similar to: how to estimatae in single index models

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 R-Help, I am Deniz. I am currently trying to replicate a semiparametric sample selection paper and I am working on Klein and Spady estimator. I am using the npindex() and npindexbw() functions. The problem is, I need results for single bandwidth and when I set bandwidth computation to "FALSE" mode, R is not optimizing anything. Here is the code I am using:

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.14-1). The package is briefly described in a recent issue of Rnews (October, 2007, http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf) for those who might be interested. A somewhat more detailed paper that describes the np package is forthcoming in the Journal of Statistical Software

Dear R users, An updated version of the np package has recently been uploaded to CRAN (version 0.14-1). The package is briefly described in a recent issue of Rnews (October, 2007, http://cran.r-project.org/doc/Rnews/Rnews_2007-2.pdf) for those who might be interested. A somewhat more detailed paper that describes the np package is forthcoming in the Journal of Statistical Software

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 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 =

Dear all, I would like to create a code for semiparametric Klein and Spady's estimator. For that I created a function that provides the log-likelihood function for each observation (so it is a function of betas and i, where i denotes the observation). Now, in order to maximize the log-likelihood function, I have to sum these log-likelihood functions for each i and so to get another function

Dear List's Members, I'm trying to implement "1. Roger Klein and Francis Vella, ?A semiparametric model for binary response and continuous outcomes under index heteroscedasticity,? Journal of Applied Econometrics 24, no. 5 (2009): 735-762. " estimator. I have a technical doubt about the choice of the optimizer for the likelihood function maximization. That of pg. 743, the

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 pleased to announce the release of version 1.0.0 of DPpackage on CRAN. DPpackage covers some important models using Dirichlet process priors. The package includes: Semiparametric Bernoulli regression Semiparametric Density estimation Semiparametric Linear mixed models Semiparametric Generalized linear mixed models Semiparametric AFT model for interval-censored data I

Dear List, I'm just teaching myself semi-parametric techniques. Apologies in advance for the long post. I've got observational data and a longitudinal, semi-parametric model that I want to fit in GAM (or potentially something equivalent), and I'm not sure how to do it. I'm posting this to ask whether it is possible to do what I want to do using "canned" commands

folks, does anyone know if the SEMIFAR model has been implemented in R? i see that there's a S-FinMetrics function SEMIFAR() that does the job, but I have no access to that software. essentially, this semiparametric fractional autoregressive model introduces a deterministic trend to the FARIMA(p,d,0) model (which, as i understand it, takes care of the random trend and short and long memory).

>Date: Fri, 22 Feb 2002 09:48:16 -0600 (CST) >From: sun at cae.wisc.edu >Subject: [R] Does R have semiparametric package for time series > >Hello, All: I am new to R. I wonder if there is package for nonparametric or >semiparametric processing of time series. Thank you very much. > >Hongyu Sun Have a look at package "sm" and, in particular function

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

I have data that comes in every 7 seconds or so and I'd like to display it in a spreadsheet, and possibly take user input from the spreadsheet. I have installed RGnumeric and written an appropriate R function that reads, manipulates and displays the data by writing via RGnumeric to a spreadsheet. However, the results of this are not displayed until the R function returns, so refreshing by

Hello, I have encountered results which I am not sure how to interpret when using anova.gam to compare 2 different models. For certain tests the results do not include an F- or associated p-statistic. This happens when comparing certain models and not others, and I do not discern a patten explaining when the test works and when it does not. Here is some output for some of my tests (y#, x1, and

Dear R users, A new package titled `np' is now available from CRAN. The package implements recently developed kernel methods that seamlessly handle the mix of continuous, unordered, and ordered factor datatypes often found in applied settings. The package also allows users to create their own nonparametric/semiparametric routines using high-level function calls (via the function npksum())

Dear R users, A new package titled `np' is now available from CRAN. The package implements recently developed kernel methods that seamlessly handle the mix of continuous, unordered, and ordered factor datatypes often found in applied settings. The package also allows users to create their own nonparametric/semiparametric routines using high-level function calls (via the function npksum())

Hi All, Sorry for this is a very naive question. I am trying to do binary classification (male vs female) using glm using following data: X1 X2 X3 Class 2.3 4.5 2.1 Male 0.9 3.2 1.6 Male 1.7 1.8 2.6 Feamle I am trying to use predict.glm for prediction with type="respose" which gives the predicted probabilities as per documentation. My

Sorry to bother you and I hope this will be easy to solve. I am trying to run R scripts in batch, called from another programme, under Windows XP. I have R 2.4.1 I need to be able to pass a list of numeric arguments to the script as well. The Rscript and its input data file are attached. I have been trying the syntax below but it doesn't work: Rcmd BATCH -no-save