similar to: median by geometric mean -- are we missing what's important?

Hi All, I need to calculate the median for even number of data points.However instead of calculating the arithmetic mean of the two middle values,I need to calculate their geometric mean. Though I can code this in R, possibly in a few lines, but wondering if there is already some built in function. Can somebody give a hint? Thanks in advance [[alternative HTML version deleted]]

Hi, I'm interested in experimental design and data analysis on mixtures, like cake recipes where the sum of the components is fixed; e.g. <http://www.itl.nist.gov/div898/handbook/pri/section5/pri54.htm>. I can't believe that R doesn't have facilities to design and analyse such experiments, but I haven't been able to find them (I have looked quite hard!). Can anyone point

Hi, Back in June I posted the message below, but had no replies. I've made a little progress since then so this is to update anyone interested (!) and to ask for comments. Brief problem statement: Under Windows, some parts of R don't handle UNC paths beginning with backslashes. Specifically a) Sys.glob() fails to find some files breaking (e.g.) Rcmdr plugins

Dear list, I have got an array with observational values t and I would like to fit a geometric distribution to it. As I understand the geometric distribution, there is only one parameter, the probability p. I estimated it by 1/mean(t). Now I plotted the estimated density function by plot(ecdf(t),do.points=FALSE,col.h="blue"); and I would like to add the geometric distribution. This

?Dear All I have some data expressed in geometric means and 95% confidence intervals. Can I code them in metafor as: rma(m1i=geometric mean 1, m2i=geometric mean 2, sd1i=geometric mean 1 CI /3.92, sd2i=geometric mean 2 CI/3.92.......etc, measure="MD") All of the studies use geometric means. Thanks! Edward ---------------------------- [[alternative HTML version deleted]]

Does anyone know how to approach R code for the MLE of a geom. distribution? thanks! [[alternative HTML version deleted]]

A statistical question, not specific to R. I'm asking for a pointer for a source of definitive descriptions of what types of data are best summarized by the arithmetic, geometric, and harmonic means. As an aquatic ecologist I see regulators apply the geometric mean to geochemical concentrations rather than using the arithmetic mean. I want to know whether the geometric mean of a set of

Is there a function or an easier way to computer geometric means of each rows in a nxn matrix and spit out in an 1xn matrix ? -- Edward Chen [[alternative HTML version deleted]]

Hello, Can anyone think of a non-iterative way to generate a decreasing geometric sequence in R? For example, for a hypothetical function dg, I would like: > dg(20) [1] 20 10 5 2 1 where I am using integer division by 2 to get each subsequent value in the sequence. There is of course: dg <- function(x) { res <- integer() while(x >= 1) { res <- c(res, x) x

>>>>> Rich Shepard >>>>> on Mon, 22 Jan 2024 07:45:31 -0800 (PST) writes: > A statistical question, not specific to R. I'm asking for > a pointer for a source of definitive descriptions of what > types of data are best summarized by the arithmetic, > geometric, and harmonic means. In spite of off-topic: I think it is a good

Hi, I have been using maxLik to do some MLE of Geometric Brownian Motion Process and everything has been going fine, but know I have tried to do it with jumps. I have create a vector of jumps and then added this into my log-likelihood equation, know I am getting a message: NA in the initial gradient My codes is hear # n<-length(combinedlr) j<-c(1,2,3,4,5,6,7,8,9,10)

I want to make a function for geometric seqeunce since testing=function(x){i=1;ans=1;while(true){ans=ans+(1/x)^i ; i=i+1} ;return(ans)} doesn't work... the program is freeze... from my research, i know i should use iterators. I read iterators.pdf at http://cran.r-project.org/web/packages/iterators/iterators.pdf and didnt find it helps solving my problem at all... Is there any sources I

Dear Rich, It depends how the data is generated. Although I am not an expert in ecology, I can explain it based on a biomedical example. Certain variables are generated geometrically (exponentially), e.g. MIC or Titer. MIC = Minimum Inhibitory Concentration for bacterial resistance Titer = dilution which still has an effect, e.g. serially diluting blood samples; Obviously, diluting the

Hi All, This example code ---------------- dDF <- structure(list(y = c(4.75587, 4.8451, 5.04139, 4.85733, 5.20412, 5.92428, 5.69897, 4.78958, 4, 4), t = c(0, 48, 144, 192, 240, 312, 360, 0, 48, 144), Batch = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ), T = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2), pH = c(4.6, 4.6, 4.6, 4.6, 4.6, 4.6, 4.6, 4.6, 4.6, 4.6), S = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), N = c(0, 0, 0, 0,

Hi, This is my first time posting to the mailing list, so if I'm doing something wrong, just let me know. I've taken ~1000 samples from 8 biological replicates, and I want to somehow combine the density functions of the replicates. Currently, I can plot the density function for each biological replicate, and I'd like to see how pool of replicates compares to a simulation I conducted

On Mon, 22 Jan 2024, Rich Shepard wrote: > As an aquatic ecologist I see regulators apply the geometric mean to > geochemical concentrations rather than using the arithmetic mean. I want to > know whether the geometric mean of a set of chemical concentrations (e.g., > in mg/L) is an appropriate representation of the expected value. If not, I > want to explain this to non-technical

Hi: I need to compute the geometric mean of a population. How i can do it?? thanks. Jorge M. A. Magalhae -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request

Hi, With R version 2.10.0 (2009-10-26) on Windows, I computed the p=1.e-20 quantile of the geometric distribution with parameter prob=0.1. > qgeom(1.e-20,0.1) [1] -1 But this is not possible, since X=0,1,2,... I guess that this might be a bug in the quantile function, which should use the log1p function, instead of the naive formula. Am I correct ? Best regards, Micha?l

Hi, I'd like to know which functions in a package call one specific function. I think I've seen a tool for identifying such dependencies, but now I can't find it :-( Searches of help and R site search for keywords like function, call, tree, depend haven't helped :-( Can anyone point me in the right direction? Thanks in advance, Keith Jewell

Dear all, I''m working with the geometric distribution for the time being, and I''m confused. This may have more to do with statistics than R itself, but since I''m getting results from R I find counterintuitive (well, yeah, my statistical intuition has not been properly sharpened), I feel like asking. The point first: If I do > rgeom(1,prob=1) I get: [1] NaN Warning