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  2. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    Consequently, if all singular values of a square matrix ⁠ ⁠ are non-degenerate and non-zero, then its singular value decomposition is unique, up to multiplication of a column of ⁠ ⁠ by a unit-phase factor and simultaneous multiplication of the corresponding column of ⁠ ⁠ by the same unit-phase factor.

  3. Monte Carlo methods for option pricing - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_methods_for...

    The value is defined as the least squares regression against market price of the option value at that state and time (-step). Option value for this regression is defined as the value of exercise possibilities (dependent on market price) plus the value of the timestep value which that exercise would result in (defined in the previous step of the ...

  4. Cost estimate - Wikipedia

    en.wikipedia.org/wiki/Cost_estimate

    A cost estimate is the approximation of the cost of a program, project, or operation. The cost estimate is the product of the cost estimating process. The cost estimate has a single total value and may have identifiable component values. A problem with a cost overrun can be avoided with a credible, reliable, and accurate cost estimate. A cost ...

  5. Roof insurance: ACV vs. replacement cost - AOL

    www.aol.com/finance/roof-insurance-acv-vs...

    For example, if the replacement cost — not the amount that you paid for it originally, but the amount it would cost to replace it today — for your roof is $20,000, but the roof loses 5 percent ...

  6. Iterative proportional fitting - Wikipedia

    en.wikipedia.org/wiki/Iterative_proportional_fitting

    The iterative proportional fitting procedure (IPF or IPFP, also known as biproportional fitting or biproportion in statistics or economics (input-output analysis, etc.), RAS algorithm [1] in economics, raking in survey statistics, and matrix scaling in computer science) is the operation of finding the fitted matrix which is the closest to an initial matrix but with the row and column totals of ...

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