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  2. Fractional factorial design - Wikipedia

    en.wikipedia.org/wiki/Fractional_factorial_design

    Each generator halves the number of runs required. A design with p such generators is a 1/(l p)=l −p fraction of the full factorial design. [3] For example, a 2 52 design is 1/4 of a two-level, five-factor factorial design. Rather than the 32 runs that would be required for the full 2 5 factorial experiment, this experiment requires only ...

  3. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    This experiment is an example of a 2 2 (or 2×2) factorial experiment, so named because it considers two levels (the base) for each of two factors (the power or superscript), or #levels #factors, producing 2 2 =4 factorial points. Cube plot for factorial design . Designs can involve many independent variables.

  4. Aliasing (factorial experiments) - Wikipedia

    en.wikipedia.org/wiki/Aliasing_(factorial...

    Aliasing (factorial experiments) In the statistical theory of factorial experiments, aliasing is the property of fractional factorial designs that makes some effects "aliased" with each other – that is, indistinguishable from each other. A primary goal of the theory of such designs is the control of aliasing so that important effects are not ...

  5. Box–Behnken design - Wikipedia

    en.wikipedia.org/wiki/Box–Behnken_design

    Box–Behnken design. In statistics, Box–Behnken designs are experimental designs for response surface methodology, devised by George E. P. Box and Donald Behnken in 1960, to achieve the following goals: Each factor, or independent variable, is placed at one of three equally spaced values, usually coded as −1, 0, +1.

  6. Robust parameter design - Wikipedia

    en.wikipedia.org/wiki/Robust_parameter_design

    A robust parameter design, introduced by Genichi Taguchi, is an experimental design used to exploit the interaction between control and uncontrollable noise variables by robustification —finding the settings of the control factors that minimize response variation from uncontrollable factors. [ 1] Control variables are variables of which the ...

  7. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    Definition. The most common problem being solved is the 0-1 knapsack problem, which restricts the number of copies of each kind of item to zero or one. Given a set of items numbered from 1 up to , each with a weight and a value , along with a maximum weight capacity , subject to and . Here represents the number of instances of item to include ...

  8. Central composite design - Wikipedia

    en.wikipedia.org/wiki/Central_composite_design

    Central composite design. In statistics, a central composite design is an experimental design, useful in response surface methodology, for building a second order (quadratic) model for the response variable without needing to use a complete three-level factorial experiment. After the designed experiment is performed, linear regression is used ...

  9. Fractal dimension - Wikipedia

    en.wikipedia.org/wiki/Fractal_dimension

    A fractal dimension is an index for characterizing fractal patterns or sets by quantifying their complexity as a ratio of the change in detail to the change in scale. [5]: 1 Several types of fractal dimension can be measured theoretically and empirically (see Fig. 2). [3][9] Fractal dimensions are used to characterize a broad spectrum of ...