search for: concave

Displaying 20 results from an estimated 29 matches for "concave".

2009 Jan 17
2
Concave Hull
Dear Friends, Here is an algorithm for finding concave hulls: http://get.dsi.uminho.pt/local/ Has anyone implemented such an algorithm in R? RSiteSearch('concave hull') didn't reveal one (I think). _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology Postal Address: P.O.Box 400400, Charl...
2006 May 02
2
Concave Hull?
...sing trmat and want to trim the resulting matrix to the area enclosed by my real data (i.e., remove all the extrapolated areas). I was using chull and in.chull to calculate the convex hull and change all the other values created by trmat to NA. However, my real data has portions that are slightly concave so chull would give me slivers that are extrapolations from my data. Is there some other type of "chull" function that will allow the resulting polygon to be slightly concave? (I can send a picture to show what I am trying to do, if needed) Thanks in advance, Mike Mike R. Saunders For...
2009 Nov 25
3
Concave hull
Dear friends, Do you know how to calculate the CONCAVE hull of a set of points (2- dimensional or n-dimensional)? is that possible in R? (With a "smoothing" parameter of course). Best, -- Corrado Topi Global Climate Change & Biodiversity Indicators Area 18,Department of Biology University of York, York, YO10 5YW, UK Phone: + 44 (0) 19...
2013 Apr 25
1
Stochastic Frontier: Finding the optimal scale/scale efficiency by "frontier" package
Hi, I am trying to find out the scale efficiency and optimal scale of banks by stochastic frontier analysis given the panel data of bank. I am free to choose any model of stochastic frontier analysis. The only approach I know to work with R is to estimate a translog production function by sfa or other related function in frontier package, and then use the Ray 1998 formula to find the scale
2010 Aug 08
3
Does anybody know how to control the appearance of the end of the line in lattice?
Hi All, I am plotting vertical lines using xyplot in lattice and type="h". It works well, but the problem is that the tops of the lines are convex and the bottoms are concave. Is there a way to flatten the tops and bottoms? Here's my code: Source<-matrix(1:30,10,3) colnames(Source)<-c("x","y1","y2") Source<-data.frame(Source) xyplot(y2+y1~x, data=Source, distribute.type=TRUE, type=c("h","h"), col=c(&q...
2003 Jul 13
3
How robust is mle in R?
A newbie question: I'm trying to decide whether to run a maximum likelihood estimation in R or Stata and am wondering if the R mle routine is reasonably robust. I'm fairly certain that, with this data, in Stata I would get a lot of complaints about non-concave functions and unproductive steps attempted, but would eventually have a successful ML estimate. I believe that, with the 'unproductive step' at least, Stata gets around the problem by switching to some alternative estimation method in difficult cases. Does anyone know how robust mle is in...
2003 Sep 01
0
Quantile Regression Packages
...bivariate fitting is based on the total variation penalty (triogram) methods described in Koenker and Mizera (2003), available at http://www.econ.uiuc.edu/~roger/research/goniolatry/gon.html and forthcoming in JRSS(B). There are options to constrain the qss components to be monotone and/or convex/concave for univariate components, and to be convex/concave for bivariate components. Fitting is done by new sparse implementations of the dense interior point (Frisch-Newton) algorithms already available in the package quantreg. The new package "nprq" thus supplements the existing packages &qu...
2013 Mar 21
0
"[[i]]$" <- "" indexing and lapply
...t;21NC02WQ.C1000000") # shows the correct naming convention before being ran through modelEstimation > dput(Sample) structure(list(`21NC02WQ.C1000000` = structure(list(Date = structure(numeric(0), class = "Date"), ConcLow = numeric(0), ConcHigh = numeric(0), Uncen = numeric(0), ConcAve = numeric(0), Julian = numeric(0), Month = numeric(0), Day = numeric(0), DecYear = numeric(0), MonthSeq = numeric(0), SinDY = numeric(0), CosDY = numeric(0)), .Names = c("Date", "ConcLow", "ConcHigh", "Uncen", "ConcAve", "Julian", &quot...
2010 Apr 26
3
Identifying breakpoints/inflection points?
Hello! I have a dataset with the following two vectors: year<-c(1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009)
2003 Jul 18
1
Grandstream BudgeTone 102 initial experiences
Just to toss in my very limited experiences with the Grandstream phone-- I haven't tested it enough to really know nor is my Asterisk config set up enough to fully try all the features. Mostly, it just works. It was very easy to configure and get running. I've been toting it around to clients as a show and tell exhibit and it has helped get people excited about the possibilities. Voice
2005 Jun 06
3
(Off topic.) Observed Fisher information.
