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Good morning, dear listers I am wondering if you could recommend a good tutorial / book for r scripting. thank you so much in advance! WenSui Liu Credit Risk Manager, 53 Bancorp wensui.liu at 53.com 513-295-4370

Good morning, dear listers I am wondering how to do string evaluation such that model <- glm(Y ~ [STRING], data = mydata) where STRING <- "x1 + x2 + x3" It is very doable in other language such as SAS. Thank you so much for your insight!

Hi all, does anyone know why the area under the curve (AUC) is negative? I'm using ROC function with a logistic regression, package Epi. First time it happens... Thanks a lot! Bruno -- View this message in context: http://r.789695.n4.nabble.com/ROC-Curve-negative-AUC-tp4650469.html Sent from the R help mailing list archive at Nabble.com.

Dear All, I am using randomForest to predict the final selling price of some items. As it often happens, I have a lot of (noisy) historical data, but the question is not so much about data cleaning. The dataset for which I need to carry out some predictions are fairly recent sales or even some sales that will took place in the near future. As a consequence, historical data should be somehow

Hi, Does anyone know of a function in R that can handle a fractional variable as the dependent variable? The catch is that the function has to be inclusive of 0 and 1, which betareg() does not. It seems like GLM might be able to handle the fractional logit model, but I can't figure it out. How do you format GLM to do so? Best, Rachael [[alternative HTML version deleted]]

I would like to test in R what regression fits my data best. My dependent variable is a count, and has a lot of zeros. And I would need some help to determine what model and family to use (poisson or quasipoisson, or zero-inflated poisson regression), and how to test the assumptions. 1) Poisson Regression: as far as I understand, the strong assumption is that dependent variable mean = variance.

Hi, I need to aggregate rows of a data.frame by computing the mean for rows with the same factor-level on one factor-variable; here is the sample code: x <- data.frame(rep(letters,2), rnorm(52), rnorm(52), rnorm(52)) aggregate(x, list(x[,1]), mean) Now my problem is, that the actual data-set is much bigger (120 rows and approximately 100.000 columns) ? and it takes very very long