search for: jdrapp

I have a vector containing players' weights. When I enter mode(data.linear$Weight) "numeric" is returned. When I type mean(data.linear$Weight) NA is returned. Any ideas as to why this may be the case? I am trying to calculate this ultimately so I can superimpose a normal density line over a histogram containing the weights?

On the cover of Zivot and Wang's Modeling Financial Time Series with S Plus, there is a correlation plot that seems to indicate the strength of correlation with color-coded squares, so that more highly correlated stocks appear darker red. If anybody out there is familiar with the book or understands what I am talking about, I am curious as to whether or not there is a similar function in R

This seems like a question that I should be able to answer on my own but after looking at the documentation I cannot seem to find the correct method. How do I add lines to a bar plot that extend from the vertical axis? For example, my vertical axis is numbered in increments of 10 and I would like these to go across the whole graph. Also, is there a way to have R label the value of each bar so

...t is technically correct to say the "mean value of the linear predictor," instead of "mean response". 20 lashes for me. Max -----Original Message----- From: Kuhn, Max Sent: Friday, July 07, 2006 4:11 PM To: 'r-help at stat.math.ethz.ch' Subject: [R] Levels and GLM jdrapp, By default, R fits full rank models. If you are coming from SAS, you're probably used to less than full rank model parameterizations. >From Section 11.1.1 of "An Introduction to R" at http://cran.r-project.org/doc/manuals/R-intro.html#Contrasts there is this: "What ab...

I am using the as.factor command to use with glm. When I use the command >maj <- as.factor(data.logistic$Majors) >maj I receive the following output: [1] M M N M M M M N N M M M N M M M M M M M M M M M N M N N M M N M M N M M M M M [40] N M N M M N M M M N M N M N M N N N M N M M M M M M N M N M M M M M N N M M M [79] M M M N N M M N M N M M M M M M M M M M M M M M M N M M M M M N

I apologize for my constant questions but I am new to R and trying to gain an appreciation for its capabilities. The following task is easy in Excel and I was hoping somebody could give me a quick explanation for how it can be acheived in R so I can avoid having to switch between the two applications. How do I find the Summary Statistics in one Vector of the dataframe by levels in another of the

All, Happy World Cup and Wimbledon. This morning finds me with the first of my many daily questions. I am running a ks.test on residuals obtained from a regression model. I use this code: > ks.test(Year5.lm$residuals,pnorm) and obtain this output One-sample Kolmogorov-Smirnov test data: Year5.lm$residuals D = 0.7196, p-value < 2.2e-16 alternative hypothesis: two.sided Warning