similar to: SPM/SemiPar -- Plotting additive interactions

Hello -- I posted this question yesterday and for some reason the post seems to be attached to the wrong thread. Also, I extended my test a little and it seems to indicate the problem is with spm. I would appreciate any help. Thanks. ========================================================== library(plyr) library(SemiPar) data <-

Hi, When you use the default knot choice in spm() (library(SemiPar)) a figure showing the knot locations is sent to the screen and you have to accept the knots to move on. I am trying to run simulations using this function. Is there a way to get spm() to use the default "REML" knots without needing to approve each set of knots? Here is an example: library(SemiPar) data(scallop)

Hi all, Does anyone know how to report heteroskedasticity and autocorrelation-consistent standard errors when using the "spm" command in SemiPar package? Suppose the original command is sp1<-spm(y~x1+x2+f(x3), random=~1,group=id) Any suggestion would be greatly appreciated. Thanks, Susan [[alternative HTML version deleted]]

Dear maintainers and R-devel, Several orphaned CRAN packages are about to be archived due to outstanding QC problems, but have CRAN and BioC packages depending on them which would be broken by the archival (and hence need archiving alongside). Therefore we are looking for new maintainers taking over maintainership for one or more of the following packages: R2HTML SemiPar cghseg hexbin lgtdl

Hi everyone: I want to fit the truncated polynomial smoothing to the quantiles instead of means, does someone know how to do it? I am thinking that maybe I can use SemiPar package, but can not find how. Thanks so many, Suyan

Hi All, Just thought you might be interested in a recently released R package, spm: Spatial Predictive Modelling. It aims to introduce some novel, accurate, hybrid geostatistical and machine learning methods for spatial predictive modelling. Of 22 functions available in spm, two functions are for accuracy assessment. Perhaps they are not only useful tools for spatial predictive modelling

Dear R users, A new version (1.1.0) of the ?spm? package for spatial predictive modelling is now available on CRAN. The introductory vignette is available here: https://cran.rstudio.com/web/packages/spm/vignettes/spm.html There are several new enhancements to the package including a fast version of random forest in using ranger (rg) library(ranger) and the ability to convert relevant

Hi all, I'm trying my best in changing the names of my experiments in the spectral map. My experiments are from six different time points, two as control and two treated experiments. I set have for each time point a different color . Now I want to change the symbols so that I have for the treated experiments one and for the controls a different one. But I want only two different symbols

Good Afternoon Everyone, I am looking for advice fitting a linear mixed model where the random components do not seem to fit within the model formulae for lmer. The columns of Z are not stratified and have the notional random formula (z1 | 1) + ... + (zk | 1). Context I am fitting a penalised thin plate spline with knots k1 to kn. The basis functions Zk are |x-ki|^3 and the penalty matrix has

Hi I need to a function that automatically fits a regression to data, using the stepAIC. I've ran the code manually and it works fine. However, when I run the function on the same data, the following error occurs: Problem in regimp(fullsim = simt, fullsim1 = simt1,..: Length of (weights) (variable 4) is 4271 != length of others (4278) I got the function to output the length of the dataset

Greetings, Fellow R-ians: I'm working with a few different quasi-likelihood formulations for some data I'm analyzing. I'd like to implement the Information Matrix Test (see, e.g., White, 1982, or Lancaster, 1984) for each of them to determine which of the models is more likely. Since the null distribution of the test statistic is chi-squared, I envision calculating the ordinate of

I am searching for an R version of the code written in GAUSS by Bruce Hansen for his paper on Econometrica, 2000, "Sample Splitting and Threshold Estimation". Someone can help me? Davide -- Davide Fiaschi Dipartimento di Scienze Economiche University of Pisa Via Ridolfi 10 56100 Pisa (PI) Italy Phone/Fax: ++39.050.2216208/++39.050.598040 E-mail: dfiaschi at ec.unipi.it Homepage:

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

Dear Friends, I am looking for an R version of the structural break test in Andrews (2003). The excellent strucchange package does not include this test (yet?). Is this test available in another package? If not, might there already be a function written to do this test? Thank you very much. Citation: Andrews, D.W.K. (2003), End-of-Sample Instability Tests. Econometrica, 71: 1661–1694.

Hi, I would need to extend the Friedman test to a replicated design. Currently the function: friedman.test(y, ...) only works for unreplicated designs. I found in Conover 1999 "Practical Nonparamteric statistics" an extension of the formula to my case. Nevertheless, other sources, like Sheskin 2000 "Parametric and Nonparametric statistical Procedures" and Daniel 1990

Dear List, I'm using gam in a multiple imputation framework -- specifying the knot locations, and saving the results of multiple models, each of which is fit with slightly different data (because some of it is predicted when missing). In MI, coefficients from multiple models are averaged, as are variance-covariance matrices. VCV's get an additional correction to account for how

I have a dataset which I am trying to smooth, using locally weighted regression. The y values are count data, integers with Poisson distribution, and it is important for the regression function to know this, since assuming a Gaussian distribution will lead to substantial errors. It is a time series; the x values have equal five minute intervals. Here is the problem: I have an embarrassment

Given a set of coordinates that form an irregular sampling area, is there an R function to determine boundary points (coordinates defining the limits of the area), either with or without user interaction ? # for example, given the following irregular sampling area, how could I define the boundary polygon? library(SemiPar) data(scallop) plot(scallop$longitude, scallop$latitude) Thanks. --Dale

Dear All, I would like to know if the Voung test (Voung; Econometrica, 1989) to compare two non-nested regression models has been implemented in R. Thanks in advance for your assistance, mirko [[alternative HTML version deleted]]

Does anyone know of a package that includes the Modified Sims test [Gewerke, 1983, Sims, 1972]? This test is used in econometrics and is a kind of alternative to the Granger test [Granger, 1969], which is in the package lmtest. Thanks in advance, chris Refernces: Gewerke, J., R. Meese, and W. Dent (1983), "Comparing Alternative Tests of Causality in Temporal Systems: Analytic Results and