Rename functions and lists

SPLICE/.Rhistory

@@ -1,172 +1,3 @@
-View(indicator)
-View(as.numeric(indicator))
-View(as.factor(indicator))
-View(output_actual[indicator])
-View(output_actual *indicator)
-View(upper.tri(output_actual[, 1:40], diag = TRUE))
-output_actual[!indicator] <- NA
-View(output_actual)
-x <- output_noinflation
-View(x[!indicator])
-x[!indicator] <- NA
-View(x)
-View(output_noinflation)
-document()
-?output_incurred
-vignette("SPLICE-demo", package = "SPLICE")
-vignette("SynthETIC-demo", package = "SynthETIC")
-?vignette
-# incurred triangles
-# Constant dollar value INCREMENTAL triangle
-incurred_noInf <- incurred_output(test, incremental = TRUE)
-# incurred triangles
-# Constant dollar value INCREMENTAL triangle
-incurred_noInf <- output_incurred(test, incremental = TRUE)
-View(incurred_noInf)
-incurred_noInf <- output_incurred(test, incremental = TRUE, aggregate_level = 2)
-View(incurred_noInf)
-incurred_noInf <- output_incurred(test, incremental = F)
-incurred_noInf <- output_incurred(test, incremental = F, future = F)
-View(incurred_noInf)
-load_all()
-incurred_noInf <- output_incurred(test, incremental = F, future = F)
-View(incurred_noInf)
-load_all()
-incurred_noInf <- output_incurred(test, incremental = F, future = F)
-View(incurred_noInf)
-ceiling(1:10)
-ceiling(1:10 / 4)
-40 + 40 - 1
-?output_incurred
-i <- 1
-j <- 1
-incurred_history <- test
-# convert to discrete time scale (t in terms of absolute time)
-t <- ceiling(incurred_history[[i]][[j]]$txn_time / aggregate_level)
-aggregate_level <- 4
-# convert to discrete time scale (t in terms of absolute time)
-t <- ceiling(incurred_history[[i]][[j]]$txn_time / aggregate_level)
-t
-incurred_right <- incurred_history[[i]][[j]]$incurred_right
-i_rescaled <- 1
-side <- 10
-# Now get the latest incurred estimate in a period
-incurred_latest <- rep(NA, i_rescaled + side - 1)
-incurred_latest
-# Fill the incurred estimates
-incurred_latest[unique(t)] <- incurred_right[!rev(duplicated(rev(t)))]
-incurred_latest
-# Fill the NAs prior to the first non-NA with 0
-# (i.e. assume no incurred until claim notified)
-firstNonNA <- min(which(!is.na(incurred_latest)))
-firstNonNA
-i <- 40
-i_rescaled <- 10
-# convert to discrete time scale (t in terms of absolute time)
-t <- ceiling(incurred_history[[i]][[j]]$txn_time / aggregate_level)
-t
-incurred_right <- incurred_history[[i]][[j]]$incurred_right
-# Now get the latest incurred estimate in a period
-incurred_latest <- rep(NA, i_rescaled + side - 1)
-# Fill the incurred estimates
-incurred_latest[unique(t)] <- incurred_right[!rev(duplicated(rev(t)))]
-incurred_latest
-unique(t)
-i_rescaled <- ceiling(i / 4)
-i_rescaled
-load_all()
-View(incurred_inflated)
-x <- incurred_inflated
-y <- output_incurred(test_inflated, incremental = TRUE)
-load_all()
-y <- output_incurred(test_inflated, incremental = TRUE)
-sum(x == y)
-sum(x != y)
-View(x)
-View(y)
-View(test_inflated)
-test_inflated[[1]][[1]]
-set.seed(20201006)
-test_claims <- SynthETIC::test_claims_object
-major <- claim_maRev_no(test_claims)
-major <- claim_maRev_time(test_claims, major)
-major <- claim_maRev_size(major)
-# minor revisions
-minor <- claim_miRev_no(test_claims)
-minor <- claim_miRev_time(test_claims, minor)
-minor <- claim_miRev_size(test_claims, major, minor)
-test <- claim_history(test_claims, major, minor)
-test_inflated <- claim_history(test_claims, major, minor, inflated = TRUE,
-base_inflation_vector = rep((1 + 0.02)^(1/4) - 1, times = 80))
-test_inflated[[1]][[1]]$miRev
-test_inflated[[1]][[1]]$incurred_right
-major[[1]][[1]]
-major[[1]][[2]]
-major[[1]][[29]]
-# Incurred triangles
-incurred_output <- function(
-incurred_history,
-aggregate_level = 1,
-incremental = TRUE) {
-frequency_vector <-  lengths(incurred_history)
-I <- length(frequency_vector)
-incurred_cumulative <- array(0, c(I, I))
-adjustment <- 0 # track the number of corrections required for keeping all the
-# transaction times within the bound
-for (i in 1:I) {
-for (j in 1:frequency_vector[i]) {
-# convert to discrete time scale (t in terms of absolute time)
-t <- ceiling(incurred_history[[i]][[j]]$txn_t)
-incurred_right <- incurred_history[[i]][[j]]$incurred_right
-# Firstly need to treat the out-of-bound transaction times
-if (any(t - i + 1 > I)) {
-t[which(t - i + 1 > I)] <- i + I - 1
-adjustment <- adjustment + 1
-}
-# Now get the latest incurred estimate in a period
-incurred_latest <- rep(NA, i + I - 1)
-# Fill the incurred estimates
-incurred_latest[unique(t)] <- incurred_right[!rev(duplicated(rev(t)))]
