similar to: Logistic Regression with Offset value

Dear R friends I´m interested into apply a Jackknife analysis to in order to quantify the uncertainty of my coefficients estimated by the logistic regression. I´m using a glm(family=’binomial’) because my independent variable is in 0 - 1 format. My dataset has 76000 obs, and I´m using 7 independent variables plus an offset. The idea involves to split the data in let’s say 5 random subsets and

Dear R friends. I have a question about running a glm( family= 'binomial', *offset=T*), (I know offset is a vector of values) My doubt is about predicting the values on a new data. Does the predict() function considers the offset? o should I especified something? Here is the model I´m using: *model<-stepAIC(glm(f_ocur~altitud+UTM_X+UTM_Y+j_sin+j_cos+temp_res+pp, offset=(log(1/offset))

Hello Trying to develop variograms and kriged surfaces from a point file. Here is what I've done so far. library(gstat) # also loads library(sp) library(lattice) soilpts$x <- soilpts$UTM_X soilpts$y <- soilpts$UTM_Y soil.dat <- subset(soilpts, select=c(x, y, Area, BulkDensity, LOI, TP, TN, TC, Total_Mg)) dim(soil.dat) [1] 1292 7 coordinates(soil.dat) <- ~ x+y

Hola a todos! Estoy intentando crear un vector (alt) a partir de la repetición de valores provenientes de otro vector (altitud). A cada valor de altitud lo quiero repetir 1247 veces, y de ahi continuar con el siguiente valor de altitud. Probé varias cosas, pero esto me pareció lo más coherente: altitud=read.csv("C:/Users/IER/Dropbox/Pasantia Castelar/YungasLigustroTS/altitud44.csv")

Hi guys i found this encryption decryption in php and try to convert it in rails but i am unable to successfully convert it. So plz help me. I you write the whole conversion code then it will be great. PHP code is like this ================ # #/********************************************** #** #** MD5 block cypher #** #** Author..: leapinglangoor [

Dear r-list: I am using rpart to build a tree on a dataset. First I obtain a perhaps too large tree: > arbol.bsvg.02 <- rpart(formula, data = bsvg, subset=grp.entr, control=rpart.control(cp=0.001)) > arbol.bsvg.02 n= 100000 node), split, n, loss, yval, (yprob) * denotes terminal node 1) root 100000 6657 0 (0.93343000 0.06657000) 2) meses_antiguedad_svg>=10.5 73899 3658

Hi R community I need to interpolate precipitation data for a natural park. I have precipitation data from some climate stationts. (I know the table is not complete but I only need to show you X,Y, Altitude and PrepJul) X Y Altitude PrepJan PrepFeb PrepMar PrepAp PrepMay PrepJun PrepJul 597706 4093438 41 0 9 77,8 63,1 17,5 0 2,6 597535

Hi R-experts, I am using the envfit function over an ordination of floristic data. The problem is that every time that I run it changes the results. Sometimes dramatically, selecting variables that the first time were not significant. I do not get what could be the problem or if is normal given the permutations are different. # the NMDS ordination gap_flor_NMDS_chord <- metaMDS(gaps_flor,