similar to: Validate fields and display errors from two models?

Dear R community, I have a fairly large file with variables in rows. Every variable (thousands) needs to be regressed on a reference variable. The file is too big to load into R (or R gets too slow having done it) and I do now read in line by line with "scan" (see below) and write the results to out. Although improved, this is still very slow... Can someone please help me and suggest

Hello all, I have two comboboxen, comboA is popultaed when :controller/list is retrieved first time. When comboA is selected, I want to auto-populate comboB (modelB belongs_to modelA). The population of tableC (modelC belongs_to modelB and belongs_to modelA) should not populate until a "GO" button is clicked (link_to with submit). Help? I need an example of how to filter the post

Hi all I have been doing series of linear regression models lm(). In this case the execution time and memory usage becomes a huge issue. I have therefore been trying to speed the process and limit the memory usage. Here follows part of the code do give better understanding of what I am doing: modela <- lm(RSSYS10 ~ RS_AGE + RS_AGESQ + SEX + RS_BMI) frssys <-

Hi all, I have a question regarding the duplication of a model and it''s associations. For example, if I have ModelA and it has_many SubModelAs and has_many SubModelBs associated with it. Each of the SubModels a belongs to ModelA. Is there a quick way of copying ModelA and the structure that lays below it? In the end I''ll then end up with ModelB which is a copy of A, and it has

I use model comparison with glms without mixed effects with anova(modelA,modelB), with mixed effects glm (glmmPQL), this doesn't work. Is there a way to compare model fits with glmmPQL's? Paula M. den Hartog Behavioural Biology Institute of Biology Leiden Leiden University [[alternative HTML version deleted]]

Dear helpeRs- I'm using a for loop to create a series of models. I'm trying to assign a name to each model created, using the loop index. The loop gets stuck at the name of the model, giving the error "target of assignment expands to non-language object". The linear model runs without error; only the name is problematic. Here is the current loop syntax. The use of dat

Hi folks. If I am indexing ModelA and ModelB and I want to search both of them, I usually just pick one arbitrarily and use it for #multi_search. Is there a slicker pattern, regarding from which model to invoke #multi_search? Can it be invoked directly from the Ferret library? Has anyone put together some sort of "dummy" search class? Thanks for any ideas. John

Hi, I''m looking to add tagging to an application, and I would like to allow self-referential tags, so that I can tag my tags. With the goal of generating a flexible tag hierarchy. After some googling it looks like acts_as_taggable is not the best piece of code, and I''m hoping to use the has_many_polymorphs plugin from http://github.com/fauna/has_many_polymorphs/tree/master.

Hi, I was hoping to get some advice regarding the testing of interactions, when one factor is modelled as a random effect... I have a model with binomial error structure where the response variable is the proportion of time spent at the main sett (animals were tracked for 28 consecutive days in each season, and were recorded either at the main sett or an outlier sett, so the response variable is

Dear List, I apologize in advance if this is silly. I tried to replicate an analysis I did previously in SPSS using R, and was surprised to find different results. So my question is: shouldn't the following SPSS syntax REGRESSION DEPENDENT INC89 /METHOD=ENTER hiedyrs experien SE93rec. Yeld the same results of the following R command modelB<-lm(INC89~HIEDYRS+EXPERIEN+SE93REC) I

I''m trying to show a preview of the comments, and I''m saving the comments through AJAX. So, I thought that I should be able to mimic the "comments" action for the "comments_preview" action very easily. So far, this isn''t the case. I have a link_to_remote tag inside of the form tag, and I don''t know how to send the parameters that are

I have a template that belongs to a certain model (model A). I need to call a helper method of a different model (model B). Then I need the helper method of B to call a helper method of model C. I tried using "include" and "require" and using namespaces, but I got "undefined method". What is the way to do it? -- Posted via http://www.ruby-forum.com/.

Hi all, I analysed my data with lme and after that I spent a lot of time for mean separation of treatments (post hoc). But still I couldn’t make through it. This is my data set and R scripts I tried. replication fertilizer variety plot height 1 level1 var1 1504 52 1 level1 var3 1506 59 1 level1 var4 1509 54 1 level1 var2 1510 48 2 level1 var1 2604 47 2 level1 var4 2606 51 2 level1 var3

Hello, I''m using find_with_ferret to search multiple models and it works great. The trouble is I need to filter the results using :include and :conditions. I get two errors depending on the syntax I use in the search. Reading the source, I see the retrieve_records method seems to filter the :include and :conditions so that they only apply to the relevant model when searching

I am trying to work my way through the book "Singer, JD and Willett, JB, Applied Longitudinal Data Analysis. Oxford University Press, 2003" using R. I have the SAS code and S-Plus code from the UCLA site (doesn't include chapter 8 or later problems). In chapter 8, there is a structural equation/path model which can be specified for the sem package as follows S <- cov(al2)

Hello together, I would like to predict my fitted values on a new dataset. The original dataset consists of the variable a and b (data.frame(a,b)). The dataset for prediction consists of the same variables, but variable b has a constant value (x) added towards it (data.frame (a,b+x). The prediction command returns the identical set of predicted values as for the original dataset yet I would have

Hello, I am presently trying to get a feel for the various packages out there that allow me to both analyze and simulate random fields. The package RandomFields is nice, but there are still a few aspects of its implementation that are confusing to me and I was hoping someone could help clarify things for me. It could also be that my questions reflect a lack of knowledge pertaining to random

Hi R-Help! I am trying to use R2WinBUGS but I get the following error message in WinBUGS (and there must be something wrong with my R statement as I tried it directly in WinBUGS and it worked): display(log) check(C:/Documents and Settings/Daikon/Roche/pop_model.txt) model is syntactically correct data(C:/Documents and Settings/Daikon/Roche/data.txt) expected key word structure compile(7) ...(and

I am trying to run a GLMM on some binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help

Has anyone programmed condition indexes in R? I know that there is a function for variance inflation factors available in the car package; however, Belsley (1991) Conditioning Diagnostics (Wiley) notes that there are several weaknesses of VIFs: e.g. 1) High VIFs are sufficient but not necessary conditions for collinearity 2) VIFs don't diagnose the number of collinearities and 3) No one has