similar to: check.k function in mgcv packages

Hello all, I'm very satisfied to say that my grip on both R and statistics is showing the first hints of firmness, on a very greenhorn level. I'm faced with a problem that I intend to analyze using ANOVA, and to test my understanding of a primitive, one-way ANOVA I've written the self-contained practice script below. It works as expected. But here's my question: How can I not

Hi, I have a question concerning the analysis of some affymetrix chips. I downloaded some of the data from GEO GSE11324 (see below). In doing so I'm stuck after I identified the probesets with significant changes. I have problems in assigning probeset specific gene names as well as getting the genomic coordinates. Furthermore I have no clue how to deal with the fact, that most genes have

I have a list of measurements taken at 1 second samples in a vector (y). All I want to do is generate a regression through them, and obtain the residuals in another vector. I am currently using the 'line' function from the eda package to do this (ie : z <- line(time,y) rsd <- residuals(z) ) but this method does not handle NA values in the data. I would like to try to use the lm

Hello, 1.1pre17 does not support Windows XP.  The reason is that InitOnceExecuteOnce is not supported. I believe it is better to take the Windows XP name out of the download link. -rsd -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://www.tinc-vpn.org/pipermail/tinc/attachments/20190708/b68071ed/attachment.html> -------------- next part

Hello, A nice guy call Jun Shen was helping me out with this, but I require a bit more help. Below is my data set or list called 'test'. I'm trying to calculate the %RSD for each pair of index and keep it in cronological order if you can imagine a 3rd column with 'date' beside index. Result Index 1 0.2901 17 2 0.2928 17 3 0.2913 18 4 0.2893 18 5

Hi, I'm trying to use Robust non-linear regression to fit dose response curves. Maybe I didnt look good enough, but I dind't find robust methods for NON linear regression implemented in R. A method that looked good to me but is unfortunately not (yet) implemented in R is described in http://www.graphpad.com/articles/RobustNonlinearRegression_files/frame.htm

Dear community, I encountered a very disturbing phenomenon today: When I try to fit any gam() with mgcv R aborts. I could not find any post regarding this in google, which mades in even more strange. I am using the latest Ubuntu, latest R and latest mgcv everything up to date. The crash occured too with the last mgcv 1.7-11. This is the output from the R shell: <pre> R version 2.14.0

Hi everyone, I can't figure out how to extract by-factor random effect adjustments from a gam model (mgcv package). Example (from ?gam.vcomp): library(mgcv) set.seed(3) dat <- gamSim(1,n=400,dist="normal",scale=2) a <- factor(sample(1:10,400,replace=TRUE)) b <- factor(sample(1:7,400,replace=TRUE)) Xa <- model.matrix(~a-1) ## random main effects Xb <-

I'm probably not using the function right, but anyway, the program said: "please bug.report." > w_R.f1=function(PR,Pc) return (Pc*PR^3) > > w_R.f2=function(PR,Pc) return (Pc*PR) > > w_R.fc=c(w_R.f1,w_R.f2) > w_R.fc[2] [[1]] function(PR,Pc) return (Pc*PR) > > RSD(type=3, + gparP=gpar(col="red"), + gparD=gpar(fill=FALSE,col=FALSE), +

Hello all, I use arima to fit the model with fit <- arima(y, order = c(1,0,1), xreg = list.indep, include.mean = TRUE) and would like to use predict() to forecast: chn.forecast <- rep(0,times=num.record) chn.forecast[1] <- y[1] for (j in 2:num.record){ indep <- c(aa=chn.forecast[j-1], list.indep[j,2:num.indep]) # this is the newxreg in the

Hello,guys: Recently, I am working on a seasonal ARIMA model. And I met some problem in the forecasting. Now I just want to know that How does R perform the predict procedure(the predict formula, the initial setting of errors,etc.)? I run the following commands and get the original code of the "predict" command, but I can't read it. Can anybody explain it to me? Thanks! saji from

Dear List, I'm getting an error in mgcv, and I can't figure out where it comes from. The setup is the following: I've got a fitted GAM object called "MI", and a vector of "prediction data" (with default values for predictors). I feed this into predict.gam(object, newdata = whatever) via the following function: makepred = function(varstochange,val){ for

Dear list, does anybody know whether there is a way to easily retrieve the so called "partial residuals" of a gam fit with package mgcv? The partial residuals are the residuals you would get if you would "leave out" a particular predictor and are the dots in the plots created by plot(gam.object,residuals=TRUE) residuals.gam() gives me whole model residuals and

Dear users, I am trying to show the equation (including coefficients from the model estimates) for a gam model but do not understand how to. Slide 7 from one of the authors presentations (gam-theory.pdf URL: http://people.bath.ac.uk/sw283/mgcv/) shows a general equation log{E(yi )} = ?+ ?xi + f (zi ) . What I would like to do is put my model coefficients and present the equation used. I am an

When I run predict.Arima in my code, I get warnings like: Warning message: In cbind(intercept = rep(1, n), xreg) : number of rows of result is not a multiple of vector length (arg 1) I think this is because I'm not running predict.Arima in the same environment that I did the fit, so the data object used in the fit is no longer present. Looking at the predict.Arima source,

Hi all, Forecasting from an arima model is easy with predict. But I can't manage to backcast : invent data from the model before the begining of the sample. The theory is easy : take your parameters, reverse your data, forecast, and then reverse the forecast I've tried to adapt the predict function to do that (i'm not sure that the statistical procedure is fine (with the residuals),

Dear All, I would like to extract the smoothing matrix of the fitted GAM, \hat{y} = Sy. I can't seem to find the function or am I missing something? Thanks, any help is greatly appreciated Man Zhang [[alternative HTML version deleted]]

Dear R-Users, Dr. Wood replied to a similar topic before where confidence intervals were for a ratio of two treatments ( https://stat.ethz.ch/pipermail/r-help/2011-June/282190.html). But my question is more complicated than that one. In my case, log(E(y)) = s(x) where y is a smooth function of x. What I want is the confidence interval of a ratio of log[(E(y2))/E(y1)] given two fixed x values of

I'm in the process of installing OpenSSH-2.5.1p1 on a cluster of machines. One of the aspects of a previous (non-OpenSSH) version of ssh that I had been using was its ability to tolerate soft links to it. Thus, one could set up # ln -s /usr/bin/ssh /usr/local/bin/machine and thereafter type just 'machine' to connect to that host. This version of OpenSSH doesn't appear to

Hi, Tinc experts There’s a requirement, where A connect to B, B connect to C; where B knows all the subnets from A and C, but A wouldn’t need to know anything about C, and C wouldn’t need to know anything about A. Any tinc configuration can make this happen? You can think of B is not an interconnect/forwarding node, instead, it only connect to A and C separately. I can think of run two tinc