Remove user specific folders

gpitt71 · Nov 13, 2023 · 684662a · 684662a
1 parent f9fa857
commit 684662a
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Showing 5 changed files with 12 additions and 41 deletions.
diff --git a/figure_2.R b/figure_2.R
@@ -5,7 +5,7 @@ library(dplyr)
 library(ChainLadder)
 library(ggplot2)
 library(scales)
-source('C:\\Users\\gpitt\\Documents\\GitHub\\conditional-aj-reserving\\helper_functions_ajr.R')
+source('conditional-aj-reserving\\helper_functions_ajr.R')
 unit=1e+06
 
 # width 4 ----

diff --git a/table_4_feature_model.R b/table_4_feature_model.R
@@ -109,16 +109,6 @@ data.list.ref <- lapply(data2fit, function(x){x[[3]]<-unique(x[[3]])
                                                 })
 
 
-# for(k in 4:(maximum.p)){
-#   
-#   cat(paste0('State space with k '),as.character(k),'\n')
-#   
-#   if(k!=8){
-#   data.list.ref <- lapply(data2fit,reformulate_state_space_X,newk = k)
-#   
-#   }else{
-#     
-#     data.list.ref <-data2fit}
 
   rbns.data <- rbns.claims.fit[,times:=cumsum(times),by=Claim_number][,.(k=last(times)),by=.(Claim_number)]
 
@@ -138,19 +128,14 @@ data.list.ref <- lapply(data2fit, function(x){x[[3]]<-unique(x[[3]])
 
   rbns.data <-merge(actual,rbns.data,by='Claim_number')
 
-  # out <- rbns.data[,c('ultimate','variance','crps_i'):=individual_resultsX(k,X=X,data.list),by=.(id)]
-
+
   out <- rbns.data[,c('ultimate','variance','crps_i'):=individual_results_X_w_pre_saved_models(k,
                                                                                                true.ultimate=true.ultimate,
                                                                                                X=Claim_type_key ,
                                                                                                models.list), 
                    by=.(Claim_number)]
 
-  # out <- rbns.data[,c('ultimate','variance','crps_i'):=individual_results_X_w_pre_saved_models(k,
-  #                                                                                              X=Claim_type_key,
-  #                                                                                              models.list), 
-  #                  by=.(Claim_number)]
-
+
 
   actual.uc=df %>%
     ungroup() %>%
@@ -269,7 +254,7 @@ colnames(results) <- c("k",
 
 results %>% xtable::xtable(digits=3) %>%print(include.rownames=FALSE)
 
-fname <- paste0("C:\\Users\\gpitt\\Documents\\GitHub\\conditional-aj-reserving\\results_csv\\real_data_w_features_",
+fname <- paste0("conditional-aj-reserving\\results_csv\\real_data_w_features_",
                 "_",
                  format(Sys.time(), 
                  "%Y_%m_%d_%H_%M"),

diff --git a/table_4_intercept_model.R b/table_4_intercept_model.R
@@ -123,8 +123,6 @@ out <- rbns.data[,c('ultimate','variance','crps_i'):=individual_results_nf(k,
                                                                            yhat=yhat), 
                  by=.(Claim_number)]
 
-# out <- rbns.data[,.(ultimate=k+individual_cost_nf(k,x.vals,yhat),
-#                     variance=individual_vty_nf(k,x.vals,yhat)),by=.(Claim_number)]
 
 fj <- NULL
 
@@ -179,10 +177,6 @@ actual.uc=df %>%
   filter(accident_period<=(maximum.p-2)&development_period<=(maximum.p-1)) %>%
   summarise(uc=sum(incPaid)) %>% unlist()
 
-# crps_data <- full_join(x = out, y = rbns.data, by = "Claim_number")[order(Claim_number),]
-# out_crps <- crps_data[,.(crps_i=crps_computer(k=k,y=ultimate,x=x.vals,cdf_i=yhat)),by=.(Claim_number)]
-
-
 
 cl.data <- find.t.data(df)
 cl.tot <- cl.calculator(incr2cum(cl.data))
@@ -218,7 +212,7 @@ colnames(results) <- c("k",
 results %>% xtable::xtable(digits=3) %>%print( include.rownames=FALSE)
 
