similar to: quantile regression using SemiPar package

Hi, I just try to draw multiple plots in one page using R, I used par command. For example I have 7 plots, but instead of arranging them in the default way plot1 plot2 plot3 plot4 plot5 plot6 plot7 I want them in this order plot1 plot2 plot3 plot4 plot5 plot6 plot7 Could somebody tell me how to do this, please? Thanks so many. Suyan

Hi Everyone: I need some help on combining two datasets into one. Since for those two datasets, there are different variables. Like In dataset 1, I have pt x1 x2 1 12 24 2 20 17 In dataset 2, I have pt x2 x3 3 19 33 4 20 16 The final dataset I want should look as pt x1 x2 x3 1 12 24 NA 2 20 17 NA 3 NA 19 33 4 NA 20 16 I used setdiff and rbind together and got what I

Hi, everyone: I forget on how to save a result from R as a word document. For example, if I run the linear regression and want to save the result: summary(lm(y~x) in a word file. So I can show it later to my clients. Any idea on how to do this? Thanks a lot, Suyan

I am trying to combine two arrays with different dimensions into one. For example The first one is 1 2 3 4 5 6 The second one is 7 8 9 10 The resulted one would be like , , 1 1 2 3 4 5 6 , , 2 7 8 9 10 I used abind to do this, but failed. Could somebody please let me know how to do this in R? Thanks so many. Suyan

Hi, I just made a boxplot but I want to change the thickness of the line used for the median to look a little thinner. Could anyone please help me figuring out the R-code to do it? Thanks, I really appreciate it. Suyan

Hi, everyone: I am running logistic regression on a bunch of variables using apply command. But an error occurs, the whole process stops. I am wondering if anyone knows how to skip this error and to continue the regression for the rest of variable. What I did is that first confine a function to the logistic regression, then use apply(data, 2, reg.fun) Then I got an error which is [1]

I'm taking the residual-regression approach to semiparametric estimation (Robinson 1988, Econometrica), and basically using SemiPar simply as a convenient means of doing multivariate nonparamteric additive models. The final bit of code is here: finalfit <- spm(res~f(V3,basis="trunc.poly")+f(V5,basis="trunc.poly")+f(V6,basis="trunc.poly")) summary(finalfit)

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

When all else fails, read the help page... ?fivenum says to look at ?boxplot.stats, and the "Details" section of ?boxplot.stats has, well, details. Tukey had reasons to call those hinges rather than quartiles. Andy > -----Original Message----- > From: Knut M. Wittkowski [mailto:kmw at rockefeller.edu] > Sent: Thursday, May 29, 2003 5:58 PM > To: Matthias Kirschner >

R-ers: I was wondering if anyone had suggestions on how to implement a GAM in a quantile fashion? I'm trying to derive a model of a "hull" of points which are likely to require higher-order polynomial fitting (e.g. splines)-- would quantreg be sufficient, if the response and predictors are all continuous? Thanks! --j

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]]

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 <-

Is there any implementation in R for finding the phase shift between two continuous signals. I would like to find the average phase shift for tow signals over two years. thanks Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted

I have summary statistics from many sets (10,000's) of near-normal continuous data. From previously generated QQplots of these data I can visually see that most of them are normal with a few which are not normal. I have the raw data for a few (700) of these sets. I have applied several tests of normality, skew, and kurtosis to these sets to see which test might yield a parameter which

Dear R-Help members, I am using Simon Wood`s mgcv package version1.7-22and R version 3.0.0 (2013-04-03) for fitting a GAM-Model to the LIDAR Data contained in the "SemiPar" package. Here is the code for fitting the model and for plotting the result: data("lidar") attach(lidar) ### # mgcv fitting ### gam_fit <- gam(logratio ~ s(range, k = 40, bs = "cr"), gamma

I am trying to `cut' a continuous variable into contiguous classes containing approximately an equal number of observations. I thought quantile() was the appropriate function to use in order to find the breakpoints, but I end up with classes of different sizes - see example below. Does anybody have an explanation for that? And what is the `recommended' way of computing what I am looking

Hi, I'm working on a data set that contains a couple of factors and a number of dependent variables. From all of these dependent variables I would like to calculate mean, standard deviation and quantiles. With the function FUN I get all the means and stdev that I want but quantiles are only calculated for the first of the dependent variables (column 8 in the summarize command). What do I

Dear all, I am searching for a way to compute a test comparable to Chuang et al. ("Causality in Quantiles and Dynamic Stock Return-Volume Relations"). The aim of this test is to check wheter the coefficient of a quantile regression granger-causes Y in a quantile range. I have nearly computed everything but I am searching for an estimator of the density of the distribution at several

I'm not sure who is responsible for quantile(), but I assume they read this list. Ivan Frohne and I have produced a revision of the quantile.default() function which enables the computation of alternative sample quantile definitions. The code and .Rd file are attached. This enables the user to produce quantiles that are equivalent to those in various statistics package. There is a type

Hello, I have a set of data with two columns: "Target" and "Actual". A http://n4.nabble.com/file/n1584647/Sample_table.txt Sample_table.txt is attached but the data looks like this: Actual Target -0.125 0.016124906 0.135 0.120799865 ... ... ... ... I want to be able to break the data into tables based on quantiles in the "Target" column. I can see (using