search for: mypred

Dear R-help, I managed (thanks to the R2PPT package) to create a PowerPoint presentation and create a table in it but for the life of me I can't find a way to populate the table with values and text. I'm aware of the function 'PPT.AddDataFrame' which creates an Excel object from a data frame, but the excel object is not nearly as nice looking and easy to manipulate (and apply

Hi all, When using the package R2PPT I am able to create a presentation, add slides, add title, add text. But when it comes to insert data.frame with the function PPT.AddDataFrame the result is everything but nice. I may need to define the data.frame in some way that power point interprets it better, but not even the example works for me: ctl <-

Hola tengo q hacer un trabajo, donde me piden q todas las salidas q haga sean en Power Point (graficos, tablas, etc). Para eso habia empezado a leer algo del paquete R2PPT, pero la verdad es q hay cosas q no entiendo de este paquete. Queria saber si alguien estuvo trabajando con el y obtuvo buenos resultados o si han usado otro paquete para hacerlo. Por ultimo una pregunta: desde Sweave se

...a, panel = function(x,y) { panel.xyplot(x, y) panel.superpose(???) # Needs more here } ) I also like to plot on each panel (there is one Subj per panel) a continuous curve with predictions that I can calculate from a rather complicated function: myPred <- (time, subj, dose) { returns predicted value of Conc for a given time, subj and dose } The predicted curves are different for each panel. How do I plot the predictions? I have tried to add panel.superinpose in the xyplot portion but can't link to the myPred function. I also know...

...ining data is sampled randomly from the complete data set. The "copy-pasted" code below illustrates: > data <- load.data() > mytree <- run.tree(data) > mypred <- gen.predictions(mytree, data ) Error in pred1.tree(object, tree.matrix(newdata)) : corrupt tree...

...#fit some linear model to random data x=matrix(rnorm(100*3),100,3) y=sample(1:2,100,replace=TRUE) mydata <- data.frame(y,x) mymodel <- lm(y ~ ns(X1, df=3) + X2 + X3, data=mydata) summary(mymodel) #create new data with 1 missing input mynewdata <- data.frame(matrix(rnorm(100*2),100,2)) mypred <- predict(mymodel, mynewdata) Thanks in advance for your help! Axel. [[alternative HTML version deleted]]

Hi, I created a logistic regression model using the glmnet package. This model is of class "glmnet" or "lognet". I wanted to plot a calibration curve for this model using the calibrate() function from rms package, but the objects used are different, rms requires a fit from lrm(). Is there another function for getting the calibration plot for this glmnet object, or can anyone

Could you just use lines(newX, myPred, col=2) -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Paul Johnson Sent: Thursday, September 23, 2004 10:3 AM To: r help Subject: followup: Re: [R] Issue with predict() for glm models I have a follow up question that...