search for: xlong

...-------- library(lattice); #multivariate time series, one row for each hour of the week: Xwide = cbind.data.frame(time=as.POSIXct("2010-09-06 00:00:00 EDT") + (0:167)*3600, Comp.1= sin(2*pi*7*(0:167)/168), Comp.2 = cos(2*pi*7*(0:167)/168)); #to pass this to xyplot, first need to reshape: Xlong <- reshape(Xwide, varying = c(2:3), idvar = "time", direction="long", timevar = "PC"); #get descriptive shingle labels Xlong[,"PC"] <- factor(Xlong[,"PC"], labels = paste("PC",1:2)); xyplot(Comp ~ time | PC ,data = Xlong, pane1l = W...

...lation on a marked spatial point process (cases and controls). I use the mgcv package to fit a GAMM model with a binary outcome, a parametric part (var1+..+varn), a spline used for the spatial variation, and a random effect coded through another spline in this form: gam(outcome~var1+.+varn+s(xlong+ylat)+s(var, bs="re"), data=MyData, family=binomial(link=logit)) My purpose is to calculate a risk map adjusted on my covariates to look for compare and look for obvious differences with a risk map calculated by kernel ratio. However...the big deal is to interpolate my model to estim...