search for: estimators

Sorry if double posted... might have sent this to old mailing list address... ---------- Forwarded message ---------- From: Stephen Thomas <stephen.warner.thomas at gmail.com> Date: Wed, Aug 5, 2015 at 10:39 AM Subject: How to use CostModel? To: LLVM Dev <llvmdev at cs.uiuc.edu> Hi, I'm trying to use the built-in CostModel class to estimate the number of machine instructions

On Wed, Jan 15, 2014 at 5:30 PM, Nadav Rotem <nrotem at apple.com> wrote: > Was the vectorizer successful in unrolling the loop in quantum_sigma_x? I > wonder if 'size’ is typically high or low. No. The vectorizer stated that it wasn't going to bother with the loop because it wasn't profitable. Specifically: LV: Checking a loop in "quantum_sigma_x" LV: Found a

Hello. Slope estimates in lme are shrinkage estimates which pull the OLS slope estimates towards the population estimates, the degree of which depends on the group sample size and the distance between the group-based estimate and the overall population estimate. Although these shrinkage estimates as said to be more precise with respect to the true values, they are also biased. So there is a

Thanks to the help of many on this list, I am now an R user and have been able to write some functioning code to do matching estimation. I have two for loops (i in 1:3, and j in 0:2). Within the loops, I had been creating matrices of relevant estimation coefficents in order to make lots of LaTeX tables. Well, now I want to be able to combine the results of many different estimations from within

I am estimating a large model by groups. How do you save the results and?returns the associated quantiles? For this example I need a data frame n?? ?xi??????? mu????????beta 1?? 0.1033614? 2.5389580 0.9092611 2? ?0.3401922? 0.5192882 1.5290615 3?? 0.5130798? 0.5668308 1.2105666 I also want to apply gevrlevelPlot() for each "n" or group. ? #Example n <- c(1, 1, 1, 1, 1, 1, 2, 2, 2,

Dear R-list, I have made a simple kernel density estimation by x <- c(2,1,3,2,3,0,4,5,10,11,12,11,10) kde <- density(x,n=100) Now I would like to know the estimated probability that a new observation falls into the interval 0<x<3. How can I integrate over the corresponding interval? In several R-packages for kernel density estimation I did not found a corresponding function. I

...abase. I have already run pooled OLS but I would need to calculate a Fixed Effects Estimator (within estimator). Unfortunately I couldn't find anything like that in the RSearch and I suppose that lme (in package nlme) is not the answer. Is there any defined function to calculate panel data estimators like Fixed Effects Estimators (within), a between estimator or a Random Effects estimator. For more details on the estimators I would like to use see: Cameron, A. C.; Trivedi, P. K.: "Microeconometrics. Methods and Applications", Cambridge University Press, 2005, pp. 695-809. Thanks...

This option prints the estimated size of the data that will be copied from the source disk. For interest, the test prints: 3747840 ../test-data/phony-guests/windows.img Estimate: 3710976 --- v2v/Makefile.am | 2 ++ v2v/cmdline.ml | 17 ++++++++++-- v2v/cmdline.mli | 2 ++ v2v/test-v2v-print-estimate.sh | 47 +++++++++++++++++++++++++++++++++

Hello, I have a loop with 1000 repetitions which includes OR computation of an exposure factor and outcome. I compute OR like this: t<-table(exposure,outcome) oddsratio(t)$measure["estimate"] This gives me the estimates for exposure=0 and exposure=1 but exposure=0 is the reference group and i need only the estimate for exposure=1. I specified a matrix OR with 3 columns (for OR

Is it possible to simultaneously estimate mean and GARCH parameters in R? In other words, I would like to estimate the normal regression equation Y = b X + u and simultaneously do a garch process on the u's to correct the standard errors. I was thinking maybe something with systemfit(), but I can't quite come up with it. Thanks, Tobias --

I am fitting quantile regression models using data collected from a sample of 124 patients. When modeling cross-sectional associations, I have noticed that nonparametric bootstrap estimates of the variances of parameter estimates are much greater in magnitude than the empirical Huber estimates derived using summary.rq's "nid" option. The outcome variable is severely skewed, and I am

Hi, I have experimented with enabling the LoopVectorizer for SystemZ. I have come across a loop which, when vectorized, seems to have been poorly generated. In short, there seems to be a completely unnecessary sequence of shufflevector instructions, that doesn't get optimized away anywhere. In other words, there is a shuffling so that leads back to the original vector: [0 1 2 3

Hi all, I'm trying to estimate model parameters in R for a pretty simple system of equations, but I'm having trouble. Here is the system of equations (all derivatives): eqAlgae <- (u_Amax * C_A) * (1 - (Q_Amin / Q_A)) eqQuota <- (p_max * R_V) / (K_p + R_V) - ((Q_A-Q_Amin)*u_Amax) eqResource <- -C_A * (p_max * R_V) / (K_p + R_V) eqSystem <- list(C_A = eqAlgae, Q_A = eqQuota,

Dear All, we (Ott Toomet and I) would like to add functions for maximum likelihood (ML) estimations of generalized tobit models of type 2 and type 5 (*see below) in my R package for microeconomic analysis "micEcon". So far we have called these functions "tobit2( )" and "tobit5( )". Are these classifications well known? How are these functions called in other

Hi, I would like estimate a model for function of production's Coob-Douglas using maximum likelihood. The model is log(Y)= beta[1]+beta[2]*log(L)+beta[3]*log(K). I tried estimate this model using the tools nlm ( ) and optim ( ) using the log-likelihood function below: > mloglik <- function (beta, Y, L, K) { + n <- length(Y) + sum ( (log(Y)-

On Tue, Aug 14, 2018 at 8:29 PM Richard W.M. Jones <rjones@redhat.com> wrote: > This option prints the estimated size of the data that will be copied > from the source disk. > > For interest, the test prints: > > 3747840 ../test-data/phony-guests/windows.img > Estimate: 3710976 > Why not use qemu-img measure on the overlay? It gives a conservative estimate that

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch [SMTP:r-help-bounces at stat.math.ethz.ch] On Behalf Of Mark Miller > Sent: Thursday, November 17, 2005 10:16 AM > To: r-help at stat.math.ethz.ch > Subject: [R] Standard Error > > I have worked out that when I fit data I get an estimate and a standard error, > but all the definitions I can find

This option prints the estimated size of the data that will be copied from the source disk. Currently this overestimates by the size of the qcow2 header, but for real disk images that doesn't matter much. For example: $ virt-builder fedora-27 $ virt-v2v -i disk fedora-27.img -o null --machine-readable --print-estimate [...] virt-v2v: This guest has virtio drivers installed. [ 44.0] Mapping

"help" We want to estimate the number of caribou in Jasper. We recently conducted an aerial survey and saw 70 uncollared caribou and 8 of 11 collared caribou. We want to estimate the number of caribou in this population with 95% confidence limits. Gary White uses the hypergeometric distribution and determines the population estimates using maximum likelihood and 95%CL as

Hi, I am taking a survival class. Recently I need to do the Nelson-Aalen estimtor in R. I searched through the R help manual and internet, but could not find such a R function. I tried another way by calculating the Kaplan-Meier estimator and take -log(S). However, the function only provides the summary of KM estimator but no estimated values. Could you please help me with this? I would