search for: unbiased

...mple.sizes){ dum <- NULL for(I in 1:5000){ x <- rnorm(N,0,1) dum <- c(dum,sd(x)) } mean.sds<- c(mean.sds,mean(dum)) } plot(sample.sizes,mean.sds) -------------- My question is why don't I get 1 as a result from my sd() for small sample sizes? According to the help, sd() is unbiased, which anyway would not explain the small offset... Is it something in rnorm()? Thanx, Roy -- The information contained in this communication and any atta...{{dropped}}

...metric -- it indicates that no block in the CFG is really more or less likely than any other. Only *biases* in a specific direction would cause the block weights to go up or down significantly. > > I don't like this statement, or don't understand it. It is useful to know a branch is unbiased. Currently we assume branches are unbiased then optimize conservatively in those cases (do no harm). But if we had greater confidence in unbiased branches (because the branch was actually profiled), we could if-convert much more aggressively As an aside, I’d like to point out that knowing that a b...

...I have a data set that I am trying to analyze in R for a course and the instructions were to get a standard deviation which I already computed in R and use that number and change it to a biased standard deviation?.(I have the two equations and I understand the difference between the two and how the unbiased has the degree of freedom?..I just do not know how use my standard deviation and transform it in R to a biased one. Thanks in advance, Jessie

Hello, I have a vector of values with significant autocorrelation, and I want to calculate an unbiased standard deviation that adjusts for the autocorrelation. The formula linked below purports to provide what I want: https://en.wikipedia.org/wiki/Unbiased_estimation_of_standard_deviation#Effect_of_autocorrelation_.28serial_correlation.29 However, rather than just implementing this equation in my...

...{ x = x[!is.na(x)] n = length(x) if (n < 4) { cat('valid cases = ',n,'\nkurtosis is not defined for less than 4 valid cases!\n') } else { z = sqrt(n/(n-1))*scale(x) mean(z^4)-3 } } # -------------------------------------------- Whereas, to calculate the (unbiased) estimated population parameter of skewness and kurtosis, the correction should also include the number of cases in the following way: # -------------------------------------------- # Function to calculate the unbiased populataion estimate of skewness: skew=function(x) { x = x[!is.na(x)] n =...

...hat R samples random integers using an intuitive but biased algorithm by going from a random number on [0,1) from the PRNG to a random integer, e.g. https://github.com/wch/r-source/blob/tags/R-3-5-1/src/main/RNG.c#L808 Many other languages use various rejection sampling approaches which provide an unbiased method for sampling, such as in Go, python, and others described here: https://arxiv.org/abs/1805.10941 (I believe the biased algorithm currently used in R is also described there). I'm not an expert in this area, but does it make sense for the R to adopt one of the unbiased random sample alg...

...on is more algorithmic than prectical. What I am trying to determine is, are the GAM algorithms used in the mgcv package affected by nonnormally-distributed residuals? As I understand the theory of linear models the Gauss-Markov theorem guarantees that least-squares regression is optimal over all unbiased estimators iff the data meet the conditions linearity, homoscedasticity, independence, and normally-distributed residuals. Absent the last requirement it is optimal but only over unbiased linear estimators. What I am trying to determine is whether or not it is necessary to check for normally-dist...

I need to calculate a large number of t statistics, and would like to do so via matrix operations. So far I have figured out a way to calculate the mean of each row of the matrix: d <- matrix(runif(100000,1,10), 1000, 10) # some test data s <- rep(1,ncol(d)) # a sum vector to use for matrix multiplication means <- (d%*%s)/ncol(d) This is at least 1 order of magnitude faster than

Hi all, I'm using nnet() for non-linear regression as in Ch8.10 of MASS. I understand that nnet() by default optimizes least squares. I'm looking to have it instead optimize such that the mean error is zero (so that it is unbiased). Any suggestions on how this might be achieved? Cheers, Mike -- Mike Lawrence http://artsweb.uwaterloo.ca/~m4lawren "The road to wisdom? Well, it's plain and simple to express: Err and err and err again, but less and less and less." - Piet Hein

...In real life I set the "twopass" default to FALSE, because in finance noise is always bigger than signal. I am cc'ing to R-help, as this is really an R question. -- -- David Brahm (brahm at alum.mit.edu) colVars <- function(x, na.rm=FALSE, dims=1, unbiased=TRUE, SumSquares=FALSE, twopass=TRUE) { if (SumSquares) return(colSums(x^2, na.rm, dims)) N <- colSums(!is.na(x), FALSE, dims) Nm1 <- if (unbiased) N-1 else N if (twopass) {x <- if (dims==length(dim(x))) x - mean(x, na.rm=na.rm) else sweep(x...

