search for: mymod

...m not doubling up. I have tried to use R cmd to create an object file from the odesolve dynload example. I am using windows and have just installed rtools, and have the latest version of stable R (2..7.2). This is what happened: C:\Program Files\R\R-2.7.2\library\odesolve\dynload\c>Rcmd SHLIB mymod.c making mymod.d from mymod.c windres --preprocessor="gcc -E -xc -DRC_INVOKED" -I C:/PROGRA~1/R/R-27~1.2/include -i mymod_res.rc -o mymod_res.o gcc -std=gnu99 -shared -s -o mymod.dll mymod.def mymod.o mymod_res.o -LC:/PROGRA~1/R/R-27~1.2/bin -lR Cannot export myderivs: symbol not f...

...make use of the odesolve library on my university's Linux grid - currently R version 2.0.1 is installed and the system runs 64-bit Scientific Linux based on Redhat. I cannot seem to get lsoda working when I define the model as a shared C library. For example, the following snippet uses the mymod.c example bundled with the package: ### START rm(list=ls()) setwd("~/projects/test_odesolve") invisible(file.remove("mymod.o","mymod.so")) system("R CMD SHLIB mymod.c") dyn.load("mymod.so") require(odesolve) parms <- c(k1 = 0.04, k2 = 1e4, k3=...

...estimation on a random effects model with first-order autocorrelation to make a further conditional test. My model is much like this (which reproduces the method on the famous Grunfeld data, for the econometricians out there it is Table 5.2 in Baltagi): library(Ecdat) library(nlme) data(Grunfeld) mymod<-lme(inv~value+capital,data=Grunfeld,random=~1|firm,correlation=co rAR1(0,~year|firm)) Embarrassing as it may be, I can find the autoregressive parameter ('Phi', if I get it right) in the printout of summary(mymod) but I am utterly unable to locate the corresponding element in the lme o...

...I'm not sure this is better. I might have done with separate pointer as you have if I started from scratch today. * Use of constructor vs "new" static methods. When using the bindings one never initializes the class manually. Instead a "factory" method is used: mymod = Module.from_file(...) mymod = Module.from_data(...) mymod = Module.new("foo") ity = Type.int(32) instead of mymod = Module(file=...) mymod = Module(data=...) mymod = Module(name="foo") ity = IntType(32) I prefer this in, especially in the cases where t...

...issue with passing arguments to a function that takes a struct argument. typedef struct _test_struct { int x; int y; } test_struct; id testLLVMStructFuncCall(test_struct x) { NSLog(@"%d %d",x.x,x.y); return N(x.x + x.y); } -(void) testLLVMStructFuncCall { CGKModule* myMod = [CGKModule moduleWithName:@"llvm_structfunccall_test"]; CGKType* testStructType = [CGKType structTypeWithElementTypes:[NSArray arrayWithObjects:[CGKType intTypeWith32Bits],[CGKType intTypeWith32Bits],nil]]; CGKFunction* lfunc = [CGKFunction functionWithName:@"testLLVMStruct...

Several bugs (no solutions, yet). These might be well known. 1) If one does, e.g., mymod <- lm(y ~ x); formula(mymod) then one does not get back the formula (one gets, Error: invalid formula) 2) if x is of mode numeric, then the model formula mymod <- lm(y ~ x + x^2) is not processed as S would do it. The model is fit ignoring the x^2 term, however mymod$call includes the...

Several bugs (no solutions, yet). These might be well known. 1) If one does, e.g., mymod <- lm(y ~ x); formula(mymod) then one does not get back the formula (one gets, Error: invalid formula) 2) if x is of mode numeric, then the model formula mymod <- lm(y ~ x + x^2) is not processed as S would do it. The model is fit ignoring the x^2 term, however mymod$call includes the...

...ay to go (just as long as the automatically generated code is easy to diff when they are regenerated). * Use of constructor vs "new" static methods. > > When using the bindings one never initializes the class manually. > Instead a "factory" method is used: > > mymod = Module.from_file(...) > mymod = Module.from_data(...) > mymod = Module.new("foo") > ity = Type.int(32) > > instead of > > mymod = Module(file=...) > mymod = Module(data=...) > mymod = Module(name="foo") > ity = IntType(32) > Yeah, Modu...

On 3/17/2012 4:14 PM, Anders Waldenborg wrote: > FYI: > > I've also been working on new python bindings. > > My bindings are written using ctypes (just like the in-tree > clang/cindex bindings). Most of Core.h is bound, and stuff from > ExecutionEngine.h, Analysis, BitReader, BitWriter. The have fairly > good test coverage (using nosetests). The ctypes definitions are

At Fri, 16 Mar 2012 14:12:08 +0100, Christoph Grenz wrote: > > Hello, > > Am Donnerstag, 15. März 2012, 21:15:02 schrieb Gregory Szorc: > > There was some talk on IRC last week about desire for Python bindings to > > LLVM's Object.h C interface. So, I coded up some and you can now find > > some Python bindings in trunk at bindings/python. Currently, the >

..., 2) > y <- c(1.4287, 1.4426, 1.4677, 1.4774, 1.4565, > ? ? ? ? 1.4807, 1.4279, 1.4684, 1.4301, 1.4188, 1.4157, 1.4686, 1.4414, > ? ? ? ? 1.4172, 1.4829, 1.4291, 1.4438, 1.4068, 1.4524, 1.4183) > mydata<-data.frame(Mixture, x1, x2, x3, y) > mydata > mymod <- y ~ 1/(Beta1*x1 + Beta2*x2 + Beta3*x3) > library(nlsr) > strt<-c(Beta1=1, Beta2=2, Beta3=3) > trysol<-nlxb(formula=mymod, data=mydata, start=strt, trace=TRUE) > trysol > # or pshort(trysol) > > > Output is > > residual sumsqua...