I have been building an R function to calculate the ***observed*** (as opposed to expected) Fisher information matrix for parameter estimates in a rather complicated setting. I thought I had it working, but I am getting a result which is not positive definite. (One negative eigenvalue. Out of 10.) Is it the case that the observed Fisher information must be positive definite --- thereby
2005 Jun 25
2
optimization problem in R ... can this be done?
...lies on the real line. g may take values along the real line. g is such that g(x,n)=g(-x,n). g is a decreasing function of x for any n; for fixed x, g(x,n) is smooth and intially decreases upon reaching an inflection point, thereafter increasing until it reaches a maxima and then declinces (neither concave nor convex). My optimization problem is to find the largest positive x such that g(x,n) is less than zero for all n. In fact, because of the symmetry of g around x, we need only consider x > 0. Such an x does exists in this problem, and of course g obtains a maximum value of 0 at some n for th...
2004 Nov 19
2
glm with Newton Raphson
Hi, Does anyone know if there is a function to find the maximum likelihood estimates of glm using Newton Raphson metodology instead of using IWLS. Thanks Valeska Andreozzi -------------------------------------------------------- Department of Epidemiology and Quantitative Methods FIOCRUZ - National School of Public Health Tel: (55) 21 2598 2872 Rio de Janeiro - Brazil
2008 Sep 16
0
Maximum likelihood estimation of a truncated regression model
...function to estimate truncated regression models as does STATA, LIMDEP etc. I tried the survival and FEAR packages and couldn't fit it for my case. So I wrote the log likelihood function of the truncated regression model and reparametrised it using Olsen (1978) so that the function is globally concave and has an unique maximiser. I used a quasi-Newton method (BFGS) to maximise my function. I also used Newton-Raphson method (maxNR) to maximise my function. The (naive) code can be seen below. sw1<-function(theta,dhat,z) { gamma<-theta[1:2] eta<-theta[3] d1<-dhat*eta-z%*%gamma d2<-...
2004 Jan 20
0
..You can be a ~Se-xxMachine~
adventurous burgundian rook elkhart butterball concave chaplin dustbin trout plane pedestal cinquefoil ely indigene choir curvilinear scald zing bramble braid cobol composition tripartite bust torpedo transverse marvin crestfallen troika molybdate aflame righteous aden diffusive lenin wilcox downright pittsburgh inflammable smear cathy orinoco
2012 Mar 07
0
sparsenet: a new package for sparse model selection
We have put a new package sparsenet on CRAN. Sparsenet fits regularization paths for sparse model selection via coordinate descent, using a penalized least-squares framework and a non-convex penalty. The package is based on our JASA paper Rahul Mazumder, Jerome Friedman and Trevor Hastie: SparseNet : Coordinate Descent with Non-Convex Penalties. (JASA 2011)
2012 Mar 07
0
sparsenet: a new package for sparse model selection
We have put a new package sparsenet on CRAN. Sparsenet fits regularization paths for sparse model selection via coordinate descent, using a penalized least-squares framework and a non-convex penalty. The package is based on our JASA paper Rahul Mazumder, Jerome Friedman and Trevor Hastie: SparseNet : Coordinate Descent with Non-Convex Penalties. (JASA 2011)
2006 Feb 10
8
Fitdistr and MLE for parameter lambda of Poisson distribution
Hello! I would like to get MLE for parameter lambda of Poisson distribution. I can use fitdistr() for this. After looking a bit into the code of this function I can see that value for lambda and its standard error is estimated via estimate <- mean(x) sds <- sqrt(estimate/n) Is this MLE? With my poor math/stat knowledge I thought that MLE for Poisson parameter is (in mixture of LaTeX
2005 Mar 09
2
Question about biasing in sd()???
Hi, Can anyone help me with the following. I have been using R for Monte Carlo simulations and got some results I couldn't explain. Therefor I performed following short test: -------------- mean.sds <- NULL sample.sizes <- 3:30 for(N in sample.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)) }
2007 Sep 16
5
using tc to drop packets based on the diffserc or tos value
Hi all, I am wondering if anyone can help me to resolve a problem. I am trying to use tc command in linux to drop udp packets of specific diffserv value. I am able set diffserv value successfully in the udp packet using command:- [root@scotch src]#iptables --table mangle --append OUTPUT \ --out-interface eth0 --protocol udp --source-port 5060 \ --jump DSCP --set-dscp 8 but i am not able to