-# Fill the NAs prior to the first non-NA with 0
-# (i.e. assume no incurred until claim notified)
-firstNonNA <- min(which(!is.na(incurred_latest)))
-if (firstNonNA > i) {
-incurred_latest[i:(firstNonNA - 1)] <- 0
-}
-# Fill the rest of NAs with the prior non-NAs
-incurred_latest <- zoo::na.locf(incurred_latest, na.rm = TRUE)
-for (k in 1:I) {
-incurred_cumulative[i, k] <- incurred_cumulative[i, k] + incurred_latest[k]
-}
-}
-}
-no_txn <- lengths(lapply(unlist(incurred_history, recursive = F), `[[`, "txn_time"))
-total_no_txn <- sum(no_txn)
-if (adjustment / total_no_txn > 0.03) {
-warning("More than 3% of the transactions were outside the bound.")
-}
-if (aggregate_level != 1) {
-# if aggregate at a higher level (e.g. aggregate_level = 4 for yearly triangles)
-new_side_length <- I / aggregate_level
-incurred_cumulative_orig <- incurred_cumulative
-incurred_cumulative <- array(0, c(new_side_length, new_side_length))
-for (i in 1:new_side_length) {
-side_occurrence <- (aggregate_level * (i-1) + 1): (aggregate_level * i)
-for (j in 1:new_side_length) {
-side_development <- aggregate_level * j
-incurred_cumulative[i, j] <- sum(
-incurred_cumulative_orig[side_occurrence, side_development])
-}
-}
-}
-if (incremental == TRUE) {
-incurred_incremental <- incurred_cumulative
-for (i in 1:dim(incurred_cumulative)[1]) {
-incurred_incremental[i, 1] <- incurred_cumulative[i, 1]
-for (j in 2:dim(incurred_cumulative)[2]) {
-incurred_incremental[i, j] <- incurred_cumulative[i, j] - incurred_cumulative[i, j - 1]
-}
-}
 incurred_incremental
 } else {
 incurred_cumulative
@@ -510,3 +341,172 @@ major <- claim_maRev_no(test_claims)
 major <- claim_maRev_time(test_claims, major)
 major <- claim_maRev_size(major)
 major[[1]][[29]]
+## generated with default assumptions
+library(SynthETIC)
+set.seed(20200131)
+n_vector <- claim_frequency(I = 40, E = 12000, freq = 0.1)
+occurrence_times <- claim_occurrence(n_vector)
+claim_sizes <- claim_size(n_vector)
+notidel <- claim_notification(n_vector, claim_sizes)
+setldel <- claim_closure(n_vector, claim_sizes)
+no_payments <- claim_payment_no(n_vector, claim_sizes)
+payment_sizes <- claim_payment_size(n_vector, claim_sizes, no_payments)
+payment_delays <- claim_payment_delay(n_vector, claim_sizes, no_payments, setldel)
+payment_times <- claim_payment_time(n_vector, occurrence_times, notidel, payment_delays)
+base_inflation_vector <- rep((1.02)^(1/4) - 1, times = 80)
+payment_inflated <- claim_payment_inflation(
+n_vector, payment_sizes, payment_times, occurrence_times,
+claim_sizes, base_inflation_vector)
+# generate datasets
+# claim level data
+claim_dataset <- generate_claim_dataset(
+frequency_vector = n_vector,
+occurrence_list = occurrence_times,
+claim_size_list = claim_sizes,
+notification_list = notidel,
+settlement_list = setldel,
+no_payments_list = no_payments
+)
+# payment level data
+test_claims <- claims(
+n_vector, occurrence_times, claim_sizes, notidel, setldel, no_payments,
+payment_sizes, payment_delays, payment_times, payment_inflated)
+transaction_dataset <- generate_transaction_dataset(
+test_claims,
+adjust = FALSE # to keep the original simulated payment times
+)
+write.csv(claim_dataset, "~/Downloads/claim_dataset_20210825.csv")
+write.csv(transaction_dataset, "~/Downloads/payment_dataset_inflated_20210825.csv")
+## With SPLICE loaded (locally)
+major <- claim_maRev_no(test_claims)
+library(devtools)
+load_all()
+## With SPLICE loaded (locally)
+major <- claim_maRev_no(test_claims)
+major <- claim_maRev_time(test_claims, major)
+major <- claim_maRev_size(major)
+# minor revisions
+minor <- claim_miRev_no(test_claims)
+minor <- claim_miRev_time(test_claims, minor)
+minor <- claim_miRev_size(test_claims, major, minor)
+test <- claim_history(test_claims, major, minor)
+test_inflated <- claim_history(test_claims, major, minor, inflated = TRUE,
+base_inflation_vector = rep((1 + 0.02)^(1/4) - 1, times = 80))
+test_inflated <- claim_history(test_claims, major, minor,
+base_inflation_vector = rep((1 + 0.02)^(1/4) - 1, times = 80))
+test_incurred_dataset <- generate_incurred_dataset(test_claims, test)
+test_incurred_dataset_inflated <- generate_incurred_dataset(test_claims, test_inflated)
+View(test_incurred_dataset)
+test[[1]][[1]]
+## generated with default assumptions
+library(SynthETIC)
+set.seed(20200131)
+n_vector <- claim_frequency(I = 40, E = 12000, freq = 0.1)
+occurrence_times <- claim_occurrence(n_vector)
+claim_sizes <- claim_size(n_vector)
+notidel <- claim_notification(n_vector, claim_sizes)
+setldel <- claim_closure(n_vector, claim_sizes)
