#STAGE 5: Output analyses: assessment of results for specific dates...

#

#AUTHOR: Benoit Parmentier                                                                       

#PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363, TASK$568--   

##SCRIPT USED FOR THE PREDICTIONS: Source or list all scripts here to avoid confusion on versions being run!!!!

#CALLED FROM MASTER SCRIPT:

#met_stations_outfiles_obj_file<-"met_stations_outfiles_obj_kriging_daily__365d_kriging_daily_mults10_lst_comb3_08062013.RData"

var<-"TMAX" # variable being interpolated

out_suffix_modis <-"_05302013"                       #pattern to find tiles produced previously     

#interpolation_method<-c("gam_fusion","gam_CAI","gam_daily") #other otpions to be added later

#interpolation_method<-c("gam_CAI") #other otpions to be added later

#interpolation_method<-c("kriging_fusion") #other otpions to be added later

#interpolation_method<-c("gwr_fusion") #other otpions to be added later

#interpolation_method<-c("gwr_CAI") #other otpions to be added later

#interpolation_method<-c("kriging_CAI") 

#interpolation_method<-c("kriging_daily") #other otpions to be added later

#interpolation_method<-c("gwr_daily") #other otpions to be added later

#Set additional parameters

#Input for sampling function...

seed_number<- 100  #if seed zero then no seed?     

constant<-0             #if value 1 then use the same samples as date one for the all set of dates

#dates_selected<-c("20100101","20100102","20100103","20100901") # Note that the dates set must have a specific format: yyymmdd

screen_data_training<-FALSE #screen training data for NA and use same input training for all models fitted

#Models to run...this can be changed for each run

#LC1: Evergreen/deciduous needleleaf trees

#Combination 3: for paper baseline=s(lat,lon)+s(elev)

#list_models<-c("y_var ~ lat*lon + elev_s")

#list_models<-c("y_var ~ lat*lon + elev_s",

#              "y_var ~ lat*lon + elev_s + N_w",