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Dear All, Help is needed! I have a matrix with frequencies of fish larvae per length class (var. sl) and age-group (var. median.no) obtained with >k<-table(cut(sl,(5:22)),median.no) >k[2:5,1:5] #to ilustrate k 4 5 6 7 (6,7] 3 1 0 0 (7,8] 3 0 1 0 (8,9] 3 4 3 5 (9,10] 3 15 7 13 from this matrix I would like to obtain the mean age per length class i.e.

Dear All, I'me having (much) trouble understanding why it happened and answering a referee's comment to part of a submitted manuscript. I've tried to google for help but... I'm really confident that although this is a R-Help list someone can help me! I used R to do an ANCOVA w/ RNA/DNA as the dep var, sl as the indep var and gut (a factor w/ levels: prey and empty) as the

Dear All, I'm trying to calculate the following: g.rate<-(SL-int)/NO where SL and NO are individual length and counts for the same subject, and the int value is a day-specific value i.e. for each DAY=88, 101..., 172 I'd like to use a different values of int=9.32, 8.43, ..., 9.81. All variables are compiled in a larger data.frame of the form: CODE SL NO DAY (...) 123 12.5 14

Dear All, I'm confortable with xyplot(...) and panel.lmline(...) statements (at least I thought I did :). I've used the following code to plot the decline in log-abundance of fish larvae (no.larvae) with age (age.cls, 4 to 27 days-old) for specific dates of sampling (day, 9 dates). I further plotted data with different colors and regression lines for ages 5-14 d and 17-23 d in a 7-by-1

Dear All, A few weeks ago I posted a question to this list but unfortunately got no answer! A friend warned me of my english. Again, the problem is: A 2-level 5-factors completely randomized design was used to investigate the potential effects of those factors on a solution's characters (several response variables). Each response-variable was measured repeatedly (13 times) during a

Dear All, I'm having trouble tweaking a forest plot made using the R meta-analysis package metafor. I did the analysis based upon the correlation coeff from studies and plotted the corresponding forest plot easily > q2<-rma(yi,vi,mods=cbind(grupo),data=qim) > q2 > forest (q2,transf=transf.ztor,digits=3, ... ,alim=c(0,1),refline=.5) > text(-1.55,42,"Esp?cie

Dear All, I'd like to fit a "kind" of logistic model to small data-set using nonlinear least-squares regression. A transcript of R-script are reproduced below. Estimated B and T (the model's coeff, herein B=-8,50 and T=5,46) seem appropriate (at least visually) but are quite diff from those obtained w/ SPSS (Levenberg-Marquardt): B=-19,56 and T=2,37. Am I doing something wrong in

*Thanks* all those who took the time to help me (even if the "question" was not related to - the use of - R). Now I think I can soundly make my point w/ the referee (can I use your replies? If so I intend to properly cite its use?!?). Regards, Eduardo Esteves ps - Sorry for not explaining the "biological details" of my posting: RNA/DNA is the ratio of RNA content to

Dear All, I'm a Marine Biologist using R (in a most informal and applied way) for a couple of years. Actually, I've been using R to analyse the results supporting my thesis. I would like to put together (in the same file) the data (.txt files) and the scripts files (.R files) for each chapter. How can I do this? Thanks in advance, Eduardo Esteves [[alternative HTML version deleted]]

Dear All, I'm new to the list and relatively new to R (but not so to S-Plus) and I?ve been asked to help study some experimental data. In a factorial experiment (5 factors at 2 levels) the response-variable was measured at various times (0, 2, 5, 7, ..., 30 days after start). There's just one run for each factor combination! I intend to use the nlme library of Pinheiro and Bates in a

Dear Sebastian Luque (and All R Users) With the following code I managed to plot different characters and regression lines for panels 2 ("Day of year 101") and >4 ("Days of year" 151, 157 and 172): xyplot(log(no.larvae)~age.cls|factor(day),data=mortal, layout=c(7,1),aspect=5/3, xlab="Age class (d)",ylab="Ln(Abundance)",

Dear All, (this msg is a statistics/computing question to the list) I'm trying to implement a modern-version of a (classic) "several-step protocol" in Fishery Biology (due to Bhattacharya, 1967): analysis of length-frequency distribution of fish larvae to id cohorts and later estimate growh rates! I've trouble with the 1st step: using kernel density estimation (KDE) function

Dear All, I'm having trouble ploting multiple xYplots (Hmisc) within the same pg although I've done it before w/ xyplots. I've produced 4 similar plots e.g. rna.h<-xYplot(Cbind(RNA,Lo,Up)~HO|factor(MO,labels=c("April", "May","June")),data=diel.data,method="bars",type="b", keys="lines",pch=16,col=1,cap=.04,

Dear All, I'm having trouble ploting multiple xYplots (Hmisc) within the same pg although I've done it before w/ xyplots. I've produced 4 similar plots e.g. rna.h<-xYplot(Cbind(RNA,Lo,Up)~HO|factor(MO,labels=c("April", "May","June")),data=diel.data,method="bars",type="b",