The probability space can be considered as a parametric space.
Hence, the quantity of interest of this model is defined on both a parametric space and a stochastic space.
By transforming the Cartesian space to a parametric space (i.e., Hough space) any parametric curve can be defined.
The F-test is a parametric test without a non-parametric alternative.
The t-test is a parametric test and the permutation process is non-parametric.
To organize the paper, the different approaches are classified into three control fields, which previously are stated: parametric space, frequency methods, discrete-time systems.
It takes into account not only the influence of geometrical deviations but also the influence of the types of contacts on the geometrical behavior of the mechanism; these physical phenomena are modeled by convex hulls (compatibility hull, interface hull and functional hull) which are defined in parametric space.
Before we state our main results, the following assumptions will be made: (A1): The parametric space ϒ is compact with (Upsilon={alpha: deltaleqalpha_{0}leq M, 0leq alpha_{1}+cdots +alpha_{p}leq M^{ast}<1, alpha_{i}geq0, i=1, 2, ldots, p }), where δ and M are finite positive constants, and the true parameter value (alpha^{0}) is an interior point in ϒ.
But don't worry, you're not losing your mind this is a new interactive installation, Parametric Space, from Zaha Hadid Architects in collaboration with designers Kollision, CAVI, and Wahlberg.
Consider the following parametrically GVQEP: For any given p ∈ Φ, ( GVQEP ) p to find x ¯ ∈ P ( x ¯ ) such that h ( x ¯, z, p ) ∩ ( − int C ( x ¯ ) ) = ∅ for all z ∈ Q ( x ¯ ), where h : E × F × Φ → 2 Y, P : E → 2 E and Q : E → 2 F are strict set-valued mappings, and ( Φ, d ˜ ) is a Hausdorff metric space (parametric space).
