similar to: Using lm with a matrix?

Can anyone explain to me what this error message means, why I'm getting it, and how to fix it? lines(lowess(xdat, ydat, f=.5), col=3) Error: NAs in foreign function call (arg 1) ______________________________________________________________________ Stuart Luppescu -=-=- University of Chicago ºÍʸ ¤ÈÃÒÆàÈþ¤ÎÉã(EUC) -=-=- s-luppescu at uchicago.edu

I can't get identify to work, using R 2.0.1 under windows xp pro, service pack 2. Here's what I enter, and the result: > plot((our.frame2$c1),(our.frame2$c9)) # Produces desired plot > identify(our.frame2$c1) # Plot comes to forefront, so I select a point warning: no point with 0.25 inches numeric(0) Is my call to identify correct? The help page for indentify (from

Hi! I'd like to plot things with axes going from the highest to the lowest value, so that e.g. high values on the xaxis are plotted to the left and low values to the right. Could anyone tell me how this is done? I couldn't find anything in the documentation. Thanks a lot! Silli

Dear R-users, I am very enthusiastic about the capacities offered by the np package and pretty fond of it. Nevertheless, trying to estimate Ichimura and Klein and Spady models on my data, I would like to be able to provide the npindex function with my guesses for the bandwidth (eventually computed by other means). The fact that the option 'bandwidth.compute' in the function npindexbw

Dear forum users, It's 3:35am and I am swamped with statistics homework lol I'm terrible with R and this time I have no idea what the prof wants. Here is the question: Consider the (two-??sample) Wilcoxon rank statistic T = ?rank(Xi). For n1=106 and n2=192, determine by simulation the ?=.05 critical point for testing H0: ?=0, H1:?<0. We can do this as follows: For m=10000 (no wimpy

Dear all, I am using np package in order to estimate a model with Klein and Spady estimator. To estimate the model I use KS <- npindexbw (xdat=X, ydat=Y, bandwidth.compute=TRUE, method="kleinspady", optim.maxit=10^3, ckertype="epanechnikov", ckerorder=2) and to estimate beta hats standard errors I use KSi <- npindex(KS, gradients=T, boot.num=300) vcov(KSi) This is

Dear all, I am trying to use the np package for the estimation of a model with Klein and Spady's semiparametric estimator. When though, I include a constant term ( a column with 1s in X) then the following message appear: Multistart 1 of 3...Error in optim(c(beta, h), fn = optim.fn, gr = NULL, method = optim.method, : non-finite value supplied by optim So, how can I include a constant

Dear all, I would like to estimate the standard errors of Klein and Spady's estimator for that I am using: library(np) N<-100 X<-matrix(c(rnorm(N,1,1), rnorm(N,0,1)), ncol=2) BETA <-matrix(1,2,1) Z<-X%*%BETA L<-rlogis(N,location=0, scale=1) Y <-as.vector(X%*%BETA+L>=0)*1 KS <- npindexbw (xdat=X, ydat=Y, bandwidth.compute=TRUE, method="kleinspady",

Dear list, I am using the np package. With the npindex function I estimate a semiparametric single index model using the method of Klein-Spady. P(Z=1|X) = G(X?b) I don?t have any problems to calculated the fitted values and standard errors X?b: bw = npindexbw(xdat=x, ydat=y_bi, method="kleinspady", nmulti=2) model = npindex(bws= bw3, gradients= TRUE, residuals = TRUE, boot.num =

Full_Name: bernardo moises lagos alvarez Version: 2.4.0 OS: Windows XP professional Submission from: (NULL) (152.74.219.16) I need obtained the MLE of weibull parameters using the nlm with exact gradient an hessian. I am doing. bug report :Erro en log(b) : el argumento "b" est? ausente, sin default 1.Construction to objectiv functin with n=1 data

Hello, First of all, let me apologize that my statistics background is modest at best. I am doing some extreme value analysis on model output (WRF) which have the following dimensions: speed(time,lat,lon) I am trying to fit the GPD (gpd.fit) to each point (time,lat,lon) to get a return level plot with values at each grid point. (Map with return level by location.) Here is some code I

i am trying to replicate the following graph using xyplot : attach(x) plot ( jitter(type), mortality, pch=16, xlim = c(0.25, 3.75)) lines ( c(1-0.375,1.375) , c ( median(mortality[type==1]), median(mortality[type==1])), lwd=5,col=2) lines ( c(2-0.375,2.375) , c ( median(mortality[type==2]), median(mortality[type==2])), lwd=5,col=2) lines ( c(3-0.375,3.375) , c ( median(mortality[type==3]),

hi all: Here's a dataframe(dat) and a vector(z): dat: x1 x2 x3 0.2 1.2 2.5 0.5 2 5 0.8 3 6.2 > z [1] 10 100 100 I wanna do the following: 10*x1,100*x2,1000*x3 My solution is using the loop for z and dat(since the length of z is the same as ncol of dat),which is tedious. I wanna an efficient solution to do it . Any help? Many thanks! My best

[This email is either empty or too large to be displayed at this time]

I ran the following code: And I run into problems with the last line of code (when it says hn<-......). I keep getting an error code: Error in distsamp(~hab ~ 1, peldist, keyfun = "halfnorm", output = "density", : object 'A' not found I would appreciate any and all help. rm(list=ls(all=TRUE)) #clear the computer's

Hola a todos, Soy nuevo en R y estoy intentando modelizar una serie de datos no estacionarios usand la distribucion Generalizada de Valores Extremos GEV. ¿Podriais indicarme como se modeliza una tendencia polinómica (cuadrática, por ejemplo) en alguno de los 3 parámetros (situación, escala o forma)? He encontrado documentación a cerca de modelización linear o exponencial, pero no acabo de

Hello, I have a double vector, x. I can access the i'th element as REAL(x)[i] Is there a function for this? I know i can write my own, but was seeing if one already exists. I did check Rinternals.h but didn't see one. Cheers Saptarshi

hello, i'am is new in R software.i have try to make a function but it can't give what it should.i dunno what have to do next. Can somebody help me to solve it.i'll very appreciate... ##GEV simulation(Non-stationary) dsim<-function(n, alpha, beta,sca,sha){ t <- 1:n location <- alpha + beta*t inv.df<-function(x) location + -(sca/sha)+(sca/sha)*(-log(x))^(-sha) u<-runif(n)

Ein eingebundener Text mit undefiniertem Zeichensatz wurde abgetrennt. Name: nicht verf?gbar URL: https://stat.ethz.ch/pipermail/r-help/attachments/20070510/b26482f4/attachment.pl

Dear All, I have a question about package "ismev", its function "gpd.fit", and interpretation of the results. I used the package ismev to do an extreme value analysis on a fire dataset. Two variables are used in the analysis. The focal variable is acreage burned per fire, ranging from 1 to 5000 acres per fire. In total, there are 69,980 observations. The date covers