...this case, it becomes impractical trying to list all probe patterns except those few you want to exclude. One way to deal with this is to use [! to exclude certain characters. For example, if we construct the clause below, we can exclude function patterns with leading "xyz": pid$target:mymod:[!x]*:entry, pid$target:mymod:[x][!y]*:entry, pid$target:mymod:[x][y][!z]*:entry { } >From this example, we know it is possible to exclude single pattern. But, to me, it becomes a puzzle if we want to exclude multiple patterns such as excluding additional pattern with leading "abc"....

...ale",16) Sex[sex==0]<-"Female" Dose<-rep("High",16) Dose[dose==0]<-"Low" Treatment<-rep("A",16) Treatment[treatment==0]<-"B" dat<-data.frame(Sex,Dose,Treatment,fix,Response) # Redundant Transfer and Execution of Dimension ID? mymod<-function(x){ model<-lm(Response~Sex,data=x) list(model,Dose=x$Dose[1],Treatment=x$Treatment[1])} myplt<-function(x){ plot(x[[1]],main=paste(x$Dose,"/",x$Treatment,sep=""))} # Generate list of Model Estimates dat.lm<-by(dat,list(Dose=dat$Dose,Treatment=dat$Tr...

..., 2, > 3, 3, 0, 2) > y <- c(1.4287, 1.4426, 1.4677, 1.4774, 1.4565, > 1.4807, 1.4279, 1.4684, 1.4301, 1.4188, 1.4157, 1.4686, 1.4414, > 1.4172, 1.4829, 1.4291, 1.4438, 1.4068, 1.4524, 1.4183) > mydata<-data.frame(Mixture, x1, x2, x3, y) > mydata > mymod <- y ~ 1/(Beta1*x1 + Beta2*x2 + Beta3*x3) > library(nlsr) > strt<-c(Beta1=1, Beta2=2, Beta3=3) > trysol<-nlxb(formula=mymod, data=mydata, start=strt, trace=TRUE) > trysol > # or pshort(trysol) > > > Output is > > residual sumsquares = 1.5412e-05 on 20 obser...

Inthe code below I was trying to to obtain the GMM estimates for CAPM (REGRESSION) for 36 stocks each have 180 observations,however it only gives me one output rather than 36. In SAS i would just put in a *By statement*. I have a variable TICKER that categorize them into 36 groups. *How can I obtain all 36 output instead of just one.* **

...anova code will jump in. If one fits a glm model with an offset, the NULL deviance is incorrectly calculated (it is calculated without the offset). The means one can get examples where the model deviance is greater than the NULL deviance. Here is some example output, (without the data). > mymod <-glm(cens ~ group, family=poisson,offset=log(time)) > anova(mymod) Analysis of Deviance Table Model: poisson, link: log Response: cens Terms added sequentially (first to last) Df Deviance Resid. Df Resid. Dev NULL 41 20.19 group 1 -17.83...

...anova code will jump in. If one fits a glm model with an offset, the NULL deviance is incorrectly calculated (it is calculated without the offset). The means one can get examples where the model deviance is greater than the NULL deviance. Here is some example output, (without the data). > mymod <-glm(cens ~ group, family=poisson,offset=log(time)) > anova(mymod) Analysis of Deviance Table Model: poisson, link: log Response: cens Terms added sequentially (first to last) Df Deviance Resid. Df Resid. Dev NULL 41 20.19 group 1 -17.83...

Dear friends, Hope you are all doing well and having a great weekend. I have data that was collected on specific gravity and spectrophotometer analysis for 26 mixtures of NG (nitroglycerine), TA (triacetin), and 2 NDPA (2 - nitrodiphenylamine). In the dataset, x1 = %NG, x2 = %TA, and x3 = %2 NDPA. The response variable is the specific gravity, and the rest of the variables are the predictors.

This question pertains to setting up a model in the package "dlm" (dynamic linear models, http://cran.r-project.org/web/packages/dlm/index.html I have read both the vignette and?"An R Package for Dynamic Linear Models" (http://www.jstatsoft.org/v36/i12/paper), both of which are very helpful. There is also some discussion at

Suppose x and y are numeric vectors of the same length. plot(x,y) #scatterplot lmObj1 <- lm(y~x) # best fit line abline(lmObj1) # good lmObj2 <- lm(x~y) #get best fit but with axes interchanged abline(lmObj2) # not what I want. I want the correct line, drawn on the same graph, but with # response and predictor variables interchanged One way to proceed would be to