similar to: read table problem

Windows 2000 . 5.00.2195 with Service Pack 1. R 1.5.1 Output from my split-split plot aov "alerted" me that I have done something wrong. I designed an experiment with all combinations of all levels of each treatment, but lost a little data (3 out of 192 plots). With the following data, I run the following model: > collim[c(1:6,187:192),c(1,3:6,9)] plot Litter Fert

Hi, I've data from an incomplete fatorial design. One level of a factor doesn't has the levels of the other. When I use lm(), the summary() return NA for that non estimable parameters. Ok, I understant it. But I use contrast::contrast(), gmodels::estimable(), multcomp::glht() and all these fail when model has NA estimates. This is becouse vcov() and coef() has different dimensions. Is

Dear R sages, I used the function rbind to combine a matrix (M) and a vector (Fert) to get a new matrix (A). This was fine. The issue is however, that the new matrix A has as its row names the name of the vector Fert, even though I set teh new vector A to have dimnames=NULL. See short code below fyi. *Fert<-c(0,1,5) * *M <- matrix(0, 2, 3) diag(M) <- c(0.3,0.5) * *A<-

Windows 2000 (v.5.00.2195), R 1.5.1 I have an lme object, fm0, which I examine with anova() and intervals(). The anova output indicates one of the interaction terms is significant, but the intervals output shows that the single parameter for that term includes 0.0 in its 95% CI. I believe that the anova is a conditional (sequential) test; is intervals marginal or approximate? Which should I

Hi R users, I sent a message yesterday about NA in model estimates ( http://r.789695.n4.nabble.com/How-set-lm-to-don-t-return-NA-in-summary-td3722587.html). If I use aov() instead of lm() I get no NA in model estimates and I use gmodels::estimable() without problems. Ok! Now I'm performing a lot of contrasts and I need correcting for multiplicity. So, I can use multcomp::glht() for this.

Dear R community, I am trying to fit an nlme model where I want to estimate the fixed effects of two treatments on the parameters on the following equation Photo~(a*(1-exp(-c*PARi/a)))-b I was able to fit a simple model without covariates following the method described in Mixed-Effects Methods and Classes for S and S-PLUS, version 3.0, but when I add the covariates, I get the error "

Hi R-Helpers: I?m trying to use the function GLMM from lme4 package, (R-1.8.1, Windows 98),and I get the following error: > pd5 = GLMM(nplant~sitio+ + fert+ + remo+ + sitio:fert+ + remo:sitio+ + remo:fert+ + remo:fert:sitio + data=datos, + family=binomial, +

Using R v. 1.7.0 on Windows 2000 I would like to plot the fitted values of a model as a function of a continuous covariate, augmented with data (e.g., augPred) grouping by combinations of fixed effects. I have not been able to use augPred effectively, and am wondering if it does not handle unbalanced data (3 out of 192 missing). I include below the model and an xyplot that almost does the

Hello, I am a Masters student and I am working on my thesis modelling smallholder farms using a program in R. I have modified the original code and I am having some issues with lists that I cannot figure out. Originally, I had list file defining lists such as: Param, Crop1, Crop1, Soil, etc. (ex. Param <- list() ). Their subsets were listed as Crop1$CContent for example and there was quite

Hi folks, As part of our build, the Tock project uses remap-path-prefix [1] to create a reproducible build. This means that the paths inside of built artifacts are not full source paths. When we later attempt to produce a listings file, the source mapping fails. The result is many copies of this recently merged warning [2]: llvm-objdump: warning:

Dear all I'm not sure if I did the right analysis for my specific split splot design. We are studying biomass increase with different CO2 concentrations with four different functional plant groups (e.g. grasses, herbs, broad-leafed trees and conifers). Of each functional plant group we have four species. The design is orthogonal. The design is: Blocks: 2 (climate chambers, called

Hello, As this little program illustrates, duplicating a STRSXP does not seem deep enough. require( inline ) fx <- cfunction( signature( x = "character"), ' SEXP y = PROTECT( duplicate( x ) ); int n = LENGTH(x); int nc = 0 ; char* p = 0 ; for( int i=0; i<n; i++){ p = (char*)( CHAR( STRING_ELT( y , i ) ) ); nc = strlen( p ) ; for( int j=0; j<nc; j++){ p[j] =

Hi all, Prefix: I am a frustrated Java coder in R. I am coding a medium sized ecosystem modelling program in R. I have changed to using S4 objects and it has cost me an order of magnitude in execution speed over the functional model. I cannot afford this penalty and have found that it is the result of all the passing-by-value of objects. I see that you can now safely inherit from

Hello, The UPS I am developing a driver to is able to report several flags for critical hardware conditions, like overheat, overload, inverter failure, output short etc. What should be the correct policy of operation when such a condition occurs? I think that the an UPS in such a condition is not reliable and therefore a system shutdown should be called. However, the developer's manual and

Can I say that RPART is a modified algo of CART and PARTY a modified of CHAID? Thanks. ---- Chua Siang Li Consultant - Operations Research Acceval Pte Ltd Tel: 6297 8740 Email: siang.li.chua at acceval-intl.com Website: www.acceval-intl.com This message and any attachments (the "message"...{{dropped:12}}

Hello there. I have fitted a rpart model. > rpartModel <- rpart(y~., data=data.frame(y=y,x=x),method="class", ....) and can use rpart$where to find out the terminal nodes that each observations belongs. Now, I have a set of new data and used predict.rpart which seems to give only the predicted value with no information similar to rpart$where. May I know how

Hi Rneters, I'm running a GLM model with a full factorial design in blocks and binomial error distribution. I would like to have the F values for this model but I got a message that "using F test with a binomial family is inappropriate in: anova.glm(model, test = "F")". Should I not report F statistics on this kind of analysis? I would appreciate any comment on this.

Hi, I'm trying to fit a logit model to a set of data that was collected under a split plot scheme. The structure of the data is Whole plot factors: Watering Frequency (2 levels: Hi/Lo) and Fertilizer type (3 factors A/B/C) Subplot factor: slope type (2 factors up/down) Response: Proportion of infected leaves(Infected leaves/Total leaves) of the plant (2 plants recorded from each plot)

Thanks Dragos, I assume I will be setting those parameters during initialization of encoder right? Question is, if connection gets too lossy, how will opus adapt to it? Can it automatically shift bitrate down to minimize impact? Mark from IRC suggests that the app has to be aware of the losses and change it on the fly. Has anybody on the list tried this? Kelvin Chua On Wed, Mar 4, 2015 at 5:53

The time has come to review the current Contributor and Core contributor grants for ZFS. Since all of the ZFS core contributors grants are set to expire on 02-24-2009 we need to renew the members that are still contributing at core contributor levels. We should also add some new members to both Contributor and Core contributor levels. First the current list of Core contributors: Bill