Publications by Mauricio Rodriguez Abreu
LAT4'82_S19
Credibility and premium update Now, we can use the credibility approach to measure frequency and severity of claims and contrast them with new observed values. Use a coverage probability of 95% and a range around the true mean of 10% We can start with some data. setwd("~/Dropbox/UDLAP/Cursos/2022 Primavera/Tema Selecto/data") data<-read.csv("insa...
2501 sym R (1205 sym/38 pcs)
LAT4072_S19
R Markdown We will start with the same Markdown from last time… just because I really need to get the lif table and all other elements. setwd("~/Dropbox/UDLAP/Cursos/2022 Primavera/Pensiones y SS/Presentaciones") ciencias<-read.csv("ciencias.csv") Now, we define a benefit the following way: Retirement age: 60 Benefit: \[ 1.5\% \times SP \times...
3477 sym R (7343 sym/61 pcs)
LAT4072_S18
knitr::opts_chunk$set(echo = TRUE) I will recover the dataset that I created with people working for Sciences… from a couple of weeks ago. setwd("~/Dropbox/UDLAP/Cursos/2022 Primavera/Pensiones y SS/Presentaciones") sdem<-read.csv("ENOEN_SDEMT121.csv") sdem<-sdem[which(sdem$eda>=15 & sdem$eda<=97),] sdem<-sdem[which(sdem$c_res!=2),] table(sdem$...
194 sym R (5895 sym/9 pcs)
LAT4072_S17
#setwd("C:/Users/23043/Dropbox/UDLAP/Cursos/2022 Primavera/Pensiones y SS/Presentaciones") setwd("~/Dropbox/UDLAP/Cursos/2022 Primavera/Pensiones y SS/Presentaciones") lt<-read.csv("ILT1.csv") library(lifecontingencies) ## Package: lifecontingencies ## Authors: Giorgio Alfredo Spedicato [aut, cre] ## (<https://orcid.org/0000-0002-0315-8888...
1735 sym R (3060 sym/26 pcs) 4 img
LAT4082_S14
title: “LAT4082_S14” author: “Mauricio Rodriguez Abreu” date: “3/13/2022” output: html_document In this session we will continue with the use of GLM’s for claim frequency and will introduce the use of GLM’s for claim severity. We are going to use a new dataset, the dataset is called InsuranceClaims setwd("~/Dropbox/UDLAP/Cursos/20...
6456 sym R (28510 sym/84 pcs) 5 img 1 tbl
LAT3082_S12
R Markdown GLM’s for pricing… install.packages("CASdatasets", repos = "http://cas.uqam.ca/pub/", type="source") library("CASdatasets") ## Loading required package: xts ## Loading required package: zoo ## ## Attaching package: 'zoo' ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric ## Loading requir...
601 sym R (5326 sym/67 pcs)
LAT2072_ENOE
R Markdown In this session, we will learn how to use the ENOE, a really important survey collecting information on employment and occupations. This survey is the one you will have to use for your final project. setwd("~/Downloads/enoe_n_2021_trim1_csv") sdem<-read.csv("ENOEN_SDEMT121.csv") Remember, my advice is to always start with a basic anali...
4254 sym R (13899 sym/90 pcs)
LAT4082_S9
R Markdown Read the file on Claim Levels setwd("~/Dropbox/UDLAP/Cursos/2022 Primavera/Tema Selecto/Presentaciones") ClaimLev <- read.csv("CLAIMLEVEL.csv") head(ClaimLev) ## PolicyNum ClaimNum Year ClaimStatus Claim Deduct EntityType ## 1 120002 20100192 2010 Closed 6838.87 1000 County ## 2 120003 20080726 2007 Closed 20...
923 sym R (7621 sym/53 pcs) 3 img
LAT4082_S8
R Markdown Aggregate loss models: x<-c(0:10) plot(pgamma(x,2,1),type="l") We can use any of the discretisation techniques library(actuar) ## Warning: package 'actuar' was built under R version 4.1.2 ## ## Attaching package: 'actuar' ## The following objects are masked from 'package:stats': ## ## sd, var ## The following object is maske...
522 sym R (2537 sym/21 pcs) 7 img
LAT4072_S7
Multiple decrements example setwd("C:/Users/23043/Dropbox/UDLAP/Cursos/2022 Primavera/Pensiones y SS/Datos") data<-read.csv("MDM.csv") head(data) ## Age Inv Death DInv DNInv Ces Ret ## 1 0 0 0 0 0 0 0 ## 2 1 0 0 0 0 0 0 ## 3 2 0 0 0 0 0 0 ## 4 3 0 0 0 0 0 0 ## 5...
1154 sym R (6561 sym/30 pcs) 1 img