 
-fname <- paste0("C:\\Users\\gpitt\\Documents\\GitHub\\conditional-aj-reserving\\results_csv\\real_data_no_features_",
+fname <- paste0("conditional-aj-reserving\\results_csv\\real_data_no_features_",
                 "_",
                 format(Sys.time(), 
                        "%Y_%m_%d_%H_%M"),

diff --git a/table_6_feature_model.R b/table_6_feature_model.R
@@ -5,14 +5,14 @@ library(dplyr)
 library(ChainLadder)
 library(ggplot2)
 
-source('C:\\Users\\gpitt\\Documents\\GitHub\\conditional-aj-reserving\\helper_functions_ajr.R')
+source('conditional-aj-reserving\\helper_functions_ajr.R')
 
 # Construct the model ----
 results = matrix(ncol=9)  
 maximum.p <- 6
 for(max.k in 4:(maximum.p)){
 
-df = read.and.pp.data(fname='C:\\Users\\gpitt\\Documents\\Phd\\visiting\\dati\\data_ku\\final_claim_data.csv')
+df = read.and.pp.data(fname='final_claim_data.csv')
 
 df = df %>% mutate(incPaid=incPaid)
 
@@ -147,20 +147,14 @@ ibnr.claims<-ibnr.claims %>%
 
   rbns.data <-merge(actual,rbns.data,by='Claim_number')
 
-  # out <- rbns.data[,c('ultimate','variance','crps_i'):=individual_resultsX(k,X=X,data.list),by=.(id)]
-
+
   out <- rbns.data[,c('ultimate','variance','crps_i'):=individual_results_X_w_pre_saved_models(k,
                                                                                                true.ultimate=true.ultimate,
                                                                                                X=Claim_type_key ,
                                                                                                models.list), 
                    by=.(Claim_number)]
 
-
-  # out <- rbns.data[,c('ultimate','variance','crps_i'):=individual_results_X_w_pre_saved_models(k,
-  #                                                                                              X=Claim_type_key,
-  #                                                                                              models.list), by=.(Claim_number)]
-  # 
-  # 
+
   actual.uc=df %>%
     ungroup() %>%
     filter(accident_period<=(maximum.p-2)&development_period<=(maximum.p-1)) %>%
@@ -272,7 +266,7 @@ colnames(results) <- c("k",
 
 results %>% xtable::xtable(digits=3) %>%print(include.rownames=FALSE)
 
-fname <- paste0("C:\\Users\\gpitt\\Documents\\GitHub\\conditional-aj-reserving\\results_csv\\real_data_w_features_",
+fname <- paste0("conditional-aj-reserving\\results_csv\\real_data_w_features_",
                 'maxp_',
                 maximum.p,
                 "_",

diff --git a/table_6_intercept_model.R b/table_6_intercept_model.R
@@ -5,7 +5,7 @@ library(dplyr)
 library(ChainLadder)
 library(ggplot2)
 
-source('C:\\Users\\gpitt\\Documents\\GitHub\\conditional-aj-reserving\\helper_functions_ajr.R')
+source('conditional-aj-reserving\\helper_functions_ajr.R')
 
 # Construct the model ----
 
@@ -202,8 +202,6 @@ actual.uc=df %>%
   filter(accident_period<=(maximum.p-2)&development_period<=(maximum.p-1)) %>%
   summarise(uc=sum(incPaid)) %>% unlist()
 
-# crps_data <- full_join(x = out, y = rbns.data, by = "Claim_number")[order(Claim_number),]
-# out_crps <- crps_data[,.(crps_i=crps_computer(k=k,y=ultimate,x=x.vals,cdf_i=yhat)),by=.(Claim_number)]
 
 
 
@@ -242,7 +240,7 @@ colnames(results) <- c("k",
 results %>% xtable::xtable(digits=3) %>%print( include.rownames=FALSE)
 
 
-fname <- paste0("C:\\Users\\gpitt\\Documents\\GitHub\\conditional-aj-reserving\\results_csv\\real_data_no_features_",
+fname <- paste0("conditional-aj-reserving\\results_csv\\real_data_no_features_",
                 'maxp_',
                 maximum.p,
                 "_",