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Dear useRs, upon request, the VGAM package (currently version 0.7-1) has been officially released on CRAN (the package has been at my website http://www.stat.auckland.ac.nz/~yee/VGAM for a number of years now). VGAM implements a general framework for several classes of regression models using iteratively reweighted least squares (IRLS). The key ideas are Fisher scoring, generalized linear and

...tp://crd.lbl.gov/departments/computer-science/PAR/research/previous-projects/torch-testbed/> : There are nearly 488 loops in this benchmark. LLVM was not able to distribute any loop. TSVC <https://github.com/shantanuatiith/TSVC_>: There are 151 loops coded in plain ‘C’, none of them got distributed. TSVC has particularly candidates valid for distribution like the one below. The inner loop in this example can be distributed. for (int nl = 0; nl < ntimes/2; nl++) { for (int i = 1; i < LEN; i++) { a[i] += c[i] * d[i]; b[i] = b[i - 1] + a[i] + d[i]; } dummy(a, b, c, d, e, aa, bb, cc,...

Hi, I'm dealing with wind data and I'd like to model their distribution in order to simulate data to fill-in missing values. Wind direction are typically following a vonmises distribution and wind speeds follow a weibull distribution. I'd like to build a joint distribution of directions and speeds as a VonMises-Weibull bivariate distribution. First is this a stupid question? I'm

...departments/computer-science/PAR/research/previous-projects/torch-testbed/>: > There are nearly 488 loops in this benchmark. LLVM was not able to distribute any loop. > > TSVC <https://github.com/shantanuatiith/TSVC_>: > There are 151 loops coded in plain ‘C’, none of them got distributed. TSVC has particularly candidates valid for distribution like the one below. The inner loop in this example can be distributed. > > for (int nl = 0; nl < ntimes/2; nl++) { > for (int i = 1; i < LEN; i++) { > a[i] += c[i] * d[i]; > b[i] = b[i - 1] + a[i] + d[i]; > } > dum...

...ution of means is equal to the mean of the population from which the samples were drawn. [2] The variance of the sampling distribution of means is equal to the variance of the population from which the samples were drawn divided by the size of the samples. --> [3] If the original population is distributed normally (i.e. it is bell shaped), the sampling distribution of means will also be normal. If the original population is not normally distributed, the sampling distribution of means will increasingly approximate a normal distribution as sample size increases. (i.e. when increasingly large samples a...

The following gives two functions for producing distribution graphs: distribution-graph produces a single graph, and multiple.distribution.graph produces a number of graphs side by side. Regards, Tore Wentzel-Larsen statistician Centre for Clinical research Armauer Hansen house Haukeland University Hospital N-5021 Bergen tlf +47 55 97 55 39 (a) faks +47 55 97 60 88 (a) email

Hello, I am trying to compute the density of a variable k that is either (1) Normally distributed; (2) Log-Normally distributed; or (3) follows proportional error distribution. I tried to search R-help and the answer for normal distribution was easy to find (please see 1c). I am not sure if my formula for dlnorm is correct (please see 2c below)? I really don't know what function to use for...

I wish to generate a vector of uniformly distributed data with a defined correlation to another vector The only function I have been able to find doing something similar is corgen from the library ecodist. The following code generates data with the desired correlation to the vector x but the resulting vector y is normal and not uniform dist...

...bunch of files containing 300 data points each with values from 0 to 1 which also sum to 1 (I don't think the last element is relevant though). In addition, each data point is annotated as an "a" or a "b". I would like to know in which files (if any) the data is uniformly distributed. I used Google and found out that a Kolmogorov-Smirnov or a Chi-square goodness-of-fit test could be used. Then I looked up ?kolmogorov and found "ks.test", but the example there is for the normal distribution and I am not sure how to adapt it for the uniform distribution. I did ?runif a...

