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Hello, I am trying to do some fairly straightforward data summarization, i.e., the kind you would do with a pivot table in excel or by using SQL queires. I have a moderately sized data set of ~70,000 records and I am trying to compute some group averages and sum values within groups. the code example below shows how I am trying to go about doing this pti <-rnorm(70000,10) fid <-

Are there any packages in R that are suitable for doing time series forecasting using neural networks? I have looked in the nnet package and neural package and they both seem geared towards classification. thanks, Spencer [[alternative HTML version deleted]]

Hello, I am trying to identify values that fall within a certain range. I thought that I might be able to use the which function to do this but I have been unable to figure out a way to do it. Perhaps a little code will illustrate what i am trying to do. a <- rnorm(1000, 100, 50) which( 100 < a <= 200) of course this doesn't work but illustrates what I ma trying to do, If anyone

I am working with a dataset where there are 5 possible outcomes (coded 1:5), I would like to create 5 categorical variables (event1...event5). I am using a for loop an if statements, but I have a large dataset( approx 100,000 rows) it takes quite a bit of time, is there a way to speed this up? Here is some sample code of what I am currently doing. test2 <-rep(seq(1:5),2000) event1 <-

I am using R 2.3.0, Is there a way to get prediction intervals using predict.gls? Any ideas would be appreciated. thanks, Spencer On 11/2/06, Frank McCown <fmccown@cs.odu.edu> wrote: > > I was wondering if anyone knows who should be contacted to add to the R > user-contributed documentation at > > http://www.r-project.org/other-docs.html > > There doesn't

I have been trying to use the ets function in the forecast package on a daily time series (ts2 is a ts object with frequency =7). However when I run the following code I get an error related to etsmodel. I have looked at ets and I can see that there is a call to the function etsmodel, but I cant seem to find info on the ets function anywhere. Does anyone know anything about the etsmodel function?

Hello, I would like to look at the compiled C code behind HoltWinters from the stats package. Is that possible? If so where do I find it? thanks, Spencer [[alternative HTML version deleted]]

I have a set of values and their corresponding weights. I can use the function weighted.mean to calculate the weighted mean, I would like to be able to similarly calculate the weighted median and quantiles? Is there a function in R that can do this? thanks, Spencer [[alternative HTML version deleted]]

Hello, I am using glmer() from lmer(lme4) to run generalized linear mixed models. I can't figure out how to extract the z values for the fixed effects that are reported using the summary function . Any help would be appreciated. Thanks, Spencer [[alternative HTML version deleted]]

I am working with a large data set of arrivals, for each day I have aggregated the arrivals into hrs (1-24) via: apply(x,2,table). On some days there are zero arrivals during some hours of the day, this leaves me with (I believe) a list of vectors of differnt lengths (see below). [[4]] 1 2 3 5 6 8 9 10 11 13 14 15 16 17 18 19 20 21 22 23 24 1 3 2 3 1 1 2 3 4 4 4 3 2 6

hello, I have a question about making n step ahead forecasts in cases where test and validation sets are availiable. For instance, I would like to make one step ahead forecasts on the WWWusage data so I hold out the last 10 observations as the validation set and fit an ARIMA model on the first 90 observations. I then use a for loop to sequentially add 9 of the holdout observations to make 1

I am using arima to develop a time series regression model, I am using arima b/c I have autocorrelated errors. Several of my independent variables are categorical and I have coded them as factors . When I run ARIMA I don't get any warning or error message, but I do not seem to get estimates for all the levels of the factor. Can/how does ARIMA handle factors in xreg? here is some example

I am fitting a regression model with a bs term and then making predictions based on the model. According to some info on the internet at http://www.stat.auckland.ac.nz/~yee/smartpred/DummiesGuide.txt there are some problems with using predict.lm when you have a model with terms such as bs,ns,or poly. However when I used one of the examples they said would illustrate the problems I get virtually

I have an array with 44800 columns and 24 rows I would like to compute the row average for the array 100 columns at a time, so I would like to end up with an array of 24 rows x 448 columns. I have tried using apply(dataset, 1, function(x) mean(x[])), but I am not sure how to get it to take the average 100 columns at a time. Any ideas would be welcomed. thanks, Spencer [[alternative HTML

All, I am working with a large data set (~ 450,000 rows by 34 columns) I am trying to fit a regression model (I have tried to use several procedures psm (Design package) lm, glm). However whenever I try to fit the model I get the following error: Error: cannot allocate vector of size 1.1 Gb Here are the specs of the machine and version of R I am using Windows Server 2003 R2 Enterprise x64

I have a set of timestamp data that I have in a text file that I would like to import into R for analysis. The timestamps are formated as follows: DT_1,DT_2 [2006/08/10 21:12:14 ],[2006/08/10 21:54:00 ] [2006/08/10 20:42:00 ],[2006/08/10 22:48:00 ] [2006/08/10 20:58:00 ],[2006/08/10 21:39:00 ] [2006/08/04 12:15:24 ],[2006/08/04 12:20:00 ] [2006/08/04 12:02:00 ],[2006/08/04 14:20:00 ] I can get

...Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > > > > ------------------------------ > > Message: 27 > Date: Tue, 1 May 2007 10:07:38 -0600 > From: sj <ssj1364@gmail.com> > Subject: [R] linout=TRUE in nnet package ? > To: r-help <r-help@stat.math.ethz.ch> > Message-ID: > <1c6126db0705010907rfba9d00n22ac108e0c697917@mail.gmail.com> > Content-Type: text/plain > > Hello, > > I am trying to figure out what nnet...

I am fitting a negative binomial regression model to some count data. I chose the negative binomial b/c the variance is greater than the mean. Anyways, when I fit the model I get the following warning: "Warning while fitting theta: alternation limit reached" The estimate that I end up with is very large (1070), and the standard error is even larger (1276). Does this indicate that I

I am using rexp to generate several exponential distributions. I am passing rexp a vector of rates , r. I am wanting to simulate a sample of size 200 for each rate so the code looks like: rexp(n=200*length(r),rate=r) this gives me a vector of the random exponential variables, but they are all disjointed b/c rexp goes through and simulates an exponential variable for each rate and it does that 200

hello, I am using arima to evaluate a time series regression model. I am using categorical variables such as day of week(Su-Sa), month(Jan-Dec), and holiday status (1/0) as my independent variables. There is evidence of multiplicative interaction between holiday status and weekday and I would like to add an interaction term to my arima model, but I am not sure about best way to go about doing it.