[R-pkg-devel] using optimx in a package

[Dirk Eddelbuettel]

On 16 October 2016 at 18:05, Glenn Schultz wrote:
| All,
| 
| I am using optimx in my package to fit the term structure of interest rates.  When I call the function from the package I get the following error:
| 
| Error in optimx.check(par, optcfg$ufn, optcfg$ugr, optcfg$uhess, lower, : 
| Cannot evaluate function at initial parameters
| Called from: optimx.check(par, optcfg$ufn, optcfg$ugr, optcfg$uhess, lower, 
| upper, hessian, optcfg$ctrl, have.bounds = optcfg$have.bounds, 
| usenumDeriv = optcfg$usenumDeriv, ...)
| 
| However, if I run the function locally outside of the package it runs a provides the correct solution to the problem.  So, the issue is the function will not run correctly when called from the package.  Any suggestions are appreciated. This package is written in S4

Make sure you _import_ the optmix package correctly in _your_ package. What
is visible to the package, versus what your commandline sees, is (almost
entirely) governed by NAMESPACE and DESCRIPTION.

'R CMD check --as-cran', particular when R is R-devel, should have plenty of pointers.

Dirk

| Glenn
| 
| Here is a dput of the Rates Object
| structure(list(Date = c("2016-07-11", NA), ED1M = c(0.47785, 
| 0.0833), ED3M = c(0.6691, 0.25), ED6M = c(0.9514, 0.5), USSW1 = c(0.74, 
| 1), USSW2 = c(0.82, 2), USSW3 = c(0.88, 3), USSW4 = c(0.93, 4
| ), USSW5 = c(1, 5), USSW7 = c(1.13, 7), USSW10 = c(1.31, 10), 
| USSW30 = c(1.72, 30)), .Names = c("Date", "ED1M", "ED3M", 
| "ED6M", "USSW1", "USSW2", "USSW3", "USSW4", "USSW5", "USSW7", 
| "USSW10", "USSW30"), row.names = 1:2, class = "data.frame")
| 
| 
| Requirements
| 
| require(lubridate)
| require(termstrc)
| require(optimx)
| 
| months.in.year = 12
| weeks.in.year = 52
| pmt.frequency = 2
| min.principal = 100
| days.in.month = 30.44
| Rates <- RatesObject #Rates(trade.date = "07-11-2016")
| 
| 
| Here is the function
| CalibrateCIR <- function(trade.date = character, 
| sigma = numeric()){
| 
| rates.data <- Rates(trade.date = trade.date) 
| shortrate = as.numeric(rates.data[1,2])/100
| 
| #set the column counter to make cashflows for termstrucutre
| ColCount <- as.numeric(ncol(rates.data))
| Mat.Years <- as.numeric(rates.data[2,2:ColCount])
| Coupon.Rate <- as.numeric(rates.data[1,2:ColCount])
| Issue.Date <- as.Date(rates.data[1,1])
| 
| #initialize coupon bonds S3 class
| #This can be upgraded when bondlab has portfolio function
| ISIN <- vector()
| MATURITYDATE <- vector()
| ISSUEDATE <- vector()
| COUPONRATE <- vector()
| PRICE <- vector()
| ACCRUED <- vector()
| CFISIN <- vector()
| CF <- vector()
| DATE <- vector()
| CASHFLOWS <- list(CFISIN,CF,DATE)
| names(CASHFLOWS) <- c("ISIN","CF","DATE")
| TODAY <- vector()
| data <- list()
| TSInput <- list()
| 
| ### Assign Values to List Items #########
| data = NULL
| data$ISIN <- colnames(rates.data[2:ColCount])
