R help - Mar 2010 - Possible to use array of spline functions for storing data?

Dear listeRs;

I am hoping to provide myself the ability to interpolate mortality  
estimates within intervals for a range of conditions and ages. I have  
four mortality tables derived from the Society of Actuaries 2001 VBT  
tables that contains interval mortality rates by starting age and year  
of duration. I would like to flexibly interpolate using a large set  
(~4MM) of ages and conditions as input to small number (~300) of  
functions, but my toy implementations puzzle me when I examine them,  
and I cannot seem to store them properly. Say you start with a vector  
of qx's:

 > qx = c(.001, .003, 0.005, 0.01, 0.03, 0.06, 0.12, 0.24,0.4, 0.8)
# Now convert to mortality
 > mx <- 2*qx/(2-qx)
# And make a spline function
 > mspline <- splinefun(mx)
# Works well.
 > mspline(5.5)
# [1] 0.04466954
# Examine the spline function
 > mspline
function (x, deriv = 0)
{
     deriv <- as.integer(deriv)
     if (deriv < 0 || deriv > 3)
         stop("'deriv' must be between 0 and 3")
     if (deriv > 0) {
         z0 <- double(z$n)
         z[c("y", "b", "c")] <- switch(deriv,
list(y = z$b, b = 2 *
             z$c, c = 3 * z$d), list(y = 2 * z$c, b = 6 * z$d,
             c = z0), list(y = 6 * z$d, b = z0, c = z0))
         z[["d"]] <- z0
     }
     res <- .C("spline_eval", z$method, as.integer(length(x)),
         x = as.double(x), y = double(length(x)), z$n, z$x, z$y,
         z$b, z$c, z$d, PACKAGE = "stats")$y
     if (deriv > 0 && z$method == 2 && any(ind <- x <=
z$x[1L]))
         res[ind] <- ifelse(deriv == 1, z$y[1L], 0)
     res
}
<environment: 0x218874878>

My first puzzlement is the lack of any evidence that this is  
particular to the data that was offered to splinefun. Is it all hidden  
within <environment: 0x218874878>? My plan had been to convert a set  
of about 300 rows of data into 300 spline functions that could be  
indexed in an array by gender, smoking status, and age.

Would I be able to create an array of such functions? Testing leaves  
me discouraged:

 > spline.arr <- array( , dim= c(sex=2, smk=2, age = 65))
 > str(spline.arr)
  logi [1:2, 1:2, 1:65] NA NA NA NA NA NA ..
# Now attempt to store one function in the first "cell":
 > spline.arr[1,1,1] <- mspline
Error in spline.arr[1, 1, 1] <- mspline :
   number of items to replace is not a multiple of replacement length

 From the help page for array I thought that the possibility of  
storing lists within arrays might mean that functions would "fit", but
have I been too expansive in my thinking? Is there an incantation that  
would let me store a language object in an array. Lists appear to be  
similarly unable to accept a function as an element:

 > spl.list <- list()
 > spl.list[["M"]][["NS"]][["20"]] <-
mspline
Error in spl.list[["M"]][["NS"]][["20"]] <-
mspline :
   invalid type/length (closure/0) in vector allocation
 > spl.list[["M"]][["NS"]][["20"]] <- 1  #
no error

-- 
David Winsemius, MD
West Hartford, CT

David Winsemius wrote:
> 
> Dear listeRs;
> 
> I am hoping to provide myself the ability to interpolate mortality  
> estimates within intervals for a range of conditions and ages. I have  
> four mortality tables derived from the Society of Actuaries 2001 VBT  
> tables that contains interval mortality rates by starting age and year  
> of duration. I would like to flexibly interpolate using a large set  
> (~4MM) of ages and conditions as input to small number (~300) of  
> functions, but my toy implementations puzzle me when I examine them,  
> and I cannot seem to store them properly. Say you start with a vector  
> of qx's:
> ....
> 
How about using the polynomial representation given be polySpline in package
splines? It a slightly decorated list of knots and coefficients that could
be stored in a database.

Dieter

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