similar to: boot() with glm/gnm on a contingency table

Hi, consider this one as an FYI, or a seed for further discussion. I am aware that many traps on sample() have been reported over the years. I know that these are also documents in help("sample"). Still I got bitten by this while writing sample(units, size=length(units)); where 'units' is an index (positive integer) vector. It works in all cases as expected (=I expect)

Hi dear all, Can someone help me about detection of outliers using jackknife after bootstrap algorithm? -- View this message in context: http://r.789695.n4.nabble.com/jackknife-after-bootstrap-tp3041634p3041634.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]

Hello; Our survey is structured as : To be investigated area is divided into 6 regions, within each region, one urban community and one rural community are randomly selected, then samples are randomly drawn from each selected uran and rural community. The problems is that in urban/rural stratum, we only have one sample. In this case, how to do bootstrap? Any comments or hints are greatly

Hi I was wondering if there is a permutation test available in R for linear models with continuous dependent covariates. I want to do a test like the one shown here. bmi<-rnorm(100,25) x<-c(rep(0,75),rep(1,25)) y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x H0<-lm(y~1+x+bmi) H1<-lm(y~1+x+bmi+x*bmi) anova(H0,H1) summary(lm(y~1+x+bmi)) But I want to use permutation testing to

Dear R experts, I have defined a class "myclass" and would like the slots to be extractable not only by "@" but also by "$". I now try to write a method for "$" that simply executes the request object at slotname, whenever someone calls object$slotname for any object of class "myclass". I don't manage to find out how I can provide this

A new 'dataframe' package is on CRAN. This is a modified version of the data frame code in R, modified to make fewer copies of the inputs and run faster, e.g. as.data.frame(a vector) makes 1 copy of the vector rather than 3, data.frame(a vector) makes 3 copies rather than 6, and x[, "a"] <- newValue makes (2,2,1) copies of (old data frame, new column, integer vector of

I've been playing with passing arguments to .C(), and found that replacing as.double(x) with if(is.double(x)) x else as.double(x) saves time and avoids one copy, in the case that x is already double. I suggest modifying as.double to avoid the extra copy and just return x, when x is already double. Similarly for as.integer, etc. [[alternative HTML version deleted]]

Hi, Recent Intel architectures AVX-512 and AVX2 provide vector gather and/or scatter instructions. Gather/scatter instructions allow read/write access to multiple memory addresses. The addresses are specified using a base address and a vector of indices. We'd like Vectorizers to tap this functionality, and propose to do so by introducing new intrinsics: VectorValue = @llvm.sindex.load

I did some benchmarking of data frame code, and it appears that R 3.0.0 is far worse than earlier versions of R in terms of how many large objects it allocates space for, for data frame operations - creation, subscripting, subscript replacement. For a data frame with n rows, it makes either 2 or 4 extra copies of all of: 8n bytes (e.g. double precision) 24n bytes 32n bytes

hi Hao, I started to upstream and the second patch is stalled under review now. - Elena -----Original Message----- From: Hao Liu [mailto:haoliuts at gmail.com] Sent: Friday, March 13, 2015 05:56 To: Demikhovsky, Elena Cc: llvmdev at cs.uiuc.edu Subject: Re: [LLVMdev] Indexed Load and Store Intrinsics - proposal Hi Elena, I think such intrinsics are very useful. Do you have any plan to

In SmallVector.h: class SmallVectorBase { *protected:* void *BeginX, *EndX, *CapacityX; *protected:* SmallVectorBase(void *FirstEl, size_t Size) : BeginX(FirstEl), EndX(FirstEl), CapacityX((char*)FirstEl+Size) {} In StringMap.h: class StringMapImpl { *protected:* // Array of NumBuckets pointers to entries, null pointers are holes. // TheTable[NumBuckets] contains a sentinel value

There is now a tutorial on bootstrapping and other resampling methods at: http://www.burns-stat.com/pages/Tutor/bootstrap_resampling.html Corrections and other suggestions are welcome. The project started because a novice asked me about bootstrapping. My response was, "How dare you bug me while I'm playing with my cats, just google for it." My correspondent was not very impressed

Hi all I want to construct a generalised nonlinear model (binomial family) using gnm, of the form: Response = a + b variable1 + c variable2 + d variable3 - d b variable4 - d c variable5, with the parameters b, c, and d appearing more than once. Hence, I think I need to use a custom nonlin function with gnm. One of my predictor variables is categorical, so I have created a dummy variable for

Hi all, I'm trying to fit a nonlinear (logistic-like) regression, and I'd like to get some recommendations for which package to use. The expression I want to fit is something like: y ~ A * exp(X * Beta1) / (1 + exp(-(x + X * Beta2 - xmid)/scal)) Basically, it's a logistic function, but I want to be able to modify the saturation amplitude by a few parameters (Beta1) and shift the

I would like to use the output from the map function in the package maps for use in, say, the spatstat package. I don't quite understand the coordinates for the border of the state: Example: library(maps) iowa<-map("region","iowa) x<-iowa$x y<-iowa$y There are NA's and duplicated coordinates. What would I need to do to use this in the spatstat owin command?

Hi everyone, I'm trying to perform the following regressions in order to compare linear vs. sigmoidal fit of the relationship between my dependent variable (y) and one explaining parameter (x2), both including the confounding effects of a third variable (x1): quasi-pois-lin <- glm(y ~ x1 + x2, family = quasipoisson(link="identity"), data=fit) quasi-pois-sig <- gnm(y ~ x1 +

Hi, I am quite new to R and would like to do nonlinear regressions with Poisson distributed data. I would like to estimate paramters of an equation of this type: FR = [c*NO * exp(a+b*NO)] / [(c+NO)*(1+exp(a+b*NO))] a,b and c are parameters, NO are input values I found both the gnm and gnlr3 function which should be able to do this regression but I can't manage to make it work. How can I

Sometimes one might like to obtain pointwise bootstrap bias-corrected, accelerated (BCA) confidence intervals for a large number of statistics computed from a single dataset. For instance, one might like to get (so as to plot graphically) bootstrap confidence bands for the fitted values in a regression model. (Example: Chiu S et al., Early Acceleration of Head Circumference in Children with

On 12/18/2014 11:56 AM, dag at cray.com wrote: > "Demikhovsky, Elena" <elena.demikhovsky at intel.com> writes: > >> Semantics: >> For i=0,1,…,N-1: if (Mask[i]) {*(BaseAddr + VectorOfIndices[i]*Scale) >> = VectorValue[i];} >> VectorValue: any float or integer vector type. >> BaseAddr: a pointer; may be zero if full address is placed in the

Below is a version of [.data.frame that is faster for subscripting rows of large data frames; it avoids calling duplicated(rows) if there is no need to check for duplicate row names, when: i is logical attr(x, "dup.row.names") is not NULL (S+ compatibility) i is numeric and negative i is strictly increasing "[.data.frame" <- function (x, i, j,