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Hello folks, TL;DR: This is my proposed hashing interface based on a proposed standard hashing interface. It also is implemented with a much faster and higher quality algorithm than the current one. This is an *early draft* of the code, looking for initial feedback. There has been recent interest in improving the quality and consistency of LLVM's approach to hashing. In particular, getting

Hi, I wonder if anyone can answer the following or point me in the direction of how to obtain answers to the questions. Below is Output from R and further down are the questions raised and explanation of the study. Output from R: glm(formula = CB95TO00 ~ URB + INC, family = poisson) Deviance Residuals: Min 1Q Median 3Q Max -1.2272 -1.1290 0.2709 0.4272 2.1376

Hello, I need some help on a regression I am running please. I am running a multiple regression in R and I am getting weird outputs and would like your help in resolving it. This is the code I run: Reg = lm (Final$Y.t.-Final$Y.t.1. ~ Final$ Y.t.1. + Final$Cor + Final$Gov+ Final$Inv+ Final$TrOp + Final$Pop+ Final$Sch , data = Final) summary(Reg) And the output I get is pasted below. As

Hi Rabby, Before you run your regression, try this: is.factor(Final$Cor) If this returns TRUE, then this variable is a factor and it will be treated as a number of levels rather than a set of numeric values. This usually happens when a text file is read in and there is at least one value that cannot be converted to numeric. So if you are doing something like this:

Consider the following little "benchmark" > require(Matrix) > tmp <- Matrix(c(rep(1,1000),rep(0,9000)),ncol=1) > ind <- sample(1:10000,10000) > system.time(tmp[ind,]) user system elapsed 0.004 0.001 0.005 > ind <- sample(1:1000,10000,replace=TRUE) > system.time(tmp[ind,]) user system elapsed 0.654 0.006 0.703 >

Hi all, I have a question about linear model with interaction: I created a data frame df like this: >df V1 V2 V3 V4 V5 1 6.414094 c t a g 2 6.117286 t a g t 3 5.756922 a g t g 4 6.090402 g t g t ... which holds the response in the first column and letters (a,c,g,t) in the other columns. I am interested to see if there are interactions between the neigbouring letters

Hi all, I have a question about linear model with interaction: I created a data frame df like this: >df V1 V2 V3 V4 V5 1 6.414094 c t a g 2 6.117286 t a g t 3 5.756922 a g t g 4 6.090402 g t g t ... which holds the response in the first column and letters (a,c,g,t) in the other columns. I am interested to see if there are interactions between the neigbouring letters