DefaultSalesModule: Model advertiser and competitor sales.
In google/amss: Agreggate Marketing System Simulator

Simulate consumer purchase behavior, and thus the advertiser's and its competitors' sales.

DefaultSalesModule(data.dt, price, mean.price = 0,
  advertiser.demand.intercept = list(),
  advertiser.demand.slope = list(favorability = rep(0,
  length(kFavorabilityStates))), competitor.demand.max = list(loyalty = c(1,
  0, 1)), competitor.demand.replacement = list(loyalty = c(0.5, 0, 1)),
  purchase.quantity.intercept = 1, purchase.quantity.slope = 0,
  purchase.quantity.competitor = 1, unit.cost = 0,
  advertiser.transitions = list(), competitor.transitions = list())

`data.dt`	data.table with rows corresponding to population segments and columns corresponding to specific variables
`price`	numeric vector of product price over time. If the vector is shorter than the number of timepoints, it is repeated as necessary.
`mean.price`	numeric scaler, the mean of price over time. Defaults to zero.
`advertiser.demand.intercept`	list of numeric vectors corresponding to each brand state (favorability, loyalty, and availability). The product of multiplicands corresponding to a particular segment with 'purchase' activity state is the probability consumers in that segment will purchase the advertiser's product if the price is mean.price and there is no competition. Missing members of the list have no effect on the calculation.
`advertiser.demand.slope`	list of numeric vectors corresponding to each brand state (favorability, loyalty, and availability). The product of multiplicands corresponding to a particular segment with 'purchase' activity state is the linear decrease in the probability consumers in that segment will purchase the advertiser's product when the price increases by 1, when there is no competition. Missing members of the list have no effect on the calculation.
`competitor.demand.max`	list of numeric vectors corresponding to each brand state (favorability, loyalty, and availability). The product of multiplicands corresponding to a particular segment with 'purchase' activity state is the probability consumers in that segment will purchase a competitor's product when advertiser's product is too expensive to be a feasible choice. Missing members of the list have no effect on the calculation.
`competitor.demand.replacement`	list of numeric vectors corresponding to each brand state (favorability, loyalty, and availability). The product of multiplicands corresponding to a particular segment specifies the degree to which advertiser and competitor sales are replacements for each other. At 1, competitor sales are unaffected by advertiser pricing, and competitor sales replace advertiser sales to the greatest degree possible. At 0, advertiser sales are unaffected by the presence of the competitor, and advertiser sales replace competitor sales to the greatest degree possible. Thus, a reasonble interpretation of consumer loyalty might set this parameter to `list(loyalty = c(0.5, 0.1, 0.9)`. Missing members of the list have no effect on the calculation.
`purchase.quantity.intercept`	numeric, at least 1. Represents the average number of units bought by each consumer purchasing from the advertiser's brand, if price is mean.price.
`purchase.quantity.slope`	numeric, generally >= 0. Represents the decrease in the average purchase quantity per consumer purchasing from the advertiser's brand given a unit increase in price. Missing members of the list have no effect on the calculation.
`purchase.quantity.competitor`	average number of units bought by consumers purchasing a comeptitor's product. Must be at the least the default value of 1.
`unit.cost`	numeric greater than 0, cost of goods sold, for one unit of the advertiser's product.
`advertiser.transitions`	list of transition matrices for each brand state, specifying post-purchase changes in consumer mindset for those who purchased the advertiser's brand. A named list with members 'favorability', 'loyalty', and 'availability' is expected. Any missing members will have no effect. The default value, `list()` results in no post-purchase migration.
`competitor.transitions`	list of transition matrices for each brand state, specifying post-purchase changes in consumer mindset for those who purchased a competitor's brand. A named list with members 'favorability', 'loyalty', and 'availability' is expected. Any missing members will have no effect. The default value, `list()` results in no post-purchase migration.