Hi, I' am doing a stats project using R to work out the size of a t-test and wilcoxon test depending on the distribution and sample size. I just can't get it to work - I want to put my results from the function size() into an array.At the moment I keep getting the error message:Error in res[distribution, test, samplesize] <- results : subscript out of boundsCan anyone tell me where

...f&ei=RSJhUd7YJIbktQaQ-YCAAw&usg=AFQjCNGpCXUdLSVHQtYJMl7MccLGQtdkDw&sig2=HBxWDrRTMN7rVqWu-Yp1zQ&bvm=bv.44770516,d.Yms Especially page 238 is interesting: "According to this model, returns are generated as follows" r_t=sigma_t xi_t sigma^2_t is calculated by EWMA xi is distributed according to the generalized error distribution. So they do not assume the returns to follow a certain distribution, but they assume the returns condition on the volatility to follow a certain distribution, right? Now my question is, how can one calculate the VaR in this case? On page 242 they giv...

...By default, all source files are automatically included for distribution as well as certain "well known" files (see DistAlways variable in Makefile.rules for details). Each Makefile specifies, via the EXTRA_DIST variable, which additional files need to be distributed. Only those files that are needed to build LLVM should be added to EXTRA_DIST. EXTRA_DIST contains a list of file or directory names that should be distributed. For example, the top level Makefile contains "EXTRA_DIST := test llvm.spec include". This means...

I've built R functions to ``effect'' a particular distribution, and would like to find out if that distribution is already ``known'' by an existing name. (I.e. suppose it were called the ``Melvin'' distribution --- I've built dmelvin, pmelvin, qmelvin, and rmelvin as it were, but I need a real name to substitute for melvin.) The distribution is really just a toy

Reid, Could you explain in detail what make dist does? :) I'd like to see how it can be integrated into the release process. Thanks, Tanya

I want to calculate the probability that a group will include a particular point using the squared Mahalanobis distance to the centroid. I understand that the squared Mahalanobis distance is distributed as chi-squared but that for a small number of random samples from a multivariate normal population the Hotellings T2 (T squared) distribution should be used. I cannot find a function for Hotelling's T2 distribution in R (although from a previous post I have been provided with functions for the...

----- Original Message ----- From: "Richard A. O'Keefe" <ok at cs.otago.ac.nz> To: <paul at datavore.com> Sent: Thursday, September 04, 2003 2:56 AM Subject: Re: [R] Overlaying graphs > I do not know how to overlay the curve graphic on top of hist graphic. > > Do you know about the "add=TRUE" option for plot()? > > I am hoping to show visually

Hi guys Given a exponential curve, is there any function on r that can generate exponential distributed random numbers? in General I want an function that can transform one probability distribution into another?? Regards ****************************************************************** Bander ************************************* [[alternative HTML version deleted]]

Ok I made Jarque-Bera test to the residuals (merv.reg$residual) library(tseries) jarque.bera.test(merv.reg$residual) X-squared = 1772.369, df = 2, p-value = < 2.2e-16 And I reject the null hypotesis (H0: merv.reg$residual are normally distributed) So I know that: 1 - merv.reg$residual aren't independently distributed (Box-Ljung test) 2 - merv.reg$residual aren't indentically distributed (Breusch-Pagan test) 3 - merv.reg$residual aren't normally distributed (Jarque-Bera test) My questions is: It is possible merv.reg$residual...

Hello, after some discussions with Martin Maechler and Josef Leydold (WU Wien), we have felt the need for some package that should allow for an object-orientated approach to distributions. Our small group at Bayreuth now has developed a package "distr" which tries to fill this gap, implementing distributions by means of S4--classes. A mother class "Distribution" is

...merv <- na.remove(log(Argentina)) I made the Augmented Dickey-Fuller test to analyse if merv have unit root: adf.test(merv,k=13) Dickey-Fuller = -1.4645, p-value = 0.805, merv have unit root than diff(merv,1) is stationary. Than I made Breushch-Pagan test to test if residuals are identically distributed: library(lmtest) bptest(merv[2:1730]~-1+merv[1:1729],~merv[1:1729]+I(merv[1:1729])^2) BP = 81.3443, df = 2, p-value = < 2.2e-16 So merv.reg$resid aren't identically distributed. Than merv is heteroscedastik. Finally I made Box-Ljung test to test if residuals are independently distributed:...