similar to: Separation issue in binary response models - glm, brglm, logistf

dear community, I am a beginer in R , and can't predict with logistic model in package logistf, could anyone help me ? thanks ! the following is my command and result : >library(logistf) >data(sex2) >fit<-logistf(case ~ age+oc+vic+vicl+vis+dia, data=sex2) >predict(fit,newdata=sex2) Error in predict(fit, newdata = sex2) : no applicable method for "predict"

Hi everyone, I'm wondering how to select the "best" model when using logistf? AIC does not work neither does anova. I tried fitting a glm model but got the separation warning message so I tried using the logistf package but as I stepwise simplify the model I don't know if the simplification is motivated or not... Can anyone explain to me how I should approach this problem? I

Hi, I got two questions and would really appreciate any help from here. First, is the penalized maximum likelihood estimation(Firth Type Estimation) only fit for binary response (0,1 or TRUE, FALSE)? Can it be applied to multinomial logistic regression? If yes, what's the formula for LL and U(beta_i)? Can someone point me to the right reference? Second, when I used *logistf *on a dataset with

Hi, I am using the densCols to draw a high volume scatter plot. Instead of using the default local density, I would like to take log of the local density and then map them to the colors. I could not figure out how to do that. For example: plot(x,y,col=densCols(x,y,"log")) ? Any help would be appreciated! Jiaxiu [[alternative HTML version deleted]]

Hello all! I have a data frame with nine variables and 293 cases. (attached goes the csv file). I need to calculate a index using the sum of one variable (N) divided by the length of other variable (Fisherman), but for each day (Date). I tried to use that codes: by (cpue, cpue$Date, function (x) sum (cpue$N)/length(cpue$Fisherman)) tapply (cpue$Data, cpue$Data, function (x) {sum

Dear Sir/Madam, I am encountering one of those alien computer momements one finds every so often in life. See the sequence below: > fish3.fis <-read.csv("emperor2.csv", check.names = TRUE, strip.white = TRUE) > colnames(fish3.fis) [1] "Month" "Year" "FishingArea" "SumOfTotalCatch" "CPUE" [6]

I am new to using R. Currently, I am using the logistf package to run logistic regression analysis. When I run the following line of code: attach(snpriskdata) logisticpaper<-logistf(sascasecon~saspackyrs+newsbmi+EDUCATION+sasagedx+sasflung+condobst+sasadultasprev) I get the following error message: Error in sum(y) : invalid 'type' (character) of argument What does this error

I have a plotted a stacked panel graph (single x axis and multiple y axis) using the package zoo and would like to add a title for each separate panel. I am using the script: z <- with(mydata,zoo(cbind(mydata$Water.level,mydata$Submerged.plants, mydata$Crayfish.CPUE,mydata$Carp.CPUE),Year)) plot(z,type="b",pch=16,lty=2,xlab="Year",ylab=c("Metres","Realtive

I'm having trouble with some catch per unit effort data (CPUE, fisheries data). Some of the samples were "retained" and some "unretained," and they are entered as 2 separate entries for the same sampling event (Date and time). I want to calculate the total CPUE (so sum the "retained" and "unretained" number for each sampling event) and am having troubld

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

Hi R users, I have a dataset with multiple variables and i'm trying to weigh average depths for fish species per year by their abundance (CPUE. I have tried the weighted.mean function but as i have two columns for the x value the lenghts differ with the w (CPUE). How do I solve this problem? So far I have tried this: data<-by(allspecies, list(allspecies$Depth, allspecies$Year),

Hi- I'm wrestling with some of my data apparently not being called into a GLM or an LM. I'm looking at factors affecting fish annual catch rates (ie. CPUE) over 30 years. Two of the factors I'm using are sea surface temperature and sea surface temperature anomaly. A small sample of my data is below: CPUE Year Vessel_ID Base_Port Boat_Lgth Planing SST Anomaly 0.127

Hi everyone, I have a problem with running a glm using a subset of my data. Whenever I choose a subset, in the summary the factors arent shown (as if the variable was a continuous variable). If I dont use subsets then all the factors are shown. I have copied the output from summary for both cases. Thanks for the help, Muri > model<-glm(log(cpue)~year,family=gaussian) Call: glm(formula =

Hi, I need to have both italics and standard font on the y axis. This is my script: plot(x,y,pch=16,xlab="metric",ylab="species CPUE") I want species in italics and CPUE in standard text. Any tips would be appreciated. Thanks. -- View this message in context: http://old.nabble.com/Different-fonts-on-the-same-axis-tp26482460p26482460.html Sent from the R help mailing list

Dear all, I'm trying to create a list of point patterns ppp.object {spatstat} in a loop. My dataset looks like this: > names(OT1);head(OT1);dim(OT1) [1] "EID" "latitude" "longitude" "month" "year" "CPUE" "TSUM" [8] "fTSUM" EID latitude longitude

Hola, Vaya desastre al mandar la cabecera de la base de datos. Al enviarlo, se veía bien, pero está visto que por el camino la cosa se torció. Siguiendo el consejo de Javier, he subido un pequeño fragmento al DropBox. He quitado algunas especies para no hacerlo muy largo. Espero que ésta vez no haya problemas. https://www.dropbox.com/s/q7zla50oq7owg8k/CPUE.csv?dl=0 Un saludo y gracias Juan

I'm having problems creating an axis label for a plot. y_label = expression(paste(plain('CPUE '),plain('(fish'),plain('x'),plain('h'^{-1}),plain(')'))) I'd like to replace the "x" with an interpunct symbol (dot). Any suggestions how to do this? Thanks in advance. [[alternative HTML version deleted]]

Hi -I'm running a GAM with 7 explanatory variables with a Poisson error structure. All of the variables are continuous so I'm getting error messages in R. cod.fall.full.gam.model<-gam(Kept.CPUE~s(HOUR)+s(LAT_dec)+s(LONG_dec)+s(meantemp_C)+s(meandepth_fa)+s(change_depth)+s(seds), data=cod.fall.version2,family=poisson) In dpois(y, mu, log = TRUE) ... : non-integer x = 5.325517

Hi, we try to do a logistic regression with the function glm. But we notice that this function don't give the same results as the SAS proc catmod (differents estimate given). We try to change the contrast on R system with: > options(contrasts=c(unordered="contr.SAS",ordered="contr.poly")) We also try with brlr and logistf functions. Unfortunately, the estimate

I''m running brglm with binomial loguistic regression. The perhaps multicollinearity-related feature(s) are: (1) the k IVs are all binary categorical, coded as 0 or 1; (2) each row of the IVs contains exactly C (< k) 1''s; (3) k IVs, there are n * k unique rows; (4) when brglm is run, at least 1 IV is reported as involving a singularity. I''ve tried recoding the n