search for: nonnegativity

Is there a way to force certain formula parameters to be nonnegative? What I want to do is to estimate student capacity over time, namely by > capacity ~ Student + Student:Day I add this formula to a glm call and obtain negative learning slope estimates (Student:Day) in some cases. However, I don't want to allow for that. In such a case, glm should solve > capacity ~ Student and

Dear all, Is there any method in R to find all possible nonnegative integer solutions to the linear equation with unit coefficients as follow: X1+X2+...+Xk=N Thank you, Amin Zollanvari

The 'NMF' package implements a number of standard algorithms to perform Nonnegative Matrix Factorization. It also provides a flexible framework to easily test and develop new methods, as well as a layer to work with Bioconductor objects. The package is available from CRAN. Feedbacks are welcome. -- Renaud Gaujoux Computational Biology - University of Cape Town South Africa

The 'NMF' package implements a number of standard algorithms to perform Nonnegative Matrix Factorization. It also provides a flexible framework to easily test and develop new methods, as well as a layer to work with Bioconductor objects. The package is available from CRAN. Feedbacks are welcome. -- Renaud Gaujoux Computational Biology - University of Cape Town South Africa

Full_Name: Kjetil Kjernsmo Version: 1.1.1.1 (patched the rpois :-)) OS: osf4.0e Submission from: (NULL) (129.240.28.227) Dear all, I have just gotten through a debugging session of my code, being confused for a few days. I sent what I thought was a straightforward matrix to chisq.test() and once in a while got the error message: > chisq.test(t2) Error in chisq.test(t2) : missing value where

A question about the inner workings of glm() and dpois(): Suppose I call glm(y ~ x, family=poisson, weights = w) where y contains NON-INTEGER (but still nonnegative) values. (a) Does glm() still correctly maximise the weighted Poisson loglikelihood ? (i.e. the function given by the same formal expression as the weighted loglikelihood of independent Poisson variables Y_i except that the

Hi, I am trying to do some calculations turning DMS data to decimal degrees using the formula (D+(M/60)+(S/3600)), some of the D's involve -ve numbers, the easiest way to do the calculation is to use absolute numbers then use the 'sign' function in R to change the answer back to the correct -ve or +ve, for example, if; D<--69 M<-8 S<-10 then decimal<-D+(M/60)+(S/3600)

Full_Name: Petr Savicky Version: 2.4.0 OS: Fedora Core release 2 Submission from: (NULL) (62.24.91.47) the error is > binom.test(0.56*10000,10000) Error in binom.test(0.56 * 10000, 10000) : 'x' must be nonnegative and integer while > binom.test(5600,10000) yields correct result. The same error occurrs for > binom.test(0.57*10000,10000)

Hi all, The function h below is a function of c and it should be a monotone increasing function since the integrand is nonnegative and integral is taken from c to infinity. However, as we can see from the plot, it is not shown to be monotone. Something wrong with the usage of integrate function? Thanks so much for your help. Hanna h <- function(c){ g <- function(x){pnorm(x-8.8,

Hi all, I am new to python, R and rpy2. I having few errors when I am using 'fisher.test' function where I am struck now. Please help to fix these bugs. My code for fisher.test goes this way *from rpy2 import * import rpy2.robjects as robjects def fisherExact(a,b,c,d): v = [a,b,c,d] m = robjects.r['matrix'](v,2,2) s = robjects.r['fisher.test'](m) return s *

Hi all, I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero { min.val =

Hi all, I'm trying to write a script that changes all negative values in a data frame column to a small positive value, based on the the minimum value of the column. However, I get the following error: Error in if (x[i] < 0) { : argument is of length zero As well, I would "minimum" to be the smallest of the non-negative values...

Hello, I am using odesolve to simulate a group of people moving through time and transmitting infections to one another. In Matlab, there is a NonNegative option which tells the Matlab solver to keep the vector elements of the ODE solution non-negative at all times. What is the right way to do this in R? Thanks, Jeremy P.S., Below is a simplified version of the code I use to try to do this,

Hi, I got an error message in my program saying "Error in eigen(gene_intersection.kernel) : error code 1 from Lapack routine 'dsyevr' Execution halted". As you see, I was trying to compute the eigenvalues of a matrix but got this error. Is there anyone who knows what this error means and how I can fix it? Theoretically the eigenvalues should be nonnegative, if it helps.

patch against recent SVN ... as far as I can tell this trivial typo has been there for 20 years: https://github.com/wch/r-source/blame/ba7920a99fb2fb62b89e404e65f8b132ed4c150a/src/library/base/man/pretty.Rd =================================================================== --- pretty.Rd (revision 74426) +++ pretty.Rd (working copy) @@ -21,8 +21,8 @@ \item{min.n}{nonnegative integer giving

Dear list, I am trying to write a function that will make a matrix of each row of a data frame (4 columns), calculate a fisher.test on each resulting matrix and assign a vector of the p-values. I have gotten through making the matrices, but cannot calculate the fisher.test. fm<-function(x) {dfrow<-nrow(x) mm <- vector("list", dfrow) for(i in 1:dfrow) mm[[i]] <-

...rog package. My questions are here: 1- In the document for the package (The quadprog Package), the inequality constraint is mentioned with >= , however in a standard QP, this usaully is written with <= . This constraint should be multiplied by a negativity sign to be standard ? 2- How about nonnegativity constraints ? Are that possible to be handled via upper and lower bounds? In document, nonnegativity is not mentioned. Is there any argument for that? 3- In QP formulation we have a constant 1/2 in objective function. This should be multiplied by the user or it is done by the algorithm? 4- More i...

Sorry. I meant in the previous email that the function h() is a monotone decreasing function. Thanks very much. 2018-02-06 13:32 GMT-05:00 li li <hannah.hlx at gmail.com>: > Hi all, > The function h below is a function of c and it should be a monotone > increasing function since the integrand is nonnegative and integral is > taken from c to infinity. However, as we can see

Hello! I suppose this is more a matrix theory question than a question on R, but I will give it a try... I am using La.svd to compute the singular value decomposition (SVD) of a variance matrix, i.e., a symmetric nonnegative definite square matrix. Let S be my variance matrix, and S = U D V' be its SVD. In my numerical experiments I always got U = V. Is this necessarily the case? Or I might

Hi guys, I'm trying to use lmomco package. first I did the manual calculation on what is the estimates scale and location parameter given L-CV=0.2, L1=1000 L-moments and k (shape parameter) =- 0.1. so what i get is: location: 821.0445 scale: 260.7590 shape: -0.1000 #I assign this as GEV vectors using vec2par GEVpara2<-vec2par(c( 821.0445 , 260.7590 ,-0.1),'gev') #then I