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  2. Van der Meer formula - Wikipedia

    en.wikipedia.org/wiki/Van_der_Meer_formula

    Δ = relative density of the stone (= (ρ s-ρ w)/ρ w) where ρ s is the density of the stone and ρ w is the density of the water d n50 = nominal stone diameter α = breakwater slope P = notional permeability S = Damage number N = number of waves in the storm ξ m = the Iribarren number calculated with the Tm

  3. James–Stein estimator - Wikipedia

    en.wikipedia.org/wiki/James–Stein_estimator

    A consequence of the above discussion is the following counterintuitive result: When three or more unrelated parameters are measured, their total MSE can be reduced by using a combined estimator such as the James–Stein estimator; whereas when each parameter is estimated separately, the least squares (LS) estimator is admissible. A quirky ...

  4. Hudson's equation - Wikipedia

    en.wikipedia.org/wiki/Hudson's_equation

    Hudson's equation, also known as Hudson formula, is an equation used by coastal engineers to calculate the minimum size of riprap (armourstone) required to provide satisfactory stability characteristics for rubble structures such as breakwaters under attack from storm wave conditions.

  5. Gravel - Wikipedia

    en.wikipedia.org/wiki/Gravel

    Gravel (/ ˈ ɡ r æ v əl /) is a loose aggregation of rock fragments. Gravel occurs naturally on Earth as a result of sedimentary and erosive geological processes; it is also produced in large quantities commercially as crushed stone. Gravel is classified by particle size range and includes size classes from granule- to boulder-sized fragments

  6. Runoff curve number - Wikipedia

    en.wikipedia.org/wiki/Runoff_curve_number

    Gravel (including right of way) 76: 85: 89: 91 Dirt (including right-of-way) 72: 82: 87: 89 Western desert urban areas Natural desert landscaping (pervious area only) 63: 77: 85: 88 Artificial desert landscaping (impervious weed barrier, desert shrub with 1- to 2-inch sand or gravel mulch and basin borders) 96: 96: 96: 96 Urban districts ...

  7. Point estimation - Wikipedia

    en.wikipedia.org/wiki/Point_estimation

    , X n) be an estimator based on a random sample X 1,X 2, . . . , X n, the estimator T is called an unbiased estimator for the parameter θ if E[T] = θ, irrespective of the value of θ. [1] For example, from the same random sample we have E(x̄) = μ (mean) and E(s 2) = σ 2 (variance), then x̄ and s 2 would be unbiased estimators for μ and ...