[R] Jackknife in Logistic Regression

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 independe

[R] Logistic Regression with Offset value

Dear R friends. I´m trying to fit a Logistic Regression using glm( family='binomial'). Here is the model: *model<-glm(f_ocur~altitud+UTM_X+UTM_Y+j_sin+j_cos+temp_res+pp, offset=(log(1/off)), data=mydata, family='binomial')* mydata has 76820 observations. The response variable f_ocur) is a 0-1. Thi

[R] Logistic Regression with Offset value

Dear R friends. I´m trying to fit a Logistic Regression using glm( family='binomial'). Here is the model: *model<-glm(f_ocur~altitud+UTM_X+UTM_Y+j_sin+j_cos+temp_res+pp, offset=(log(1/off)), data=mydata, family='binomial')* mydata has 76820 observations. The response variable f_ocur) is a 0-1. Thi

[R] predict glm() with offset

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: *mod

[R] ffsave problems

Dear R friends. After having some troubles learning how to create a ffdf object, now I find myself having problems saving it. this is the data i´d like to save: str(DATA) List of 3 $ virtual: 'data.frame': 6 obs. of 7 variables: .. $ VirtualVmode : chr "double" "short" "integer" "integer"

[R] ffbase, help with %in%

Hello to everyone. I'm trying to use the %in% to match to vectors in ff format. a<-as.ff(data[,1]) %in% fire$fecha > aff (open) logical length=3653 (3653) [1][2][3][4][5][6][7][8][3646] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE : FALSE [36

[R] Deldir() Thiessen Polygons Problem

Good evening to all. I find myself trying to create some Thiessen Polygons, in order to finish a meteorology research. This is the script I found to create the Polygons: * * *voronoipolygons <- function(x) {* * require(deldir)* * if (.hasSlot(x, 'coords')) {* *crds <- x@coords * *} else