similar to: Use of geometric mean for geochemical concentrations

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

>>>>> 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

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

better posted on r-sig-ecology? -- or maybe even stack exchange? Cheers, Bert On Mon, Jan 22, 2024 at 7:45?AM Rich Shepard <rshepard at appl-ecosys.com> wrote: > 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 >

On Mon, 22 Jan 2024, Bert Gunter wrote: > better posted on r-sig-ecology? -- or maybe even stack exchange? Bert, Okay. Regards, Rich

I think https://stats.stackexchange.com would be best: r-sig-ecology is pretty quiet these days On 2024-01-22 11:05 a.m., Rich Shepard wrote: > On Mon, 22 Jan 2024, Bert Gunter wrote: > >> better posted on r-sig-ecology? -- or maybe even stack exchange? > > Bert, > > Okay. > > Regards, > > Rich > > ______________________________________________

On Mon, 22 Jan 2024, Martin Maechler wrote: > I think it is a good question, not really only about geo-chemistry, but > about statistics in applied sciences (and engineering for that matter). > John W Tukey (and several other of the grands of the time) had the log > transform among the "First aid transformations": > > If the data for a continuous variable must all be

Ah.... LOD's, typically LLOD's ("lower limits of detection"). Disclaimer: I am *NOT* in any sense an expert on such matters. What follows are just some comments based on my personal experience. Please filter accordingly. Also, while I kept it on list as Martin suggested it might be useful to do so, most folks probably can safely ignore the rant that follows as off topic and not

I need to understand how and why dcast() adds NAs to a data frame that contained no missing values. The database table of chemical concentrations has all missing values removed because they cannot contribute to data analyses. The structure of the R data frame of these data have no NA values, and neither does the data frame resulting from applying the reshape2 melt() function to it. However,

Still OT... but here is my own (I think previously mentioned here) rant on people thrashing about with log transformation and an all-too-common kludge to deal with zeros mixed among small numbers... https://gist.github.com/jdnewmil/99301a88de702ad2fcbaef33326b08b4 OP perhaps posting a link here to your question posed wherever you end up with it will help shorten this thread. On January 22, 2024

?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]]

Data frame has this structure: 'data.frame': 11169 obs. of 4 variables: $ stream : Factor w/ 37 levels "Burns","CIL",..: 1 1 1 1 1 1 1 1 1 1 ... $ sampdate: Date, format: "1987-07-23" "1987-09-17" ... $ param : Factor w/ 8 levels "As","Ca","Cl",..: 1 1 1 1 1 1 1 1 1 1 ... $ quant : num 0.01 0.01 0.01 0.01

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

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

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)

---------- Forwarded message --------- From: Sahil Sharma <sahilsharmahimalaya at gmail.com> Date: Tue, Oct 17, 2023 at 12:10?PM Subject: r-stats: Geometric Distribution To: <do-use-Contact-address at r-project.org> Hey I want to raise one issue in *r-stats **geometric distribution * function. I have found the dgeom(x,p) which denotes probability density function of geometric

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

Folks: I know this may be overreaching, but are we missing what's important? WHY do the zeros occur? Are they values less then a known or unknown LOD? -- and/or is there positive mass on zero? In either case, using logs to calculate a geometric mean may not make sense. Paraphrasing Greg Snow, what is the scientific question? What is the model? Cheers, Bert On Mon, Jan 17, 2011 at 9:13 AM,

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]]