Ch8QA | R Documentation |
Randomly generates and typesets problems of 18 specified types from Chapter 8 of ALMCR3e. All problems use the Standard Sickness-Death Table, based on the 3-state Markov model defined on pages 290 and 764–766 of AMLCR3e. This function generates two PDF files, one listing the problems, and another with the step-by-step solutions.
Ch8QA(probspertype = 5, probspec = NULL, randomize = FALSE, probsummary = FALSE,
qfile = "qfilech8", afile = "afilech8", keeptex = FALSE)
probspertype |
Number of problems of each type to generate. Use this argument (instead of |
probspec |
Vector of length 18 giving the number of each of the 18 types of Chapter 8 SULT problems to generate. Use this argument (instead of |
randomize |
Boolean variable controlling whether the problems will be randomized (TRUE), or appear in problem type order (FALSE). |
probsummary |
Boolean variable controlling whether a summary of the problem types generated will be placed at the end of the question file. |
qfile |
Name (and path) to write question PDF file. |
afile |
Name (and path) to write solution PDF file. |
keeptex |
Boolean variable controlling whether the .tex files compiled to produce the PDFs are kept (TRUE) or deleted (FALSE) after the PDF is rendered. |
Specify the types of problems generated using either the (scalar) probspertype
parameter or the (vector) probspec
parameter. See package vignette for further information.
Invoked for the side effect of producing the two PDF files.
Chris Groendyke groendyke@rmu.edu
Dickson, D.C.M., Hardy, M.R., Waters, H.R., 2020 Actuarial Mathematics for Life Contingent Risks, Third Edition, Cambridge, UK: Cambridge University Press.
Ch3QA
, Ch4QA
, Ch5QA
, and Ch10QA
for analogous functions for generating problems and solutions for material in chapters 3, 4, 5, and 10, respectively.
# Generate 1 problem of each type, in random order.
Ch8QA(probspertype = 1, randomize = TRUE, probsummary = TRUE)
# Generate 30 total problems from among the 18 Ch. 5 problem types.
#Ch8QA(probspec = tabulate(sample(1:18, 30, TRUE), nbins=18))
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