search for: modelmatrix

Hello everybody, I'm trying to predict a linear regression model but it does not work. My Model: y = Worktime + Vacation + Illnes + Bankholidays My modelmatrix is of dimension 28x4 Then I want to make use of the function predict because there confidence.intervals are include. My idea was: mod <- lm(y~Worktime+Vacation+Illnes+Bankholidays) newdate=data.frame(x=c(324,123,0.9,0.1)) predict(y,newdate) But I always get the message: 'newdata'...

..."Too much damping - convergence tolerance not achievable" (as you also can see in the program posted below). What does it mean? Is there anything wrong with my data? Question 3: How to construct the design matrix is a puzzle to me. Here I constructed the design matrix using the function modelMatrix and the object targets. However, I am not sure whether it is constructed appropriately. Looking forward to your suggestions. (Additional info about my experimental design. Uppercase and lowercase words in the R object targets (see below in the posted program) have different meanings. The locusts on...

...equest for confirmation ... I do think a couple of extra sentences of explication in the documentation for dummies like me wouldn't hurt, I would be happy to submit a documentation patch if that seems worthwhile.) - -------- I've tried looking through model.matrix.default and through the modelmatrix function in src/library/stats/src/model.c , but it's pretty hairy ... Related discussion: http://stackoverflow.com/questions/5616210/model-matrix-with-na-action-null http://stackoverflow.com/questions/6447708/model-matrix-generates-fewer-rows-than-original-data-frame https://stat.ethz.ch/...

Hi, I have a question about limma. I have data from spotted arrays. I have class A and Class B on the same slide. In Limma if I put class A as the reference (ref), are the list of genes I get in the output for class A or class B? #design <- modelMatrix(targets, ref="classA") design Josephine Brennan [[alternative HTML version deleted]]

...*************************************** > targets SlideNumber FileName Cy3 Cy5 ml12med 12 ml12med.spot CD4 CD8 ml13med 13 ml13med.spot CD8 CD4 ml14med 14 ml14med.spot DN CD8 ml15med 15 ml15med.spot CD8 DN ml16med 16 ml16med.spot CD4 DN ml17med 17 ml17med.spot DN CD4 > design <- modelMatrix(targets, ref="CD4") Found unique target names: CD4 CD8 DN > design CD8 DN ml12med 1 0 ml13med -1 0 ml14med 1 -1 ml15med -1 1 ml16med 0 1 ml17med 0 -1 > fit <- lmFit(MA, design, ndups=2) > contrast.matrix <- cbind("CD8-CD4"=c(1,0),"DN-CD4&...

...r = 00 both are named var00. Additionally, if a level of a factor variable contains a colon, this could be confused for an interaction. While a human can generally work out the meaning of each column somewhat manually, I am interested in achieving this programmatically. My solution is to edit the modelmatrix function in /src/library/stats/src/model.c to additionally return the following: intrcept factors contr1 contr2 count With the availability of these in R it is possible to determine the precise meaning of each column without the error-prone parsing of strings. I have attached my edit: see lines 7...