Rounded

Let us assume that we do not want the integer quantity but the exact real number. To this end, we need to call the solve function with the additional argument rounded = false

Example

julia> nvm = NVModel(demand = Normal(50, 20), cost = 2, price = 7)
Data of the Newsvendor Model
 * Demand distribution: Normal{Float64}(μ=50.0, σ=20.0)
 * Unit cost: 2.00
 * Unit selling price: 7.00

julia> res_real = solve(nvm, rounded = false)
=====================================
Results of maximizing expected profit
 * Optimal quantity: 61.32
 * Expected profit: 202.41
=====================================
This is a consequence of
 * Cost of underage:  5.00
   ╚ + Price:               7.00
   ╚ - Cost:                2.00
 * Cost of overage:   2.00
   ╚ + Cost:                2.00
 * Critical fractile: 0.71
 * Rounded to nearest integer: false
-------------------------------------
Ordering the optimal quantity yields
 * Expected sales: 46.44 units
 * Expected lost sales: 3.56 units
 * Expected leftover: 14.88 units
-------------------------------------

This reveals a slighlty higher profit than with the standard (rounded up) integer result:

julia> q_opt(nvm)
61

julia> profit(res_real)
202.41322650461186

julia> profit(nvm)
202.40715617998893

rounded(res_real) applied to a result tells whether the integer result was looked for is.

julia> rounded(res_real)
false