search for: areg

Hi R helpers! I'm still a bit ( alot) confused by the use of "inverseTrans" and "ytype" in areg.boot (Hmisc): What I want to do seems very simple, but I do not get the result I want: plot the predicted values in the original scale. (I did not understand the documentation, sorry!) for instance the following code f<-areg.boot(Pe[here]~monotone(t[here])+monotone(v[here])+I(Pa[here]-Pm[here]...

Hello everybody, I'm a new user of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x <- runif(20, 0, 1) xnew <- runif(2000, 0, 1) y <- sin(x) a <- ppr(x, y,

hi, i am looking to reproduce a study done in stata in R, where a regression was done while absorbing a categorical variable.? i am new to R, i've i installed the design package but haven't been able to find an applicable function. thanks for any help.

Hello R helpers! I'm using the avas function form package acepack (called from areg.boot package Hmisc) to estimate automatically transformations of predictors (in this case monotonous) and response. Well, it seems to work quite well, but I have 3 basic questions: - which set of basis functions is used in this procedure? - how do I back transform my estimate (y hat ) to the orig...

Hi Folks, Mac OS 10.4.4 R 2.2.1(2005-12-20 r36812) Hmisc 3.0-10 acepack 1.3-2.2 I keep getting a "segmentation fault" when trying to run areg.boot in the Hmisc package. I include below output from two different attempts. Thank you in advance for any help. Hank Stevens The following is taken from the example in the areg.boot documentation, run inside Aquamacs Emacs: > set.seed(171) # to be able to reproduce example > x1 &l...

...t's because my implementation is wrong. def MoveTy : SDTypeProfile<1, 1, []>; def MoveFlag : SDNode<"FOOISD::MOVE_FLAG", MoveTy, [SDNPHasChain, SDNPSideEffect, SDNPMayStore, SDNPMayLoad]>; let hasSideEffects = 1, mayStore = 1, mayLoad = 1 in { def MOVE : InstFOO<(outs ARegs:$dst), (ins BRegs:$src), "move $dst, $src", [(set i32:$dst, (MoveFlag i32:$src))]>; For example, I add this node into SDAG when I want to move the formal argument from the specific register class to other register class. I implement it in Lowe...

...ifferent register types (ie gpr, index, base, etc..) In 3.4, we would get something like this: mov @a, %b1 // moving this immediate to a base register, which is what we want In 3.6, we now get this: mov @a, %r0 // r0 = gpr mov %r0, %b1 // b1 = base reg The register class looks like this: def ARegs : RegisterClass<"us", [i16], i16, (add GPRRegs, IndexRegs, BaseRegs)>; I have absolutely no idea why this is not matching any longer? The fix here is to define an MI with explicit single register class (ie it only allows PTRRegs as the destination). This must be an issue with so...

Hye every one, My question will certainly seem stupid as I am quite a beginner in R. I would like to trace a curve which fits these two vectors: x<-c( 2,3,4,5,6,7,8,10 ) y<-c( 20, 12, 8, 6, 5, 4.5, 4, 3.8) It seems to follow a non linear model. Could anyone help me because I could'nt find the answer I am looking for in the FAQs. In advance thank you for your time. G. Lefebvre

...> mov @a, %b1 // moving this immediate to a base register, which is what > we want > > > > In 3.6, we now get this: > > > > mov @a, %r0 // r0 = gpr > > mov %r0, %b1 // b1 = base reg > > > > The register class looks like this: > > > > def ARegs : RegisterClass<"us", [i16], i16, (add GPRRegs, IndexRegs, > BaseRegs)>; > > > > I have absolutely no idea why this is not matching any longer? > > > > The fix here is to define an MI with explicit single register class (ie > it only allows PTRRegs as...

...n 3.4, we would get something like this: > > mov @a, %b1 // moving this immediate to a base register, which is what we want > > In 3.6, we now get this: > > mov @a, %r0 // r0 = gpr > mov %r0, %b1 // b1 = base reg > > The register class looks like this: > > def ARegs : RegisterClass<"us", [i16], i16, (add GPRRegs, IndexRegs, BaseRegs)>; > > I have absolutely no idea why this is not matching any longer? > > The fix here is to define an MI with explicit single register class (ie it only allows PTRRegs as the destination). > >...

