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Hi All, In another thread Andy Liaw, who CRAN lists as locfit maintainer; said: <quote> From: "Liaw, Andy" <andy_liaw at merck.com> To: "Guy Green" <guygreen at netvigator.com>; <r-help at r-project.org> Subject: Re: Alternatives to linear regression with multiple variables Date: 22 February 2010 17:50 You can try the locfit package, which I believe can handle up to 5 variables. E.g., </quote> Looking in the locfit documentation (e.g....

Hello, First of all, I'm new to R and I don't have anyone who already knows the language to ask for tips, so please excuse my ignorance. I'm trying to download data direct from the Federal Reserve statistics website and graph it, using the following: #This downloads the data from the Fed website

Hello, Is there a command for freeing up the memory used by R in holding data tables? The structure of the procedure I have is as follows: 1) Read multiple txt files in using read.table(...). 2) Combine the read tables using rbind(...). 3) Attach the data using attach(...) and then use do a multiple regression using lm(...). So far so good, but when I then perform a further regression by

Hello, I am trying to create a graphic to help me visualise data. A (very simplified) sample of the data is http://n4.nabble.com/file/n1839676/circle_data.txt circle_data.txt : Aug-07 Nov-07 Feb-08 data1 1 1.5 -1 data2 1 1.2 1.6 data3 1.3 1.4 1.8 data4 1.3

Hello Everyone,   Learning about R and its wonderful array of functions. If it's not obvious, I usually try to find out what a function stands for. I think this helps me remember better.   One function that has me stumped is "sink." Can anyone tell me if this stands for something?   Thanks,   Paul         __________________________________________________ [[alternative HTML

Hello, I have been using read.table to read data files into R, then rbind to combine them into one table. The column headings are all identical, so it should be straightforward, and it seems to be working well so far. My question is: What is the maximum number of tables that can be combined with rbind? Is it driven by the number of rows in the tables, by a constraint with the syntax of rbind

Hello, I have been using a very simple rbind approach (simple enough for me to understand) to combine data files within R. It seems to work fine, but then generates warning messages for reasons that I can't begin to understand. The text below shows the issue. testread12=read.table("C:/Files/Test100.txt", head = T) testread11=read.table("C:/Files/Test101.txt", head =

Hello, I have a set of data with two columns: "Target" and "Actual". A http://n4.nabble.com/file/n1584647/Sample_table.txt Sample_table.txt is attached but the data looks like this: Actual Target -0.125 0.016124906 0.135 0.120799865 ... ... ... ... I want to be able to break the data into tables based on quantiles in the "Target" column. I can see (using

I have a simple table of data: Result Var1 Var2 Var3 1 0.10 0.78 0.12 0.38 2 0.20 0.66 0.39 0.12 3 0.10 0.83 0.09 0.52 4 0.15 0.41 0.63 0.95 5 0.60 0.88 0.91 0.86 6 -0.02 0.14 0.69 0.94 I am trying to achieve two things: 1) Manipulate this data so that I have the "Result" data unchanged, and all the other data

I'm sure this is a really simple problem, but I've spent hours digging and I keep running into roadblocks. I'm trying to get a simple chart with three time series. Similar to the attached example http://www.nabble.com/file/p25398419/Excel%2Bchart%2Bexample.pdf Excel+chart+example.pdf , something that was quite easy to do in Excel, except that I need a log y-axis: something that R

I wonder if someone can give some pointers on alternatives to linear regression (e.g. Loess) when dealing with multiple variables. Taking any simple table with three variables, you can very easily get the intercept and coefficients with: summary(lm(read_table)) For obvious reasons, the coefficients in a multiple regression are quite different from what you get if you calculate regressions for

Hello, I have been having difficulty getting boxplot to give the output I want - probably a result of the way I have been handling the data. The data is arranged in columns: each date has two sets of data. The number of data points varies with the date, so each column is of different length. I want to get a series of boxplots with the date along the x-axis, with alternating colors, so that it