","y") Now consider the following two linear models that provide identical fitted values,

I am unsure what is being returned, and what is supposed to be returned, when using 'predict' with "type='expected'" for an aftreg survival model. The code below first generates a weibull model, then uses predict to create a vector of the linear predictors, then attempts to create the 'expected' vector, which is empty. The final two steps in the code generate a

Hi, I''m trying to get a handle on hfsc. Here is my configuration: root@jmnrouter:/jmn# tc class show dev vlan1 class hfsc 1: root class hfsc 1:1 parent 1: ls m1 0bit d 0us m2 225000bit ul m1 0bit d 0us m2 225000bit class hfsc 1:10 parent 1:1 rt m1 191000bit d 25.0ms m2 135000bit ls m1 0bit d 0us m2 135000bit ul m1 0bit d 0us m2 225000bit class hfsc 1:20 parent 1:1 rt m1 22008bit d

Dear list, I have the following problem. I have a data frame like this CLUSTER YEAR variable Delta R_pivot M1 2005 EC01 NA NA M1 2006 EC01 2 NA M1 2007 EC01 4 5 M2 2005

Dear list, I'll try to be more clear in explaining my problem. I have a data frame like this called X: CLUSTER YEAR variable value1 value2 M1 2005 EC01 NA NA M1 2006 EC01 2 5 M1 2007

Dear All, I have two matrices A (40 x 732) and B (40 x 1230) and would like to calculate correlation between them.  I can use: cor(A,B, method="pearson") to calculate correlation between all possible pairs. But the issue is that there is one-many specific mappings between A and B and I just need to calculate correlations for those pairs (not all). Some variables in A (proteins, say p1)

Hi, everyone I am trying to estimate 3 parameters for my survival function. It's very complicated. The negative loglikelihood function is: l<- function(m1,m2,b) -sum( d*( log(m1) + log(m2) + log(1- exp(-(b + m2)*t)) ) + (m1/b - d)*log(m2 + b*exp(-(b + m2)*t) ) + m1*t - m1/b*log(b+m2) ) here d and t are given, "sum" means sum over these two vairables. the parameters

first, apologies for so many posts yesterday and today. I am wrestling with nls() and nls2(). I have tried to whittle it down to a simple example that still has my problem, yet can be cut-and-pasted into R. here it is: library(nls2) options(digits=12); y= c(0.4334,0.3200,0.5848,0.6214,0.3890,0.5233,0.4753,0.2104,0.3240,0.2827,0.3847,0.5571,0.5432,0.1326,0.3481) x=

I would like to perform partial mantel tests on only within group values, with "between group" values assigned to NA. This is possible in package ncf partial.mantel.test, however this sues a different permutation to that used in ecodist.ecodist will not accept data with NA values, returning a "matrix is not square error. is it possible to perform this test in ecodist? many thanks

Hi, I stumbled upon a strange thing regarding types and module linking, which I don't quite get, so maybe someone around here can enlighten me. Consider the following code, which will create 2 modules m1 and m2, and a named structured type %T = { i32 }; m1 contains only a function definition f(%T), m2 contains a function declaration f(%T) and a function definition h(%T), where h will call f

Hi R users, This query is regarding the use of the 'envelope' function in Spatstat. My data can be represented as a point process with CONTINUOUS marks: points <- ppp(x=x,y=y, marks=m, window= wind) However the marks are alignments (lines), and so have to be treated differently to normal scalar marks. Hence to create a mcf object with the appropriate test function for alignment

Hello List I have just written a little function that takes two matrices as arguments and returns a large matrix that is composed of the two input matrices in upper-left position and lower-right position with a padding value everywhere else. (function definition and toy example below). I need nonsquare matrices and rowname() and colname() inherited appropriately. Two questions: (1) Is there a

I've tripped over this behaviour as well. I ended up working around the problem by creating a new context every time I wanted to link modules together. Which led to me accidently generating one module using two different contexts. Which isn't an error that is detected by module verification. It only causes issues for comparisons like Type equality that compare pointers, and those types of

Dear lists, I want to construct a loop in R, but don't know how to do it. I can do it in SAS, but I prefer in R (which I am hoping I will off SAS for good soon). Could anyone help me to convert the SAS codes to equivalent R codes. Basically, the following codes were written to establish the sire gametes or phases for daughter design for one markers two alleles. Here are the SAS code: do