search for: book2

It would be nice if the 00check.log file also included this part of the output: Running ?bladder.R? Comparing ?bladder.Rout? to ?bladder.Rout.save? ... OK Running ?book1.R? Comparing ?book1.Rout? to ?book1.Rout.save? ... OK Running ?book2.R? Comparing ?book2.Rout? to ?book2.Rout.save? ... OK etc. The survival package has enough test scripts that it exceeds my terminal's scroll bar; I have to either watch closely or run R CMD check survival >& mylog Terry Therneau

...d a pubrole_id foreign key. What I want to do is query the DB using AR so that I can get a list of all publications that belong_to a particular author, and group the results by the pubrole.role_name (Author, Joint Author, Editor, etc.) so that the results look something like: Author book1 info book2 info etc. Joint Author book1 info book2 info Editor etc. Can anyone suggest how to do this, or point to an example that already exists? Thanks. -- Posted via http://www.ruby-forum.com/.

I have a problem with ruby on rails validation total_book_toy.rhtml ================ <%= text_field ''book1'', ''title1'' %> <%= text_field ''book2'', ''title2'' %> I want to validate these text_field so user can''t insert same title. However, I was stuck how to do it. Or maybe you have another way how to do it. Any suggestion, please? Thank you so much. -------------- next part -------------- An HTML atta...

I'm new to R and some what new to the world of stats. I got frustrated with excel and found R. Enough of that already. I'm trying to test and correct for Heteroskedasticity I have data in a csv file that I load and store in a dataframe. > ds <- read.csv("book2.csv") > df <- data.frame(ds) I then preform a OLS regression: > lmfit <- lm(df$y~df$x) To test for Heteroskedasticity, I run the BPtest: > bptest(lmfit) studentized Breusch-Pagan test data: lmfit BP = 11.6768, df = 1, p-value = 0.0006329 From the above, if I...

R-helpers I have 120 small Excel sheets to read and I am using library(xlsReadWrite): one example below. I had hoped to read sheets by looping over a list of numbers in their name (eg Book1.xls, Book2.xls, etc). I thought I had seen examples which used eval-parse-paste in this way. However, I have not been able to get it to work.. 1. is this a feasible approach? 2. if not advice would be welcome. 3. Equally, advice about a better approach would also be v. welcome. I have...

...re seperated out into two tables: book_borrowers and movie_borrowers and therefore 2 different activerec objects: BookBorrower and MovieBorrower This particular screen will display something like this (plz excuse formatting): Name Has Borrowed ------- ------------------- Ron Book1, Book2, Movie4 Bob Book3 Tom Movie1 Paging seems quite simple if I would like to display either books or movies that you have borrowed in a table but I''m struggling a bit in paging over the combination. I''ve played with having a seperate object that combines the two (and i...

Dear all, Good day! I have a problem in reading Excel files in R and appending them to each other. Suppose we have several Excel files in a directory with headers and want to use R to append them in a single file with an additional variable in the final file indicating from which files the data come from. As I have many Excel files and their sizes are very big I should write a loop in R to do

...ot;, >> startRow = 1, startCol = 1) >> >> Hope this helps, >> >> Rui Barradas >> Em 18-08-2012 00:04, Amir Kasaeian escreveu: >>> Dear Rui, >>> >>> Thank you very much for your message. >>> Suppose we have 3 Excel files: Book1, Book2 and Book3 in a single directory. Please note the headers and their order. I need an output EXCEL file like Amir which includes all the information of the 3 Booki files. I think with the attached file I explain my problem. >>> As a matter of fact, I need to creat a new file named Amir which...

...the world of stats. I got >> frustrated with excel and found R. Enough of that already. >> >> I'm trying to test and correct for Heteroskedasticity >> >> I have data in a csv file that I load and store in a dataframe. >> >>> ds <- read.csv("book2.csv") >>> df <- data.frame(ds) >> >> I then preform a OLS regression: >> >>> lmfit <- lm(df$y~df$x) > > Just btw: lm(y ~ x, data = df) is somewhat easier to read and also > easier to write when the formula involves more regressors. > >&g...