| data$ISSUEDATE <- rep(as.Date(rates.data[1,1]),ColCount - 1)
| data$MATURITYDATE <-
| sapply(Mat.Years, function(Mat.Years = Mat.Years, Issue = Issue.Date) 
| {Maturity = if(Mat.Years < 1) {
| Issue %m+% months(round(Mat.Years * months.in.year))} else 
| {Issue %m+% years(as.numeric(Mat.Years))}
| return(as.character(Maturity))
| }) 
| data$COUPONRATE <- ifelse(Mat.Years < 1, 0, Coupon.Rate) 
| data$PRICE <- ifelse(
| Mat.Years < 1, (1 + (Coupon.Rate/100))^(Mat.Years * -1) * 100, 100)
| data$ACCRUED <- rep(0, ColCount -1)
| 
| for(j in 1:(ColCount-1)){
| Vector.Length <- as.numeric(round(
| difftime(data[[3]][j],
| data[[2]][j],
| units = c("weeks"))/weeks.in.year,5))
| 
| Vector.Length <- ifelse(round(Vector.Length) < 1, 1 , 
| round(Vector.Length * pmt.frequency))
| 
| data$CASHFLOWS$ISIN <- append(
| data$CASHFLOWS$ISIN, rep(data[[1]][j],Vector.Length))
| 
| data$CASHFLOWS$CF <- append(
| data$CASHFLOWS$CF,
| as.numeric(
| c(rep((data[[4]][j]/100/pmt.frequency),Vector.Length-1) * min.principal,
| (min.principal + 
| (data$COUPONRATE[j]/100/pmt.frequency)* min.principal))))
| 
| by.months = ifelse(data[[4]][j] == 0, round(difftime(
| data[[3]][j], rates.data[1,1])/days.in.month), 6)
| 
| data$CASHFLOWS$DATE <- append(
| data$CASHFLOW$DATE, seq(
| as.Date(data[[2]][j]) %m+% months(as.numeric(by.months)), 
| as.Date(data[[3]][j]),
| by = as.character(paste(by.months, "months", sep = " "))))
| 
| } #The Loop Ends here and the list is made
| 
| data$TODAY <- as.Date(rates.data[1,1])
| TSInput[[as.character(rates.data[1,1])]] <- c(data)
| 
| #set term strucutre input (TSInput) to class couponbonds
| class(TSInput) <- "couponbonds"
| CashFlow <- TSInput[[1]]
| CIR.CF.Matrix <<- create_cashflows_matrix(TSInput[[1]], include_price = TRUE)
| CIR.Mat.Matrix <<- create_maturities_matrix(TSInput[[1]], include_price = TRUE )
| 
| #Objective function for the origin to be inaccessable the followign 
| #condition must be met
| # 2 * kappa * theta <= sigma^2 
| CIRTune <- function(param = numeric(), 
| shortrate = numeric(), 
| sigma = sigma, 
| cfmatrix = matrix(), 
| matmatrix = matrix()){
| 
| kappa = param[1]
| theta = param[2]
| 
| FwdRate <- CIRSim(kappa = kappa,
| theta = theta,
| shortrate = Rates[1,2]/100,
| T = 30,
| step = 6/months.in.year,
| sigma = sigma,
| N = 1)
| 
| Spot <- cumprod(1+(FwdRate))
| t <- seq(1,length(Spot),1)
| Spot <- Spot^(1/t)
| #DiscMatrix <<- 1/(Spot^matmatrix)
| CIRTune <- sqrt((sum(colSums((cfmatrix * 1/(Spot^matmatrix)))^2))/ncol(matmatrix))
| return(CIRTune)
| }
| 
| # Fit the model to the market 
| fit <- optimx(par = c(.1, .05), 
| fn = CIRTune, 
| method = "L-BFGS-B",
| lower = c(.1,.01),
| upper = c(.9, .2) , 
| shortrate = shortrate,
| sigma = sigma,
| cfmatrix = CIR.CF.Matrix, 
| matmatrix = CIR.Mat.Matrix) 
| 
| return(fit)
| }
| 
| 
| 
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http://dirk.eddelbuettel.com | @eddelbuettel | edd at debian.org