Search results
Results from the WOW.Com Content Network
If y=c is a horizontal asymptote of f(x), then y=c+k is a horizontal asymptote of f(x)+k; If a known function has an asymptote, then the scaling of the function also have an asymptote. If y=ax+b is an asymptote of f(x), then y=cax+cb is an asymptote of cf(x) For example, f(x)=e x-1 +2 has horizontal asymptote y=0+2=2, and no vertical or oblique ...
The folium of Descartes (green) with asymptote (blue) when = In geometry , the folium of Descartes (from Latin folium ' leaf '; named for René Descartes ) is an algebraic curve defined by the implicit equation x 3 + y 3 − 3 a x y = 0. {\displaystyle x^{3}+y^{3}-3axy=0.}
The asymptotic directions are the same as the asymptotes of the hyperbola of the Dupin indicatrix through a hyperbolic point, or the unique asymptote through a parabolic point. [1] An asymptotic direction is a direction along which the normal curvature is zero: take the plane spanned by the direction and the surface's normal at that point. The ...
The function f(n) is said to be "asymptotically equivalent to n 2, as n → ∞". This is often written symbolically as f ( n ) ~ n 2 , which is read as " f ( n ) is asymptotic to n 2 ". An example of an important asymptotic result is the prime number theorem .
In physics and other fields of science, one frequently comes across problems of an asymptotic nature, such as damping, orbiting, stabilization of a perturbed motion, etc. . Their solutions lend themselves to asymptotic analysis (perturbation theory), which is widely used in modern applied mathematics, mechanics and phy
The intuition of the delta method is that any such g function, in a "small enough" range of the function, can be approximated via a first order Taylor series (which is basically a linear function). If the random variable is roughly normal then a linear transformation of it is also normal. Small range can be achieved when approximating the ...
A sigmoid function is a bounded, differentiable, real function that is defined for all real input values and has a non-negative derivative at each point [1] [2] and exactly one inflection point. Properties
A sequence of distributions corresponds to a sequence of random variables Z i for i = 1, 2, ..., I . In the simplest case, an asymptotic distribution exists if the probability distribution of Z i converges to a probability distribution (the asymptotic distribution) as i increases: see convergence in distribution.