...bar(); printf ("g = %d\n", g); g = 0; for (i = 0; i < 500000; i++) bar(); printf ("g = %d\n", g); } I expect the loop body frequency for the second loop to be about half of the first one. This holds fine for this test case: $ bin/opt -analyze -block-freq -S unbiased-branches.ll Printing analysis 'Block Frequency Analysis' for function 'bar': block-frequency-info: bar - entry: float = 1.0, int = 8 Printing analysis 'Block Frequency Analysis' for function 'main': block-frequency-info: main - entry: float = 1.0, int = 8 - for.c...

Hi people, If there is a fn "colMeans" why isn't there a "colSDs" etc Thanks, Phil. -- Philip Rhoades Pricom Pty Limited (ACN 003 252 275) GPO Box 3411 Sydney NSW 2001 Australia Mobile: +61:0411-185-652 Fax: +61:2:8923-5363 E-mail: pri at chu.com.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

...0.25 c3 -> d3 = 0.125 c3 -> d4 = 0.125 c4 = 0.25 d1 = 0.125 d1 -> e1 = 0.0625 d1 -> e2 = 0.0625 d2 = 0.125 d3 = 0.125 d3 -> e3 = 0.0625 d3 -> e4 = 0.0625 d4 = 0.125 One way of thinking about this is that for any basic block X which is predicated by N branches of unbiased probability (50/50), the frequency computed for that block is 2^(-N). The problem is that this doesn't represent anything close to reality. Processors' branch prediction works precisely because very, *very* few branches in programs are 50/50. Most programs do not systematically explore bre...

...> > algorithm by going from a random number on [0,1) from the PRNG to a random > > integer, e.g. > > https://github.com/wch/r-source/blob/tags/R-3-5-1/src/main/RNG.c#L808 > > > > Many other languages use various rejection sampling approaches which > > provide an unbiased method for sampling, such as in Go, python, and others > > described here: https://arxiv.org/abs/1805.10941 (I believe the biased > > algorithm currently used in R is also described there). I'm not an expert > > in this area, but does it make sense for the R to adopt one of...

On 9/20/18 1:43 AM, Carl Boettiger wrote: > For a well-tested C algorithm, based on my reading of Lemire, the unbiased > "algorithm 3" in https://arxiv.org/abs/1805.10941 is part already of the C > standard library in OpenBSD and macOS (as arc4random_uniform), and in the > GNU standard library. Lemire also provides C++ code in the appendix of his > piece for both this and the faster "nea...

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...s is probably biased high due to non-independence. Ideally I think I need the correlation coefficient between the predictions and observed values for the out of bag sample for each of the n trees produced, but I don't see this produced anywhere. Does anyone know of a means of getting a useful unbiased diagnostic for assessing overall fit? thanks Simon ____________________________________________________________ Sign-up for Bird Atlas 2007-11 at www.birdatlas.net ____________________________________________________________ Dr Simon Gillings Senior Research Ecologist - Land Use British Trust f...

...umber on [0,1) from the PRNG to a > random > >>> integer, e.g. > >>> https://github.com/wch/r-source/blob/tags/R-3-5-1/src/main/RNG.c#L808 > >>> > >>> Many other languages use various rejection sampling approaches which > >>> provide an unbiased method for sampling, such as in Go, python, and > others > >>> described here: https://arxiv.org/abs/1805.10941 (I believe the > biased > >>> algorithm currently used in R is also described there). I'm not an > expert > >>> in this area, but does i...

Dear list, I did simulations in which I generated 10000 independent Bernoulli(0.5)-sequences of length 100. I estimated p for each sequence and I also estimated the conditional probability that a one is followed by another one (which should be p as well). However, the second probability is significantly smaller than 0.5 (namely about 0.494, see below) and of course smaller than the direct

...e firm for whom the Bank as a firm already provides other services. It may equally decide to allocate to its own proprietary book or with an associate of HSBC Group. This represents a potential conflict of interest. HSBC Bank plc has internal arrangements designed to ensure that the firm would give unbiased and full advice to the corporate finance client about the valuation and pricing of the offering as well as internal systems, controls and procedures to identify and manage conflicts of interest. HSBC Bank plc Registered Office: 8 Canada Square, London E14 5HQ, United Kingdom Registered in England...