+no_payments <- claim_payment_no(n_vector, claim_sizes)
+payment_sizes <- claim_payment_size(n_vector, claim_sizes, no_payments)
+payment_delays <- claim_payment_delay(n_vector, claim_sizes, no_payments, setldel)
+payment_times <- claim_payment_time(n_vector, occurrence_times, notidel, payment_delays)
+base_inflation_vector <- rep((1.02)^(1/4) - 1, times = 80)
+payment_inflated <- claim_payment_inflation(
+n_vector, payment_sizes, payment_times, occurrence_times,
+claim_sizes, base_inflation_vector)
+# generate datasets
+# claim level data
+claim_dataset <- generate_claim_dataset(
+frequency_vector = n_vector,
+occurrence_list = occurrence_times,
+claim_size_list = claim_sizes,
+notification_list = notidel,
+settlement_list = setldel,
+no_payments_list = no_payments
+)
+# payment level data
+test_claims <- claims(
+n_vector, occurrence_times, claim_sizes, notidel, setldel, no_payments,
+payment_sizes, payment_delays, payment_times, payment_inflated)
+transaction_dataset <- generate_transaction_dataset(
+test_claims,
+adjust = FALSE # to keep the original simulated payment times
+)
+# write.csv(claim_dataset, "~/Downloads/claim_dataset_20210825.csv")
+# write.csv(transaction_dataset, "~/Downloads/payment_dataset_inflated_20210825.csv")
+# triangles
+# Constant dollar value INCREMENTAL triangle
+output_noinflation <- claim_output(n_vector, payment_times, payment_sizes,
+incremental = TRUE)
+# Inflated INCREMENTAL triangle
+output_actual <- claim_output(n_vector, payment_times, payment_inflated,
+incremental = TRUE)
+# write.csv(output_noinflation, "~/Downloads/triangle_noInf_20210825.csv")
+# write.csv(output_actual, "~/Downloads/triangle_inflated_20210825.csv")
+## With SPLICE loaded (locally)
+major <- claim_maRev_no(test_claims)
+major <- claim_maRev_time(test_claims, major)
+major <- claim_maRev_size(major)
+# minor revisions
+minor <- claim_miRev_no(test_claims)
+minor <- claim_miRev_time(test_claims, minor)
+minor <- claim_miRev_size(test_claims, major, minor)
+test <- claim_history(test_claims, major, minor)
+test_inflated <- claim_history(test_claims, major, minor,
+base_inflation_vector = rep((1 + 0.02)^(1/4) - 1, times = 80))
+test_incurred_dataset <- generate_incurred_dataset(test_claims, test)
+test_incurred_dataset_inflated <- generate_incurred_dataset(test_claims, test_inflated)
+major[[1]][[1]]
+View(test_incurred_dataset_inflated)
+View(test_incurred_dataset)
+View(transaction_dataset)
+write.csv(test_incurred_dataset, "~/Downloads/incurred_dataset_noInf_20210825.csv")
+write.csv(test_incurred_dataset_inflated, "~/Downloads/incurred_dataset_inflated_20210825.csv")
+write.csv(incurred_noInf, "~/Downloads/incurred_triangle_noInf_20210825.csv")
+# incurred triangles
+# Constant dollar value INCREMENTAL triangle
+incurred_noInf <- output_incurred(test, incremental = TRUE)
+# Inflated INCREMENTAL triangle
+incurred_inflated <- output_incurred(test_inflated, incremental = TRUE)
+write.csv(incurred_noInf, "~/Downloads/incurred_triangle_noInf_20210825.csv")
+write.csv(incurred_inflated, "~/Downloads/incurred_triangle_inflated_20210825.csv")
+x <- claim_dataset %>%
+select(claim_no, occurrence_time) %>%
+merge(test_incurred_dataset, by = "claim_no")
+library(dplyr)
+i
+x <- claim_dataset %>%
+select(claim_no, occurrence_time) %>%
+merge(test_incurred_dataset, by = "claim_no")
+View(x)
+test_incurred_dataset <- generate_incurred_dataset(test_claims, test)
+colnames(test_incurred_dataset)
+occurrence <- data.frame(
+claim_no = claim_dataset$claim_no,
+claim_size = claim_dataset$claim_size,
+txn_time = claim_dataset$occurrence_time,
+txn_delay = -claim_dataset$notidel,
+txn_type = "O",
+incurred = 0,
+OCL = 0,
+cumpaid = 0,
+multiplier = NA)
+View(occurrence)
+x <- rbind(test_incurred_dataset, occurrence) %>%
+arrange(claim_no, txn_time)
+View(x)
+nrow(x)
+nrow(test_incurred_dataset) + nrow(claim_dataset)
+1.7948353 - 0.6238351
+2.5837741 - 0.1206679
+y <- rbind(test_incurred_dataset_inflated, occurrence) %>%
+arrange(claim_no, txn_time)
+write.csv(x, "~/Downloads/incurred_dataset_noInf_20210825.csv")
+write.csv(y, "~/Downloads/incurred_dataset_inflated_20210825.csv")
+# incurred triangles
+# Constant dollar value INCREMENTAL triangle
+incurred_noInf <- output_incurred(test, incremental = TRUE)
+# Inflated INCREMENTAL triangle
+incurred_inflated <- output_incurred(test_inflated, incremental = TRUE)
+write.csv(incurred_noInf, "~/Downloads/incurred_triangle_noInf_20210825.csv")
+write.csv(incurred_inflated, "~/Downloads/incurred_triangle_inflated_20210825.csv")

