similar to: Normalizing linear regression slope to intercept

Dear list, I am new with ggplot2 and I have spend quiet some time putting together the following code to create the attached plot. However there's still a few things that I'm having trouble with! I would be grateful if someone can tell me how to fix (1) the colour of my bars into grey scales (2) removing the y-axis (species name) on the right figure to avoid duplication, and (3) fix the

Dear list, After reading different mails, blogs, and tried a few different codes without any success, I am asking your help! I have the following data frame where each row represent a survey unit with the following variables: > names(RV09) [1] "record.t" "trip" "set" "month" "stratum" "NAFO" [7]

Begin forwarded message: > From: Dan Kelley <Dan.Kelley at Dal.Ca> > Date: March 19, 2004 12:00:01 PM AST > To: Don MacQueen <macq at llnl.gov> > Subject: Re: [R] osx/fink: cannot do "R INSTALL" (library mixup) > > That works perfectly! THanks. I did > 524 export PKG_LIBS="-L/usr/local/lib -L/sw/lib" > 525 R INSTALL pspline > and

Dear list, I have been struggling for some time now with this code... I have this vector of unique ID "EID" of length 821 extracted from one of my dataframe (skate). It looks like this: > head(skate$EID) [1] "896-19" "895-8" "899-1" "899-5" "899-8" "895-7" I would like to remove the complete rows in another dataframe

Hi all, I have created forest plots using the package "meta" that I submitted as pdf for publication. I just received an email from the editor asking me if I could send these files in an Excel or MS Word format such that they can treat them as tables with box plots. I am not sure if I can do this... Is this possible? I've tried the capture.output command, but I get a blank MS Word

Dear List, I've just tried to specify a GAM without an intercept -- I've got one of the (rare) cases where it is appropriate for E(y) -> 0 as X ->0. Naively running a GAM with the "-1" appended to the formula and the calling "predict.gam", I see that the model isn't behaving as expected. I don't understand why this would be. Google turns up this old

Dear all I have just had the question from a colleague. I know that it is not directly related to R (I will probably use R to do the analysis), but I hope someone can give us some insight: Thanks, AJ Smit I sampled populations of a seaweed in the intertidal in order to estimate the standing biomass of that seaweed at that site. Due to clumped distribution patterns, I chose a stratified

Hi, I am trying to write a for loop with if else statements to calculate biomass density estimates for different types of sampling gear. My code is: bmd=for (i in 1:length(Gear)){ if (Gear==20) {bioden=Biomass/141} else {if (Gear==23) {bioden=Biomass/68}} else {if (Gear==160) {bioden=Biomass/4120}} else {if (Gear==170) {bioden=Biomass/2210}} else {if (Gear==300)

Hi there, I have a data frame as listed below: > Ca.P.Biomass.A P Biomass 1 334.5567 0.2870000 2 737.5400 0.5713333 3 894.5300 0.6393333 4 782.3800 0.5836667 5 857.5900 0.6003333 6 829.2700 0.5883333 I have fit the data using logistic, Michaelis?Menten, and linear model, they all give significance. > fm1 <- nls(Biomass~SSlogis(P, phi1, phi2, phi3), data=Ca.P.Biomass.A)

Is there a way a function ('parent', say) can manipulate the ... argument, and then pass the manipulated value into another function ('child', say) that it calls? What I'm trying to do is to use some plotting defaults within 'parent' that are not part of parent's argument list, but to let the use over- ride these defaults if they choose. A sketch is below.

Hi. It's my understanding that a cross-correlation function of vectors x and y at lag zero is equivalent to their correlation (or covariance, depending on how the ccf is defined). If this is true, could somebody please explain why I get an inconsistent result between cov() and ccf(type = "covariance"), but a consistent result between cor() and ccf(type = "correlation")? Or

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, I have a strange su hehavior on a CentOS 5.4 32Bit installation in a VMware ESXi virtualizied environment: If I am root and want to change the user to a non-root user, the system prompts me for a password: [root at halifax ~]# useradd test00 [root at halifax ~]# su - test00 We trust you have received the usual lecture from the local System

I have never used -> but I noticed at http://github.com/jiho/r-utils/blob/master/beamer_colors.R that some people do. In fact, the above-named code has a sort of elegance about it (except for the use of "=" for assignment...). To my eye, -> calls to mind a type of assignment that is meant to stand out. For example, perhaps it would make sense to use -> to assign

I was surprised to find that just changing the base level of a factor variable changed the number of significant coefficients in the solution. I was surprised at this and want to know how I should choose the order of the factors, if the order affects the result. Here is the small example. It is taken from 'The R Book', Crawley p. 365. The data is at

Hi. I'm not having any luck installing the binary for the new Macintosh OS called "Tiger". I get error messages as below. Can anyone offer me some advice? (PS: I checked the bug list first but a search on "Tiger" turned up nothing so I hope it's OK to post here.) Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared

Hello R Community, Subject: Bayes Factor A Bayesian ANOVA of the form: competitionBayesOut <- anovaBF(biomass ~ clipping, data = competition) Returns the following Error message: Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ?compare? for signature ?"BFlinearModel", "missing", "tbl_df"? My guess the problem is in

Dear R users, Does anyone knows how to run a glmm with one fixed factor and 2 random numeric variables (indices)? Is there any way to force in the model a separate interaction of those random variables with the fixed one? I hope you can help me. #eg. Reserve <- rep(c("In","Out"), 100) fReserve <- factor(Reserve) DivBoulders <- rep

Dear all, I have a problem with interactions in lmer. I have 2 factors (garden and gebiet) which interact, plus one other variable (home), dataframe arr. When I put: / lmer (biomass ~ home + garden:gebiet + ( 1|Block), data = arr)/ it writes: /Error in lme4::lFormula(formula = biomass ~ home + garden:gebiet + (1 | : rank of X = 28 < ncol(X) = 30/ In the lmer help I found out that if not

Evening folks, I'm trying to print a series of graphs to .jpeg using a variable as the title, but run into the difficultly that I can't find a way to append the file extension to the .jpeg (in this case extensionless!) files. Example: ---- species.name="CussoniaHolstii" dia<-10:100 biomass = -21.4863 + 0.5797 * (dia ^ 2) biomass jpeg(species.name) plot (biomass,

Am trying to update my wine i get the following .. [] download]# yum update wine* Loading "priorities" plugin Loading "fastestmirror" plugin Loading mirror speeds from cached hostfile * epel: ftp.nluug.nl * rpmforge: fr2.rpmfind.net * base: ftp.halifax.rwth-aachen.de * updates: ftp.halifax.rwth-aachen.de * addons: ftp.halifax.rwth-aachen.de * extras: