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Revision 98a32cf9

Added by Benoit Parmentier about 11 years ago

running kriging fusion with 0 to 10% monthly holdout for multitimescale paper, OR

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climate/research/oregon/interpolation/master_script_temp.R
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#STAGE 5: Output analyses: assessment of results for specific dates...
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#
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#AUTHOR: Benoit Parmentier                                                                       
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#DATE: 09/11/2013                                                                                 
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#DATE: 09/12/2013                                                                                 
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#PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363, TASK$568--   
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......
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#met_stations_outfiles_obj_file<-"met_stations_outfiles_obj_gam_CAI__365d_gam_CAI_lst_comb3_08252013.RData"
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var<-"TMAX" # variable being interpolated
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out_prefix<-"_365d_gam_fus_lst_comb3_09112013"                #User defined output prefix
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out_suffix<-"_OR_09112013"                                       #Regional suffix
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out_prefix<-"_365d_kriging_fus_lst_comb3_09122013"                #User defined output prefix
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out_suffix<-"_OR_09122013"                                       #Regional suffix
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out_suffix_modis <-"_05302013"                       #pattern to find tiles produced previously     
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#interpolation_method<-c("gam_fusion","gam_CAI","gam_daily") #other otpions to be added later
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#interpolation_method<-c("gam_CAI") #other otpions to be added later
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interpolation_method<-c("gam_fusion") #other otpions to be added later
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#interpolation_method<-c("kriging_fusion") #other otpions to be added later
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#interpolation_method<-c("gam_fusion") #other otpions to be added later
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interpolation_method<-c("kriging_fusion") #other otpions to be added later
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#interpolation_method<-c("gwr_fusion") #other otpions to be added later
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#interpolation_method<-c("gwr_CAI") #other otpions to be added later
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#interpolation_method<-c("kriging_CAI") 
......
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nb_sample_month <-1           #number of time random sampling must be repeated for every hold out proportion
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step_month <-0.1         
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constant_month <-0             #if value 1 then use the same samples as date one for the all set of dates
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prop_minmax_month <-c(0.4,0.7)  #if prop_min=prop_max and step=0 then predictions are done for the number of dates...
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prop_minmax_month <-c(0,0.1)  #if prop_min=prop_max and step=0 then predictions are done for the number of dates...
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#dates_selected<-c("20100101","20100102","20100103","20100901") # Note that the dates set must have a specific format: yyymmdd
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#dates_selected<-c("20100101","20100102","20100301","20100302","20100501","20100502","20100701","20100702","20100901","20100902","20101101","20101102")
......
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#LC1: Evergreen/deciduous needleleaf trees
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#Combination 3: for paper baseline=s(lat,lon)+s(elev)
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list_models<-c("y_var ~ s(lat,lon) + s(elev_s)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(N_w)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(E_w)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(LST)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(DISTOC)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(LC1)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(CANHGHT)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(LST) + ti(LST,LC1)",
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                "y_var ~ s(lat,lon) + s(elev_s) + s(LST) + ti(LST,CANHGHT)")
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#list_models<-c("y_var ~ s(lat,lon) + s(elev_s)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(N_w)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(E_w)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(LST)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(DISTOC)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(LC1)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(CANHGHT)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(LST) + ti(LST,LC1)",
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#                "y_var ~ s(lat,lon) + s(elev_s) + s(LST) + ti(LST,CANHGHT)")
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#Combination 4: for paper baseline=s(lat,lon)
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# list_models<-c("y_var ~ s(lat,lon)",
......
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#list_models<-c("y_var ~ s(lat,lon) + s(elev_s)")
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# list_models<-c("y_var ~ lat*lon + elev_s",
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#                "y_var ~ lat*lon + elev_s + N_w",
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#                "y_var ~ lat*lon + elev_s + E_w",
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#                "y_var ~ lat*lon + elev_s + LST",
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#                "y_var ~ lat*lon + elev_s + DISTOC",
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#                "y_var ~ lat*lon + elev_s + LC1",
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#                "y_var ~ lat*lon + elev_s + CANHGHT",
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#                "y_var ~ lat*lon + elev_s + LST + I(LST*LC1)",
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#                "y_var ~ lat*lon + elev_s + LST + I(LST*CANHGHT)")
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list_models<-c("y_var ~ lat*lon + elev_s",
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               "y_var ~ lat*lon + elev_s + N_w",
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               "y_var ~ lat*lon + elev_s + E_w",
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               "y_var ~ lat*lon + elev_s + LST",
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               "y_var ~ lat*lon + elev_s + DISTOC",
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               "y_var ~ lat*lon + elev_s + LC1",
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               "y_var ~ lat*lon + elev_s + CANHGHT",
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               "y_var ~ lat*lon + elev_s + LST + I(LST*LC1)",
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               "y_var ~ lat*lon + elev_s + LST + I(LST*CANHGHT)")
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#Default name of LST avg to be matched               
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lst_avg<-c("mm_01","mm_02","mm_03","mm_04","mm_05","mm_06","mm_07","mm_08","mm_09","mm_10","mm_11","mm_12")  

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