similar to: Summary.Formula: prmsd and test statistic

Un texte encapsul? et encod? dans un jeu de caract?res inconnu a ?t? nettoy?... Nom : non disponible URL : <https://stat.ethz.ch/pipermail/r-help/attachments/20080725/bcafe250/attachment.pl>

Hello R-gurus, I'm trying to adjust different growth curves to a rather extensive dataset. I wrote up a function to go through all of them, but am encountering a problem : among the more than 1000 curves I have, obviously for some of them I encounter conversion problems. I'd like for my function to keep going to the next curve and store the fact that for curve number X I had a convergence

Hi, I'm fitting a standard nonlinear model to the luminances measured from the red, green and blue guns of a TV display, using nls. The call is: dd.nls <- nls(Lum ~ Blev + beta[Gun] * GL^gamm, data = dd, start = st) where st was initally estimated using optim() st $Blev [1] -0.06551802 $beta [1] 1.509686e-05 4.555250e-05 7.322720e-06 $gamm [1] 2.511870 This works fine but I

Dear all, I did post this more or less identical mail in a follow up to another question I posted, but under another heading. I try again, but now under the correct header. upon running this code (from the Hmisc library-latex function) I believe the call to summary.formula is allright and produces wonderful tables, but the latex command results in a correct formatted table but where all the

Dear R Support Team, I am experiencing an issue with my R package during the `R CMD check` process. A non-standard file named `vert.txt` is being generated in the check directory, causing a NOTE in the check results. Despite adding `vert.txt` to `.Rbuildignore`, the file is still appearing. And, there are no commands in any part of my package's code that would generate this file. Here

I'm hoping someone with some experience generating tables in Sweave will be able to solve this problem for me. I'm experiencing some inconsistency with the way floating point numbers are displayed -- for some tables, they will be in standard notation, e.g. 11±26 while in others, it uses exponential notation, e.g. 1.1e+01±2.6e+01 I am using code such as the following; note I have

On Sun, 2015-05-24 at 19:58 +0200, Tobias Klausmann wrote: > Signed-off-by: Tobias Klausmann <tobias.johannes.klausmann at mni.thm.de> > --- > src/glsl/ast_to_hir.cpp | 14 +++++ > src/glsl/builtin_variables.cpp | 13 +++- > src/glsl/glcpp/glcpp-parse.y | 3 + > src/glsl/glsl_parser_extras.cpp | 1 + > src/glsl/glsl_parser_extras.h

Here is a potential wishlist item for adding an argument (asp) to symbols(). The following code produces a postscript file with two pages; both should show a circle of radius 2 units. Horizonal and vertical arrows are drawn to check that the circle is of the correct radius; in the first plot, the circle is wrong. To fix this, I found that I needed to first set up the plot bounds, using xlim,

Hallo! Can anyone explain to me how to add a vert. scrollbar to a listbox using tcltk please? Thanks -- Frank Gerrit Zoellner -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject

Dear r-help mailing list, Is there a way to incorporate weights into the minsplit criteria in rpart, when the weights are uneven? I could not find a way for the minsplit threshold to take the weights into account, and when the weights are uneven it becomes an issue, as the following example shows. My current workaround is to expand the data into one in which each row is an observation, but that

Greetings R world, I know some version of the this question has been asked before, but i need to save the output of a loop into a data frame to eventually be written to a postgres data base with dbWriteTable. Some background. I have developed classifications models to help identify problem accounts. The logic is this, if the model classifies the record as including variable X and it turns out

Hi, I have a technical question about rpart: according to Breiman et al. 1984, different costs for misclassification in CART can be modelled either by means of modifying the loss matrix or by means of using different prior probabilities for the classes, which again should have the same effect as using different weights for the response classes. What I tried was this: library(rpart)

Hi all, I have to draw a map of microorganisms repartition in a sample. I use the "image" function of geoR package to build the map but there are three problems: 1) the legend is Horizontal (with or without vert.leg=TRUE) 2) I want to plot the position of organisms and level curves of density on the map but I don't find the script to insert these data on the map. 3)the grey range

Here's a quick patch to have either horz or vert (instead of both) maximized windows honor the "ignore" option: --- src/window.c +++ src/window.c @@ -4012,7 +4012,7 @@ constrainNewWindowSize (CompWindow *w, if (d->opt[COMP_DISPLAY_OPTION_IGNORE_HINTS_WHEN_MAXIMIZED].value.b) { - if ((w->state & MAXIMIZE_STATE) == MAXIMIZE_STATE) + if (w->state

Hello all, I wish to extract the terms from an rpart object. Specifically, I would like to be able to know what is the response variable (so I could do some manipulation on it). But in general, such a method for rpart will also need to handle a "." case (see fit2) Here are two simple examples: fit1 <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis) fit1$call fit2 <-

Hi, I am writing to seek some guidance regarding using Lasso regression with the R package LARS. I have introductory statistics background but I am trying to learn more. Right now I am trying to duplicate the results in a paper for shRNA prediction "An accurate and interpretable model for siRNA efficacy prediction, Jean-Philippe Vert et. al, Bioinformatics" for a Bioinformatics project

Greetings All, I am looking to write a parametrized Rscript that will accept a variable name(that also is the name of the flat file), transform the data into a data frame and preform various modeling on the structure and save the output and plot of the model. In this example i am using a rpart decision tree. The only problem i am having is integrating the parameter into the internal object name

I run the following code: library(rpart) data(kyphosis) fit <- rpart(Kyphosis ~ ., data=kyphosis) plot(fit) text(fit, use.n=TRUE) The text labels represent the count of each class at the leaf node. Unfortunately, the numbers are rounded and in scientific notation rather than the exact number of examples sorted by that node in each class. The plot is supposed to look like

https://bugs.freedesktop.org/show_bug.cgi?id=97192 Bug ID: 97192 Summary: SuperTuxkart graphic errors [NVE4 - GK104] Product: Mesa Version: unspecified Hardware: x86-64 (AMD64) OS: other Status: NEW Severity: normal Priority: medium Component: Drivers/DRI/nouveau Assignee:

Dear R-users I am using RPART package to get regression trees. However having trouble getting the text function to put the full splitting rule number on the plot, instead to puts it in scientific notation. When a covariate has 1e4 or greater number of digits then the splitting rule number displayed on the plot is in scientific notation. But print.rpart displays the splitting rules in full.