Hi Simon, I have been attempting a similar thing as you, but using the glsm.krige function, without success. From what i can work out the the output.glm.control() settings are sent to the .cond.sim function from geoR, which is doing something different to what you are after (I believe). I have had a brief look at the binom.krige.bayes function, and it appears the median of the values is performed within the sub function .pred.quan.aux function on the first line
temp.med <- apply(temp.pred$mean, 1, median) I assume that it would be possible for you to adjust this function to get it to do what you want, but i am unsure about that, as i have been using the glsm.krige function. If you try to re-run your code with a smaller prediction grid (50 points), the output.glm.control function will most likely work for you, however i have waited over a day for 8000 points with no luck. Jason On 25/11/10 00:04, O'Hanlon, Simon J wrote: > Dear List, > I have been using geoRglm to perform spatial prediction in the binomial-logit > spatial model. > > I have been able to produce maps of some predicted volumetric quantity > (prevalence) over a wide geographic area (2385km * 1375km in 131,175 5km > cells) , using covariates in the fixed part of the model. Using the function > binom.krige.bayes produces output which includes an estimate of the > predictive median for each cell in the map. This is specified when setting > 'inference=TRUE' in the control function called 'output.glm.control' which is > called by binom.krige.bayes. > > However the median is only one map of the posterior distribution of the > estimated quantity. I want to look at some of the other maps, including the > mean map of the predicted. In order to do this I need to get the posterior > prediction of the prevalence for each map cell for each iteration of the > simulation. Then for each cell I can calculate the mean etc. In order to do > this there is a TRUE/FALSE switch called 'sim.predict' in the control > function 'output.glm.control'. When set to false you simply return the > predictive median. When set to TRUE you should return the values of the > predictied quantity for each iteration of the model. When I set this to true > RGui crashes with no warning or error messages (even when verbose mode is > turned on). R is not using it vector or stack heaps, and I am only using 8GB > out of 16GB of system ram. Also the table which should be dimensioned to hold > the predictions is well inside the limits placed by R (i.e. a table with less > than 2^31-1 elemen! ts! > ). I am running 150,000 iterations of a model , predicting over 131,175 map > cells, and I have thinning set to 100 (to minimise autocorrelation between > simulations), so I should be recording 1500 simulation results (150,000 / > 100). > > Has this problem happened to anybody else and does anybody know of another > way to record the predictive posterior draws of the simulations? > > Much obliged and sorry if I have not used appropriate jargon in places - I am > relatively new to this. > > Cheers, > > Simon > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
