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Dear all, I'm a newbie in R. I am running simulations using a fixed bandwidth in nonparametric regressions, sending all the output to a file myoutput.txt using sink("myoutput.txt"), & R is printing all warnings by the end of the simulation on the file. I know the source of the problem & can take care of it. However, finding a 50 MB file (where all the output is printed, e.g.

...spss los datos de la muestra están representados en un histograma y a esos se les añade la curva de normalidad teórica). También esto es posible en r? Puntaje <- c (21, 23, 37, 48, 22, 29, 38, 30, 46, 26, 25, 46, 21, 34, 31, 43, 40, 46, 33, 44) Gracias de antemano. Saludos Cordiales, John Jacho DEPARTAMENTO DE OPERACIONES Av. 6 de Diciembre N33-42 e Ignacio Bossano, Torre Constitución, Piso 9 PBX: (593-2) 3982080 Ext: 2605 jjacho en mednet.com.ec

...C. (1999) Local Regression and Likelihood, Springer" from my local library, so a small explanation or advice would be greatly appreciated. I do not mind using an improved version of `what I want', but I would like to understand what am I doing? Thanks in advanced for your help, David Jacho-Ch?vez

Dear all, I'm interested in testing 2 nonlinear restrictions on coefficients of a nls object. Is there a package for doing this? Something in the lines of `test(nls object, res=c("res 1","res 2"),...)' I only found the function delta.method in the alr3 library that calculates the se of a singleton nonlinear restriction of a nls object using the delta method. Thanks in

Dear all, I am trying to use the 'glm' package as part of a semiparametric technique that involves weighting a likelihood in various ways, i.e. L(theta;data)=Sum_i=1,..,n (W_i)(log L(theta;data_i)) Where W_i can be a kernel weighting function, or W_i can be an indicator of 'non-missingness' divided by a propensity score. In a Monte Carlo exercise, the option glm(...,