similar to: trouble automating formula edits when log or * are present; update trouble

Greetings, R developers Here are my requests today. 1. Would you care to review this vignette http://pj.freefaculty.org/R/Rchaeology.pdf and tell me if you think it is wrong headed, and 2. Supposing you do not think I'm completely wrong, would you care to point me at more examples of R idioms that lead to deep insights into the nature of R programming? Longer more boring explanation: In

Hi, I recently ran into an inconsistency in the way model.matrix.default handles factor encoding for higher level interactions with categorical variables when the full hierarchy of effects is not present. Depending on which lower level interactions are specified, the factor encoding changes for a higher level interaction. Consider the following minimal reproducible example: -------------- >

Hello Tyler, I want to bring to your attention the following document: "What happens if you omit the main effect in a regression model with an interaction?" (https://stats.idre.ucla.edu/stata/faq/what-happens-if-you-omit-the-main-effect-in-a-regression-model-with-an-interaction). This gives a useful review of the problem. Your example is Case 2: a continuous and a categorical regressor.

Hello Tyler, Thank you for searching for, and finding, the basic description of the behavior of R in this matter. I think your example is in agreement with the book. But let me first note the following. You write: "F_j refers to a factor (variable) in a model and not a categorical factor". However: "a factor is a vector object used to specify a discrete classification"

Hello Tyler, I rephrase my previous mail, as follows: In your example, T_i = X1:X2:X3. Let F_j = X3. (The numerical variables X1 and X2 are not encoded at all.) Then T_{i(j)} = X1:X2, which in the example is dropped from the model. Hence the X3 in T_i must be encoded by dummy variables, as indeed it is. Arie On Thu, Nov 2, 2017 at 4:11 PM, Tyler <tylermw at gmail.com> wrote: > Hi

Hello Tyler, You write that you understand what I am saying. However, I am now at loss about what exactly is the problem with the behavior of R. Here is a script which reproduces your experiments with three variables (excluding the full model): m=expand.grid(X1=c(1,-1),X2=c(1,-1),X3=c("A","B","C")) model.matrix(~(X1+X2+X3)^3-X1:X3,data=m)

Hi I have multi domain environment with root domain and subdomain. Forest and domain level windows 2003 native. Also forest prep and domain prep did for sccm 2007 ocs 2007 and Exchange 2003. After join Samba to domain like ad dc I had some problem with replication: ################################################# [root at dc03 ~]# samba-tool drs replicate dc02 dc03

I am sure this question has come up, but searching hasn't given me any results. So I need to enter this line: mx1 <- randomForest(X1 ~ elevation + slope + vegtype, data = moths.train) But the problem is that X1 is currently hard coded. I would instead like to be able to put in the value of X1 through a list. For example: list <- list("X1", "X2", "X3")

Greetings. I've written a convenience function for multicollinearity diagnosis. I'd like to report to the user the formula that is used in a regression. I get output like this: > mcDiagnose(m1) [1] "The following auxiliary models are being estimated and returned in a list:" [1] "`x1` ~ ." formula(fmla)() [1] "`x2` ~ ." I'd like to fill in the period

Am 13.03.19 um 18:50 schrieb Rowland Penny via samba: > Try running 'samba-tool ldapcmp ldap://dc1 ldap://dc2' thanks! I get differences, too many to post here, but I assume mostly related to the drift between the 2 dcs now? (lastLogonTimestamp seems obvious to me) What might solve the initial problem *maybe* * Comparing [DNSFOREST] context... * Objects to be compared: 19

Hi, I'd like to apply a 2^k factorial design with k=10 parameters. Obviously this results in a quite long term for the model equation due to the high number of combinations of parameters. How can I specify the equation for the linear model (lm) without writing all combinations explicitly down by hand? Does a R command exist for this problematic? Thanks for your help in advance, Sven

Hi, I have started getting the following error message when I run the repadmin showreps command on the Windows Server 2008 server that is my primary DC: DsReplicaGetInfo() failed with status 8453 (0x2105): Replication access has been denied. DsReplicaGetInfo() failed with status 8453 (0x2105): Replication access has been denied. My scenario has a Windows Server 2008 as the primary DC

Hi! This is my first time posting. I've read the general rules and guidelines, but please bear with me if I make some fatal error in posting. Anyway, I have a continuous response and 29 predictors made up of continuous variables and nominal and ordinal categorical variables. I'd like to do lasso on these, but I get an error. The way I am using "lars" doesn't allow for the

> > Hi > > > > > > I have multi domain environment with root domain and subdomain. > > Forest and domain level windows 2003 native. > > > Also forest prep and domain prep did for sccm 2007 ocs 2007 and > > Exchange 2003. > > > > > > After join Samba to domain like ad dc I had some problem with > > replication: > >

Dear list, given this formula: > fmla <- formula(y1 ~ spp1 + spp2 + spp3 + spp5) > fmla[[3]] spp1 + spp2 + spp3 + spp5 is this the intended behaviour of as.character: > as.character(fmla[[3]]) [1] "+" "spp1 + spp2 + spp3" "spp5" ? Where does the extra "+" come from? > as.character(fmla) [1] "~"

I would like to ask for advice from R experts about the benefits or dangers of using attr to return information with an object that is returned from a function. I have a feeling as though I have cheated by using attributes, and wonder if I've done something fishy. Maybe I mean to ask, where is the dividing line between attributes and instance variables? The separation is not clear in my mind

Thanks a lot for help in advance. I am switching from matlab to R and I guess I need some time to get rolling. I was wondering why this code : > fit.0 <- lm( Response ~ 1, data = ds3) > step(fit.0,scope=list(upper=~.,lower=~1),data=ds3) Start: AIC= -32.66 Response ~ 1 Call: lm(formula = Response ~ 1, data = ds3) Coefficients: (Intercept) 1.301 is not working

Hello, I am trying to "paste" together a formula to use in the mob function of party. This means the formula will be of the form y ~ x1+ ...+xM | z1+..zN. I am doing some preliminary fits of y ~ x1+ ...+xM, then want to add the conditional part of the equation using update(). Here's the test code: var1 <- 1:78 x1 <- paste("x", var1, sep="") f1 <-

Hi, I am trying to build a series of rlm models. I have my data frame and the models will be built using various coulmns of the data frame. Thus a series of models would be m1 <- rlm(V1 ~ V2 + V3 + V4, data) m2 <- rlm(V1 ~ V2 + V5 + V7, data) m3 <- rlm(V1 ~ V2 + V8 + V9, data) I would like to automate this. Is it possible to use a string in place of the formula? I tried doing: fmla

Hi, I'm trying to compile half precision program for ARM, while it seems LLVM fails to automatically generate fused-multiply-add instructions for c += a * b. I'm wondering whether I did something wrong, if not, is it a missing feature that will be supported later? (I know there're fp16 FMLA intrinsics though) Test programs and outputs, $ clang -O3 -march=armv8.2-a+fp16fml