similar to: lambda.r 1.1.0 on CRAN

Dear colleagues in R, Has anybody implemented the 1) (Goodman & Kruskal) lambda or the 2) (Thiel's) uncertainty coefficient statistics (in the asymmetric and symmetric forms), or is anyone aware that they might reside in some package? A search in the R archives does indicate that they are (somehow) part of the CoCo package, but I would rather not start learning how to transform my

SoftImpute is a new package for matrix completion - i.e. for imputing missing values in matrices. SoftImpute was written by myself and Rahul Mazumder. softImpute uses uses squared-error loss with nuclear norm regularization - one can think of it as the "lasso" for matrix approximation - to find a low-rank approximation to the observed entries in the matrix. This low-rank approximation

SoftImpute is a new package for matrix completion - i.e. for imputing missing values in matrices. SoftImpute was written by myself and Rahul Mazumder. softImpute uses uses squared-error loss with nuclear norm regularization - one can think of it as the "lasso" for matrix approximation - to find a low-rank approximation to the observed entries in the matrix. This low-rank approximation

I used the nlrq function in the package "quantreg". There is a lambda in the output when I set trace=TRUE. With different start point, the results are converged, but the last lambda is different. I want to know the meaning "lambda=1" and "lambda=0". Many Thanks! Examples of output 1. Where the last lambda=1: 108.6581 : 0.3 8.0 iter 0 value 108.658087 final

>>>>> Serguei Sokol >>>>> on Tue, 4 Dec 2018 11:46:32 +0100 writes: > Le 04/12/2018 ? 11:27, I?aki Ucar a ?crit?: >> On Tue, 4 Dec 2018 at 11:12, <qweytr1 at mail.ustc.edu.cn> wrote: >>> function ppois is a function calculate the CDF of Poisson distribution, it should generate a non-decreasing result, but what I got is:

The nice new log=TRUE option in dpois appears to mess up the case where lambda=0 (I was trying to calculate the likelihood of a saturated model). Because the behavior is now always to calculate the probability in terms of exp(log(prob)), there's a test for lambda<=0 which really needs to be only lambda<0. dpois(0:5,0) ought to give 1 0 0 0 0 but gives NaNs instead. Here's

Hello, using the lda-method from MASS-package I was wondering whether there is a built-in method for figuring out Wilks' Lambda? Searching the Web I found in the r-help archive a thread form june 2002, but it didn't help me. I understand I can use manova and its summary-method to get Wilks' Lambda on the screen, but I don't see the connection to lda from MASS. Or does

Hi, I posted some days ago a question concerning the computation of lambda in the smooth.spline function (which I repreat at the bottom of the mail) given _df_ . Unfortunately the documentation is not clear to me. Maybee someone can help to answer in my view the basic question: If the penalized log likelihood is L = (y - f)' W (y - f) + lambda c' Sigma c how the _lambda_ in the above

function ppois is a function calculate the CDF of Poisson distribution, it should generate a non-decreasing result, but what I got is: > any(diff(ppois(0:19,lambda=0.9))<0) [1] TRUE Actually, > ppois(19,lambda=0.9)<ppois(18,lambda=0.9) [1] TRUE Which could not be TRUE. Code is tested in both R 3.5.1 and Microsoft R Open 3.5.1. _

Hello R users, I am trying to calculate the stochastic lambda for a published matrix population model using the popbio package. Unfortunately, I have been unable to match the published results. Can anyone tell me whether this is due to slightly different methods being used, or have I gone wrong somewhere in my code? Could the answer be as simple as comparing deterministic lambdas to

Usually when using raw glmnet I let the implementation choose the lambdas. However when training via caret::train the lambda values are predetermined. Is there any way to have caret defer the lambda choices to caret::train and thus choose the optimal lambda dynamically? -- Yang Zhang http://yz.mit.edu/

does anyone know how to extract Shrinkage intensity lambda and lambda.var values after run cov.shrink(x)? thanks, KZ [[alternative HTML version deleted]]

Hello, all. I have a somewhat embarrassing error, in that I cannot reliably reproduce it. I have sporadically experienced the error both on an SGI machine running Irix 6.5 and on a LinuxPPC machine. I have only seen this error using version 0.65.0. (I've been using versions since 0.61 or so.) The error message is in the subject line. Here's the traceback from the most recent

Anyone know of a package for numerically estimating lambda(3) and lambda(4) using location, position, skew and kurtosis estimates. I have a distribution and would like to use the gld package to do some simulations of the distribution, but need the lambda estimates to feed into gld. I have a program in Maple, which I may convert to C code for use in R, but before moving down that road I

Dear All, I would like to extract Lambda Sets from a binary matrix that represents a social network. The calculation of Lambda Sets is set out in Borgatti 1990 (which can be downloaded freely). The package SNA goes part of the way with the function MaxFlow but does not have the Lambda partitioning - but perhaps it is called differently in R. Does anyone know if it exists as a function or if there

Hi all, I am using glampath package for L1 regularized logistic regression. I have read the article " L1 regularization path algorithm for GLM" by park and Hastie (2006). One thing I can't understand that how to find best lambda for my prediction. I want to use that lambda for the prediction not the entire set. thanks. -- View this message in context:

Hi, I'm a beginner in the field, I have to perform the ridge regression with lm.ridge for many datasets, and I wanted to do it in an automatic way. In which way I can automatically choose lambda ? As said, right now I'm using lm.ridge MASS function, which I found quite simple and fast, and I've seen that among the returned values there are HKB estimate of the ridge constant and L-W

Le 04/12/2018 ? 11:27, I?aki Ucar a ?crit?: > On Tue, 4 Dec 2018 at 11:12, <qweytr1 at mail.ustc.edu.cn> wrote: >> function ppois is a function calculate the CDF of Poisson distribution, it should generate a non-decreasing result, but what I got is: >> >>> any(diff(ppois(0:19,lambda=0.9))<0) >> [1] TRUE >> >> Actually, >> >>>

Hi, all, I am using the lars package for lasso estimate. So I get a lasso fit first: lassofit = lars(x,y,type ="lasso",normalize=T, intercept=T) Then I want to get coefficient with respect to a certain value of \lambda (the tuning parameter), I know lars has three mode options c("step", "fraction", "norm"), but can I use the \lambda value instead

Hi, When using the glmnet() function of the package glmnet, A series of coefficients is returned for a list of descending lambda values. I am unable to locate anything in the documentation that explains HOW this choice of lambda series is made. (There is documentation about how to choose my own, but I want to understand how the authors are doing it) Any ideas? -- Noah Silverman UCLA