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    Sunseeker

    @Sunseeker

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    • Modelling claim frequency R 問題
      library(ggplot2)
      library(dplyr)
      library(class)
      library(MASS)
      library(caret)
      library(devtools)
      library(countreg)
      library(forcats)
      library(AER)
      library(pscl)
      install.packages("countreg", repos="http://R-Forge.R-project.org")
      #Attaching data for modeling
      data(dataCar)
      data1 <- dataCar
      #Data Cleaning & Pre-processing
      data2 <- unique(data1)
      data3 <- data2[data2$veh_value > quantile(data2$veh_value, 0.0001),] 
      data4 <- data3[data3$veh_value < quantile(data3$veh_value, 0.999), ]
      #Regrouping vehicle categories
      top9 <- c('SEDAN','HBACK','STNWG','UTE','TRUCK','HDTOP','COUPE','PANVN','MIBUS')
      data4$veh_body <- fct_other(data4$veh_body, keep = top9, other_level = 'other')
      #Converting catagorical variables into factors
      names <- c('veh_body' ,'veh_age','gender','area','agecat')
      data4[,names] <- lapply(data4[,names] , factor)
      str(data4)
      ##data partition - original data
      data <- data4
      data_partition <- createDataPartition(data$numclaims, times = 1,p = 0.8,list = FALSE)
      str(data_partition)
      training <- data[data_partition,]
      testing  <- data[-data_partition,]
      #Re-sampling
      sample1 <- subset(data4, numclaims!=0)
      sample2 <- data4[ sample( which(data4$numclaims==0), 
                                round(0.9*length(which(data4$numclaims==0)))), ]
      sample3 <- data4[ sample( which(data4$numclaims==0), 
                                round(0.1*length(which(data4$numclaims==0)))), ]
      y <- rnbinom(n = 6323, mu = 1, size = 3) # n value should be equal to sample 3
      sample3$numclaims <- y
      df_sample <- rbind(sample1,sample2,sample3)
      

      我在學習怎麼用R 去模擬claim frequency 在網上看見這個例子 開始在最後的

      y <- rnbinom(n = 6323, mu = 1, size = 3) # n value should be equal to sample 3
      sample3$numclaims <- y
      df_sample <- rbind(sample1,sample2,sample3)
      

      我在學習怎麼用R 去模擬claim frequency 在網上看見這個例子 開始在y <- rnbinom(n = 6323, mu = 1, size = 3) # n value should be equal to sample 3 sample3$numclaims <- y df_sample <- rbind(sample1,sample2,sample3)
      我在學習怎麼用R 去模擬claim frequency 在網上看見這個例子 開始在最後的random negative binomial simulation 裡面 mu=1 和 size=3 是怎麼得出的呢?
      還有df_sample 是什麼意思?
      有大神可以指教一下? 抱歉 新手用R 嘗試自己理解

      发布在 R
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      Sunseeker