similar to: how to deal with singularities in lm()

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I would like to code a script which processess all possible combinations of matrix columns. The purpose of such operation is to automatically find best combination of factors (not those factors in mean of R, but explaining factors -- independent variables) received from lm(). The independent variables are present in columns of the matrix. I am not a

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I need to count the covariance of two time series. Both of them contain the dates' vector and vector of values. But the dates are not the same. It means some dates of first ts are not in the second respectively. And I need the covariance of same dates, of course. Could anyone help me, please? Thank you. lukas - -- Lukas Kubin lukas.kubin at

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a stock market trading values time series. What's the best way to extract the "last day of month" values. I looked at function window() but doesn't appear suitable for this since it expects regular dates. Thank you. lukas - -- Lukas Kubin lukas.kubin at permonik.com phone: 00420603836180 -----BEGIN PGP SIGNATURE-----

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Is it possible to create a time series from existing data frame? One column of that frame contains dates (like "01/01/01") and the second one the values. The period is non-regular (it is not strictly daily nor working-days-daily). Thank you. lukas - -- Lukas Kubin lukas.kubin at permonik.com phone: 00420603836180 -----BEGIN PGP

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 What are the best tools (models within R) for use in predicting stock market trading values? Currently I'm using the smooth.spline but are there any others used in practice? Do I find the mathematical formulations of R-functions somewhere (I now I could deduct it from the source code algorithms but ...)? Of the smooth.spline() for example? Thank

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I need to read in a dataframe stored in a cvs file. The problem is I don't know how to tell R the first column (in format like "7-Jan-80") is a vector of dates. Could you help me, please? Thanks. lukas - -- Lukas Kubin lukas.kubin at permonik.com phone: 00420603836180 -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.0.5 (GNU/Linux)

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I wish to use rsync to synchronize a whole fat32 (MSWindows) partition mounted into a linux system. I run rsync from linux. The problem is rsync synchronizes most of the data even if the data hasn't changed since the original image was made. I used the -avz parameters to do the backup and the same for restoration. Also I've tried just -rvz. It

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm getting the rsync error "partial transfer (code 23) at main.c(925)" when restoring a 'rsync-ed' Windows partition from a Linux system. I feel the problem might be caused by the characterset (win-1250) which the files on Windows partition are stored in. Is there any solution to this? Thank you lukas - -- Lukas Kubin phone:

As a true R-Newbie, I thought I would respond to Zed Shaw's ideas. I think they're all good. I've put comments re the ones which would be critical for me >>>1) An R Cookbook section of the site where people can submit pieces >>>of interesting code that satisfies a need. This would be similar to the >>>Perl/Python/Java Cookbook texts that O'Reilly

Hi, Pine user should read the following advisory. I have not checked it because I don't use Pine. Werner -- Omnis enim res, quae dando non deficit, dum habetur et non datur, nondum habetur, quomodo habenda est. -- Augustinus -------------- next part -------------- An embedded message was scrubbed... From: "V. Alex Brennen"

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, folks - has anyone experienced this on Red Hat 7.2? Same results with 2.2.1a and 2.2.2. Compiling smbd/server.c In file included from /usr/include/linux/vfs.h:4, from /usr/include/linux/fs.h:14, from /usr/include/linux/capability.h:17, from /usr/include/sys/capability.h:24,

[ Sorry, I did not see the renamed thread until I'd already replied on the old one. Calling this a phishing attack is exactly right. ] On 2010-01-30, Joachim Schipper wrote: > If I understand you correctly, you argue that connecting to malicious > hosts is currently secure, and will remain secure, but that it will > become easier to convince people to send the passphrase for

Hello, I want to specify a linear regression model in which the metric outcome is predicted by two factors and their interaction. glm() computes effects for each factor level and the levels of the interaction. In the case of singularities glm() displays "NA" for the corresponding coefficients. However, svyglm() aborts with an error message. Is there a possibility that svyglm()

Hello, I'm doing an lm(y1~x1), no NAs in them, both of length 283. I get out however and 'NA' for the estimate of x1 and summary gives: Residuals: Min 1Q Median 3Q Max -0.1998309 -0.0447269 -0.0006252 0.0390933 0.3141687 Coefficients: (1 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) -0.021291 0.003994 -5.331 2.01e-07 *** x1

Hello, i have the following model, poi1<-glm(F~S+T+L+C,family=poisson,x=T) where F,S,T,L are metric and C is a factor variable with the levels "0", "1", "2", "3", "4", "5" and "6" if i do summary(poi1), i get the following Call: glm(formula = F ~ S + T + L + C, family = poisson, x = T) Deviance Residuals: Min

I run lm to fit an OLS model where one of the covariates is a factor with 30 levels. I use contr.treatment() to set the base level of the factor, so when I run lm() no coefficients are estimated for that level. But in addition (and regardless of which level I choose to be the base), lm also gives a vector of NA coefficients for another level of my factor. The output says that these coefficients

Hi- I'm wrestling with some of my data apparently not being called into a GLM or an LM. I'm looking at factors affecting fish annual catch rates (ie. CPUE) over 30 years. Two of the factors I'm using are sea surface temperature and sea surface temperature anomaly. A small sample of my data is below: CPUE Year Vessel_ID Base_Port Boat_Lgth Planing SST Anomaly 0.127

Hello, I have a data set which I am using to find a model with the most significant parameters included and most importantly, the p-values. The full model is of the form: sad[,1]~b_1 sad[,2]+b_2 sad[,3]+b_3 sad[,4]+b_4 sad[,5]+b_5 sad[,6]+b_6 sad[,7]+b_7 sad[,8]+b_8 sad[,9]+b_9 sad[,10], where the 9 variables on the right hand side are all indicator variables. The thing I don't understand

I am using a nested model in R and the lm output shows 47 not defined because of singularities and I have no idea why. Any help on why this is happening or how to fix this problem would be very much appreciated. Below is the output I received from R. Thanks and happy holidays! Call: lm(formula = Dist ~ Treatment/SiteL/Territory) Residuals: Min 1Q Median 3Q Max -6.646 -1.443

Hello, I am trying to run a linear regression analysis on my data set. For some reason most variables are removed due to singularities. My linear regression looks this way (I am using only partial data, which is selected by flags): fm<-lm(log(cplex6.time..sec..[flags]) ~ cplex6.cities[flags] + log(1/features.meanOver.frust[flags]) + log(1/features.meanOver.minDist[flags]) + [...]