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Что (кто) такое complete randomization - определение
STATISTICAL METHOD IN GENETIC EPIDEMIOLOGY
Mendelian randomisation; Mendelian randomization analysis; Mendelian Randomization
Найдено результатов: 601
Mendelian randomization
In epidemiology, Mendelian randomization (commonly abbreviated to MR) is a method using measured variation in genes to interrogate the causal effect of an exposure on an outcome. Under key assumptions (see below), the design reduces both reverse causation and confounding, which often substantially impede or mislead the interpretation of results from epidemiological studies.
Complete spatial randomness
PROCESS WHEREBY POINT EVENTS OCCUR WITHIN A GIVEN STUDY AREA IN A COMPLETELY RANDOM FASHION
Complete spatial randomness (CSR) describes a point process whereby point events occur within a given study area in a completely random fashion. It is synonymous with a homogeneous spatial Poisson process.
complete graph
SIMPLE UNDIRECTED GRAPH IN WHICH EVERY PAIR OF DISTINCT VERTICES IS CONNECTED BY A UNIQUE EDGE
Full graph; Complete Digraph; Complete digraph; K n; Tetrahedral Graph; Complete graphs
A graph which has a link between every pair of nodes. A
complete bipartite graph can be partitioned into two subsets
of nodes such that each node is joined to every node in the
other subset.
(1995-01-24)
Complete (complexity)
NOTION OF THE "HARDEST" OR "MOST GENERAL" PROBLEM IN A COMPLEXITY CLASS
Complete problem; Hard (complexity)
In computational complexity theory, a computational problem is complete for a complexity class if it is, in a technical sense, among the "hardest" (or "most expressive") problems in the complexity class.
♯P-complete
COMPLEXITY CLASS
Sharp-P-Complete; Sharp P complete; Number-P hard; Number-P-complete; Sharp-P hard; Sharp-P-complete
The #P-complete problems (pronounced "sharp P complete" or "number P complete") form a complexity class in computational complexity theory. The problems in this complexity class are defined by having the following two properties:
Chain-complete partial order
POSET COMPLETION
Chain complete; Chain completeness
In mathematics, specifically order theory, a partially ordered set is chain-complete if every chain in it has a least upper bound. It is ω-complete when every increasing sequence of elements (a type of countable chain) has a least upper bound; the same notion can be extended to other cardinalities of chains..
NP-complete
![Levin]] proved that each easy-to-verify problem can be solved as fast as SAT, which is hence NP-complete.](https://commons.wikimedia.org/wiki/Special:FilePath/3SAT 17 svg.svg?width=200 "Levin]] proved that each easy-to-verify problem can be solved as fast as SAT, which is hence NP-complete.")
![P≠NP]], while the right side is valid under the assumption that P=NP (except that the empty language and its complement are never NP-complete, and in general, not every problem in P or NP is NP-complete)](https://commons.wikimedia.org/wiki/Special:FilePath/P np np-complete np-hard.svg?width=200 "P≠NP]], while the right side is valid under the assumption that P=NP (except that the empty language and its complement are never NP-complete, and in general, not every problem in P or NP is NP-complete)")
![reductions]] typically used to prove their NP-completeness](https://commons.wikimedia.org/wiki/Special:FilePath/Relative NPC chart.svg?width=200 "reductions]] typically used to prove their NP-completeness")
COMPLEXITY CLASS
NP-complete problem; NP-complete problems; NP complete; NP completeness; NP-C; Np complete; Np-complete; NP-complete language; Np-complete problem; NP-Completeness; Np completeness; Non-deterministic polynomial-time complete; NP-Complete; Nondeterministic Polynomial Complete; Non polynomial complete; Np-Complete; NP-complete; NP-incomplete
<complexity> (NPC, Nondeterministic Polynomial time complete)
A set or property of computational decision problems which
is a subset of NP (i.e. can be solved by a
nondeterministic Turing Machine in polynomial time),
with the additional property that it is also NP-hard. Thus
a solution for one NP-complete problem would solve all
problems in NP. Many (but not all) naturally arising problems
in class NP are in fact NP-complete.
There is always a polynomial-time algorithm for transforming
an instance of any NP-complete problem into an instance of any
other NP-complete problem. So if you could solve one you
could solve any other by transforming it to the solved one.
The first problem ever shown to be NP-complete was the
satisfiability problem. Another example is {Hamilton's
problem}.
See also computational complexity, halting problem,
Co-NP, NP-hard.
http://fi-www.arc.nasa.gov/fia/projects/bayes-group/group/NP/.
[Other examples? ]
(1995-04-10)
Complete androgen insensitivity syndrome
INTERSEX CONDITION THAT RESULTS IN A PHENOTYPIC FEMALE
Complete Androgen Insensitivity Syndrome; Complete androgen insensitivity; Total androgen insensitivity syndrome; Complete AIS; Goldberg-Maxwell syndrome
Complete androgen insensitivity syndrome (CAIS) is an AIS condition that results in the complete inability of the cell to respond to androgens. As such, the insensitivity to androgens is only clinically significant when it occurs in individuals who are exposed to significant amounts of testosterone at some point in their lives.
Complete variety
TYPE OF ALGEBRAIC VARIETY
Completeness of projective varieties; Complete algebraic variety
In mathematics, in particular in algebraic geometry, a complete algebraic variety is an algebraic variety X, such that for any variety Y the projection morphism
Degree-preserving randomization
Degree Preserving Randomization
Degree Preserving Randomization is a technique used in Network Science that aims to assess whether or not variations observed in a given graph could simply be an artifact of the graph's inherent structural properties rather than properties unique to the nodes, in an observed network.
Википедия
Mendelian randomization
In epidemiology, Mendelian randomization (commonly abbreviated to MR) is a method using measured variation in genes to interrogate the causal effect of an exposure on an outcome. Under key assumptions (see below), the design reduces both reverse causation and confounding, which often substantially impede or mislead the interpretation of results from epidemiological studies.
The study design was first proposed in 1986 and subsequently described by Gray and Wheatley as a method for obtaining unbiased estimates of the effects of a putative causal variable without conducting a traditional randomized controlled trial (i.e. the "gold standard" in epidemiology for establishing causality). These authors also coined the term Mendelian randomization.
