Description Usage Arguments Details Value References Examples
Generate combination sets to be used in TURF analysis, formatted for use in turf
. Can be used to generate
all possible combinations of n choose k or Monte Carlo simulated subsets of combinations involving the same
n items.
1 | turf.combos(n, k, ...)
|
n |
Required. Scalar indicating the number of items to be included in the TURF algorithm; 0 < n < ( |
k |
Required. Vector of length 1 to n containing any values 1 to n indicating the combination sizes to be evaluated
by the TURF algorithm. Non-integer values are coerced using |
... |
Optional. Additional arguments controlling behavior and output of the TURF algorithm. See |
Generally, it is only necessary to call turf.combos
independently of turf
if the user wishes to manually modify combination sets
that will be evaluated. See turf
and turf.args
for additional information on usage.
A list of length(
k)
elements, each of which is comprised of a p x n matrix of zeroes and ones. Rows
(p) are individual combinations to be evaluted by the TURF algorithm. Columns (n) correspond to items and must be in the same
order as the items variables in data
submitted to TURF. Ones indicate that an item is included in a given combination. Each ith
element contains only combinations of the size indicated by the ith position of k.
Adler, T.J., Smith, C. & Dumont, J. 2010. Optimizing product portfolios using discrete choice modeling and TURF. In: S. Hess, A. Daly (Eds), Choice modeling: the state-of-the-art and the state-of-practice; proceedings from the Inaugural International Choice Modeling Conference. Emerald Publishing Group Ltd., pp. 485-497.
Krieger, A.M. & Green, P.E. 2000. Turf revisited: Enhancements to toal unduplicated reach and frequency analysis. Marketing Research, 12, 30-36.
Markowitz, L. 2005. Going beyond TURF to complement and extend existing product lines. Ipsos-Insight, November 2005.
Miaoulis, G., Free, V. & Parsons, H. 1990. TURF: A new planning approach for product line extensions. Marketing Research, March, pp. 28-40.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ##Example 1
##Generate all combinations of 3, 4, 5 and 6 items drawn from 10 items.
ex1 <- turf.combos(10, 3:6)
colSums(ex1[[2]])
##Example 2
##Pass additional arguments
data(turf_ex_data)
psims <- colSums(turf_ex_data[,-c(1:2)]) / sum(turf_ex_data[,2])
psims <- psims / sum(psims)
ex2 <- turf.combos(10, 4, mc=TRUE, nsims=100, psims=psims)
colSums(ex2[[1]])
|
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