...corresponds to xtreg in STATA) but with _variable_ weights (they correspond to changing industry shares in the market). Here is what I do: regsc<-lme(dsc~dcomp+dperc,random=~1|ind7090) update(regsc,weights=varFixed(~wt)) 1. however, my results are different from what I obtain in Stata using areg (the weighted fixed effects times series regression). any ideas? 2. how do I read of the random affects results from this regression? (i.e. coefficients on dcomp and dperc?) Any hint would greatly be appreciated. Best, -Raphael [[alternative text/enriched version deleted]]

...if you have time)! ;-) I have a very simple question and I really hope that someone could help me I would like to estimate a simple fixed effect regression model with clustered standard errors by individuals. For those using Stata, the counterpart would be xtreg with the "fe" option, or areg with the "absorb" option and in both case the clustering is achieved with "vce(cluster id)" My question is : how could I do that with R ? An important point is that I have too many individuals, therefore I cannot include dummies and should use the demeaning "usual" p...

Dear R-helpers, I have a very simple question and I really hope that someone could help me I would like to estimate a simple fixed effect regression model with clustered standard errors by individuals. For those using Stata, the counterpart would be xtreg with the "fe" option, or areg with the "absorb" option and in both case the clustering is achieved with "vce(cluster id)" My question is : how could I do that with R ? An important point is that I have too many individuals, therefore I cannot include dummies and should use the demeaning "usual" pr...

Hi Folks, Mac OS 10.4.4 R 2.2.1(2005-12-20 r36812) Hmisc 3.0-10 acepack 1.3-2.2 I had R crashes while running areg.boot in Hmisc (see old message below), but now I realize that the problem appears to be in the avas function in acepack. I tried running running the avas example (in acepack package), and got an immediate crash. Any thoughts? The Apple crash report (from R GUI crash) follows. Hank Date/Time...

>I am trying to use the Hmisc function transace to transform predictors > > test<-cbind(flowstress,pressres,alloy) > xtrans<-transace(x,binary=pressres',monotonic='flowstress', categorical='alloy') > > >and I am getting the following message?? >Error in ace(x[, -i], x[, i], monotone = im, categorical = ic) : > unused argument(s) (monotone ...)

Hi, I am working on a new back-end for LLVM. This architecture has two register types, data(A) and accumulator(B). A registers are i32 where as B registers are i64. This is causing me some headaches, as far as I can tell, it's not really possible to mix the two using tablegen? In the hardware, every instruction can either take an A register or a B register, in tablegen (as far as I can

...;>> we want >>> > >>> > In 3.6, we now get this: >>> > >>> > mov @a, %r0 // r0 = gpr >>> > mov %r0, %b1 // b1 = base reg >>> > >>> > The register class looks like this: >>> > >>> > def ARegs : RegisterClass<"us", [i16], i16, (add GPRRegs, IndexRegs, >>> BaseRegs)>; >>> > >>> > I have absolutely no idea why this is not matching any longer? >>> > >>> > The fix here is to define an MI with explicit single register c...

I am using ACE/AVAS to fit a non-parametric regression model to a multivariate data set. Is there a way to add confidence intervals to the fit and predictions by using bootstrap? Thanks for any suggestions. [[alternative HTML version deleted]]

Dear fellow R-users, I?m using the Glm function (gamma family of distributions) from the rms package to compare 2 groups on costs data. Although the summary function does provide the mean cost difference and standard errors, I believe these values were in the (natural) log ratio format. Is there a function to express these values into the original scale of the response variable (i.e., dollars)

Hi Every Body, I don't know why some regression functions have no related prediction function. For example lowess, loess, lokerns, lpridge, lpepa, and ksmooth. What could help? Is there any global or wrapper function so that can help? Regards, Amir Safari --------------------------------- [[alternative HTML version deleted]]