SPLICE/NAMESPACE

@@ -1,12 +1,12 @@
 # Generated by roxygen2: do not edit by hand
 
 export(claim_history)
-export(claim_maRev_no)
-export(claim_maRev_size)
-export(claim_maRev_time)
-export(claim_miRev_no)
-export(claim_miRev_size)
-export(claim_miRev_time)
+export(claim_majRev_freq)
+export(claim_majRev_size)
+export(claim_majRev_time)
+export(claim_minRev_freq)
+export(claim_minRev_size)
+export(claim_minRev_time)
 export(dtri)
 export(generate_incurred_dataset)
 export(output_incurred)

SPLICE/R/data.R

@@ -28,7 +28,10 @@
 #'   \item{cumpaid}{double; cumulative claim paid **after** the transaction.}
 #'   \item{multiplier}{revision multipliers (subject to further constraints
 #'                     documented in \code{\link{claim_history}}), `NA` for
-#'                     transactions that do not involve a revision.}
+#'                     transactions that do not involve a revision. Note that
+#'                     major revision multipliers apply to the incurred losses,
+#'                     while minor revision multipliers apply to the outstanding
+#'                     claim payments.}
 #' }
 #' @seealso \code{\link{generate_incurred_dataset}}
 #' @name test_incurred_dataset