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...tead of nrow(x) in calculating Cp and adjusted R-squared strictly.compatible Implement misfeatures of leaps() in S -- Kate Cleary MS Candidate Department of Fish, Wildlife, and Conservation Biology Colorado State University Fort Collins, CO 970-491-3535 Links: ------ [1] https://webmail.warnercnr.colostate.edu/leaps/help/regsubsets [[alternative HTML version deleted]]

Hello, helpeRs, I've been trying, unsuccessfully, to change a dataframe from long to wide format using reshape (the original). I would appreciate it if someone could demonstrate the correct syntax. The script below will create a toy example. The new wide data should have a column name for each unique entry in the "fame" column. Under each column should be either the

I ran logistic regression models last week using glm (...,family=binomial) and got a set of results. Since then I have loaded the Epi package for ROC analysis. Now when I run those same models I get completely different results, with most being: Warning message: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart,

Dear HelpeRs: I have a data set in the following format, which will be familiar to those of you working with NCDC climate data. Example: Year <- rep(1:3, each = 3) Year <- c(Year,Year) ID <- rep(1:2, each = 9) Jan <- runif(18, min = 0, max = 20) Feb <- runif(18, min = 0, max = 20) Mar <- runif(18, min = 0, max = 20) var <- gl(3,1,18,label =

Dear helpeRs, I have a dataframe (14947 x 27) containing measurements collected every 5 seconds at several different sampling locations. If one measurement at a given location is less than zero on a given day, I would like to delete all measurements from that location on that day. Here is a toy example: toy <- data.frame(CH = rep(3:5,3), DAY = c(rep(4,5), rep(5,4)), SLOPE =

Hello List, I was wondering if a package or piece of code exists that will allow all possible subsets regression model selection within program R. I have already looked at step(AIC) which does not test differing combinations of variables within a model as far as I can tell. In addition I tried to use the leaps command, but that does not use the criterion I am looking for. Any help or advice

I am interested in estimating the variance components from different groups of variables in a linear regression. For example, I want to model dependent variable ?Y? based on six covariates as follows: (these are land use types measured at three scales for each Y, "Local", "Riparian", and "Catchment" - these are not nested as there is a unique area for each Y -

Here are the specifications from Excel 2010. There are others for older versions of Excel so you may need to do a search specific to your application. http://office.microsoft.com/en-us/excel-help/excel-specifications-and-limits-HP010342495.aspx?CTT=5&origin=HP005199291 You should be OK looking at these specs. However, in my experience Excel is a resource hog and this doesn't rule out

Dear R helpers, I have a dataframe (test1) containing the time of sunrise and sunset for each day of the year for 3 years. I have another dataframe (test2) containing measurements that are taken every 15 minutes, 24/7. I would like to extract all rows from test2 that occur between sunrise and sunset for the appropriate date. Can you suggest a good vectorized way to do this? Keep in mind

Hello, helpeRs, I have a vector of numbers from 1-365 (days of the year) that I would like to convert to a date. There are no NA's and no missing values. I did not insert leading zero's for numbers less than 100. Using the syntax: dat$doy.1 <- as.numeric(format(dat$doy, "%j" )) I get the following error message: Error in prettyNum(.Internal(format(x, trim, digits,

Dear helpeRs, I am attempting to read in a series of csv files so I can bind them into one large dataframe. I have written the following script: test <- list.files(".", pattern = "csv") #lline 1 imp <- list() #line 2 for (i in 1:length(test)) { #line 3 imp[i] <- read.csv(test[i]) #line 4 }