我有一个课程，按以下方式组织：
balancesheet <- setClass("balancesheet",
slots = c(
report_date = "numeric",
account_id = "numeric",
q = "numeric",
maturity_date = "numeric",
assetLiability = "numeric",
lcr_weight = "numeric",
nsfr_weight = "numeric"
),
prototype=list(
report_date = 0,
account_id = 100000,
q = 1,
maturity_date = 1,
assetLiability = 1,
lcr_weight = 0,
nsfr_weight = 0
)
)
然后我用我的数据填充这个类，它看起来像（它的一些部分）：
[[1]]
An object of class "balancesheet"
Slot "report_date":
[1] 17226
Slot "account_id":
[1] 20202
Slot "q":
[1] 163592774
Slot "currency":
[1] 810
Slot "maturity_date":
[1] 17227
Slot "assetLiability":
[1] -1
Slot "lcr_weight":
[1] 0
Slot "nsfr_weight":
[1] 1
[[144]]
An object of class "balancesheet"
Slot "report_date":
[1] 17226
Slot "account_id":
[1] 31403
Slot "q":
[1] 0
Slot "currency":
[1] 810
Slot "maturity_date":
[1] 17256
Slot "assetLiability":
[1] -1
Slot "lcr_weight":
[1] 0.5
Slot "nsfr_weight":
[1] 0.5
[[146]]
An object of class "balancesheet"
Slot "report_date":
[1] 17226
Slot "account_id":
[1] 40903
Slot "q":
[1] 490
Slot "currency":
[1] 810
Slot "maturity_date":
[1] 17227
Slot "assetLiability":
[1] -1
Slot "lcr_weight":
[1] 0.4
Slot "nsfr_weight":
[1] 0
[[600]]
An object of class "balancesheet"
Slot "report_date":
[1] 17167
Slot "account_id":
[1] 91412
Slot "q":
[1] 74442089
Slot "currency":
[1] 810
Slot "maturity_date":
[1] 17197
Slot "assetLiability":
[1] 1
Slot "lcr_weight":
[1] 0.1
Slot "nsfr_weight":
[1] 0
[[601]]
An object of class "balancesheet"
Slot "report_date":
[1] 17167
Slot "account_id":
[1] 91414
Slot "q":
[1] 38306207912
Slot "currency":
[1] 810
Slot "maturity_date":
[1] 17347
Slot "assetLiability":
[1] 1
Slot "lcr_weight":
[1] 0.1
Slot "nsfr_weight":
[1] 0
[[602]]
An object of class "balancesheet"
Slot "report_date":
[1] 17167
Slot "account_id":
[1] 91416
Slot "q":
[1] 5847202
Slot "currency":
[1] 810
Slot "maturity_date":
[1] 17532
Slot "assetLiability":
[1] 1
Slot "lcr_weight":
[1] 0.1
Slot "nsfr_weight":
[1] 0
然后我写了一个方法来转换数据框中的这个列表：
setGeneric(name="getBalanceSheet",
def=function(balancesheet.list)
{
standardGeneric("getBalanceSheet")
}
)
setMethod(f="getBalanceSheet",
signature="ANY",
definition=function(balancesheet.list)
{
balancesheet.df <- vector()
n <- length(balancesheet.list)
for(i in 1:n)
{
object <- balancesheet.list[[i]]
row <- c(object@report_date,object@maturity_date,object@account_id,object@q,object@assetLiability,object@lcr_weight,object@nsfr_weight)
balancesheet.df <- rbind(balancesheet.df,row)
}
return(balancesheet.df)
}
)
这个数据框看起来像：
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row 17226 17227 20202.0 1.635928e+08 -1 0.00 1.0
row 17226 17227 20208.0 1.943708e+08 -1 0.00 1.0
row 17226 17227 20209.0 5.638990e+07 -1 0.00 1.0
row 17226 17227 30233.0 2.314207e+08 1 0.40 1.0
row 17226 17256 31903.0 0.000000e+00 1 0.50 0.5
row 17226 17256 32002.0 1.600000e+06 1 0.50 0.5
row 17226 17256 32003.0 2.000000e+06 1 0.50 0.5
其中1为report_date，2为maturity_date，3为account_id，4为q，5为assetLiability_flag，6为lcr_coeff }，7是nsfr_coeff。
然后我为这个类设置了一个方法如下：
setGeneric(name="LiquidityRisk",
def=function(balancesheet.list)
{
standardGeneric("LiquidityRisk")
}
)
setMethod(f="LiquidityRisk",
signature="ANY",
definition=function(balancesheet.list)
{
outflows <- 0
inflows <- 0
available1 <- 0
required1 <- 0
n <- length(balancesheet.list)
for (i in 1:n)
{
object <- balancesheet.list[[i]]
if (object@maturity_date <= (object@report_date + 30) && object@assetLiability == -1) {
outflows <- outflows + object@q * object@lcr_weight
}
if (object@maturity_date <= (object@report_date + 30) && object@assetLiability == 1)
{
inflows <- inflows + object@q * object@lcr_weight
}
if (object@maturity_date <= object@report_date + 360 && object@assetLiability == -1)
{
available1 <- available1 + object@q * object@nsfr_weight
}
if (object@maturity_date <= object@report_date + 360 && object@assetLiability == 1)
{
required1 <- required1 + object@q * object@nsfr_weight
}
}
cat(outflows, " ", inflows," ",available1," ",required1, "
")
ratios <- list()
output <- as.data.frame(matrix(0,1,3))
colnames(output) <- c("outflows","inflows","netcashflows")
output[1] <- outflows
output[2] <- inflows
output[3] <- max(outflows-inflows,0.25*outflows)
output.nsfr <- as.data.frame(matrix(0,1,2))
colnames(output.nsfr) <- c("available","required")
output.nsfr[1] <- available1
output.nsfr[2] <- required1
ratios[["lcr"]] <- output
ratios[["nsfr"]] <- output.nsfr
#ratios[["lcr"]] <- round(output/10^9,1)
#ratios[["nsfr"]] <- round(output.nsfr/10^9,1)
return(ratios)
}
)
它有效！
但是，我只检查了balancesheet.list的一个report_date（2017-03-01，数字格式为17226）：我为此report_date过滤了它并使用了我的方法。如果我有10个这样的report_dates，我会以同样的方式为每个人做手。但是，我有很多report_dates，即每个月从2003年到2017年（以及每个月的相应数据）。我怎样才能在lcr的某个单独的txt或Excel文件中报告nsfr和report_date系数？
我想到了一些与循环有关的report_date的唯一值，但没有取得成功。
答案 0 :(得分：0)
如果您的所有数据都保存在上面显示的17226相同的7列数据框中，您可以split(df, df[,1])按日期将df分成列表（您将拥有超过150个这些列表）我推测）然后你可以用lapply或sapply将split df作为第一个参数并将LiquidityRisk作为FUN参数？
ManyMonths <- lapply(split(df, df[,1]), LiquidityRisk)
这会将所有结果打印为单个对象，如果您选择，可以将其保存到文件中： Export a list into a CSV or TXT file in R