Proportional representationProportional representation (PR) refers to a type of electoral system under which subgroups of an electorate are reflected proportionately in the elected body. The concept applies mainly to political divisions (political parties) among voters. The essence of such systems is that all votes cast - or almost all votes cast - contribute to the result and are effectively used to help elect someone - not just a bare plurality or (exclusively) the majority - and that the system produces mixed, balanced representation reflecting how votes are cast.
Mixed-member proportional representationMixed-member proportional representation (MMP or MMPR) is a mixed electoral system in which votes are cast for both local elections and also for overall party vote tallies, which are used to allocate additional members to produce or deepen overall proportional representation. In some MMP systems, voters get two votes: one to decide the representative for their single-seat constituency, and one for a political party. In Denmark and others, the single vote cast by the voter is used for both the local election (in a multi-member or single-seat district), and for the overall top-up.
Average-case complexityIn computational complexity theory, the average-case complexity of an algorithm is the amount of some computational resource (typically time) used by the algorithm, averaged over all possible inputs. It is frequently contrasted with worst-case complexity which considers the maximal complexity of the algorithm over all possible inputs. There are three primary motivations for studying average-case complexity.
Radioactive wasteRadioactive waste is a type of hazardous waste that contains radioactive material. Radioactive waste is a result of many activities, including nuclear medicine, nuclear research, nuclear power generation, nuclear decommissioning, rare-earth mining, and nuclear weapons reprocessing. The storage and disposal of radioactive waste is regulated by government agencies in order to protect human health and the environment.
High-level radioactive waste managementHigh-level radioactive waste management concerns how radioactive materials created during production of nuclear power and nuclear weapons are dealt with. Radioactive waste contains a mixture of short-lived and long-lived nuclides, as well as non-radioactive nuclides. There was reportedly some of high-level nuclear waste stored in the United States in 2002. The most troublesome transuranic elements in spent fuel are neptunium-237 (half-life two million years) and plutonium-239 (half-life 24,000 years).
Best, worst and average caseIn computer science, best, worst, and average cases of a given algorithm express what the resource usage is at least, at most and on average, respectively. Usually the resource being considered is running time, i.e. time complexity, but could also be memory or some other resource. Best case is the function which performs the minimum number of steps on input data of n elements. Worst case is the function which performs the maximum number of steps on input data of size n.
Plurality votingPlurality voting refers to electoral systems in which a candidate(s), who poll more than any other counterpart (that is, receive a plurality), are elected. In systems based on single-member districts, it elects just one member per district and may also be referred to as first-past-the-post (FPTP), single-member plurality (SMP/SMDP), single-choice voting (an imprecise term as non-plurality voting systems may also use a single choice), simple plurality or relative majority (as opposed to an absolute majority, where more than half of votes is needed, this is called majority voting).
Single transferable voteThe single transferable vote (STV) is a multi-winner electoral system in which each voter casts a single vote in the form of a ranked-choice ballot. Voters have the option to rank candidates, and their vote may be transferred according to alternate preferences if their preferred candidate is eliminated or elected with surplus votes, so that their vote is used to elect someone they prefer over others in the running. STV aims to approach proportional representation based on votes cast in the district where it is used, so that each vote is worth about the same as another.
Mixed-member majoritarian representationMixed member majoritarian representation (MMM) is type of a mixed electoral system combining majoritarian and proportional methods, where the disproportional results of the majoritarian side of the system prevail over the proportional component. Mixed member majoritarian systems are therefore also as a type of semi-proportional representation, and are usually contrasted with mixed-member proportional representation (MMP) which aims to provide proportional representation via additional compensation ("top-up") seats.
Duverger's lawIn political science, Duverger's law holds that single-ballot majoritarian elections with single-member districts (such as first past the post) tend to favor a two-party system. The theory is attributed to Maurice Duverger, a French sociologist who published several papers on it in the 1950s and 1960s. In the course of further research, other political scientists began calling the effect a "law" or principle. As a corollary to the law, Duverger also asserted that proportional representation favors multi-partyism, as does the plurality system with runoff elections.
Bounded setIn mathematical analysis and related areas of mathematics, a set is called bounded if it is, in a certain sense, of finite measure. Conversely, a set which is not bounded is called unbounded. The word "bounded" makes no sense in a general topological space without a corresponding metric. Boundary is a distinct concept: for example, a circle in isolation is a boundaryless bounded set, while the half plane is unbounded yet has a boundary. A bounded set is not necessarily a closed set and vice versa.
Approximation algorithmIn computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems (in particular NP-hard problems) with provable guarantees on the distance of the returned solution to the optimal one. Approximation algorithms naturally arise in the field of theoretical computer science as a consequence of the widely believed P ≠ NP conjecture. Under this conjecture, a wide class of optimization problems cannot be solved exactly in polynomial time.
Worst-case complexityIn computer science (specifically computational complexity theory), the worst-case complexity measures the resources (e.g. running time, memory) that an algorithm requires given an input of arbitrary size (commonly denoted as n in asymptotic notation). It gives an upper bound on the resources required by the algorithm. In the case of running time, the worst-case time complexity indicates the longest running time performed by an algorithm given any input of size n, and thus guarantees that the algorithm will finish in the indicated period of time.
Upper and lower boundsIn mathematics, particularly in order theory, an upper bound or majorant of a subset S of some preordered set (K, ≤) is an element of K that is greater than or equal to every element of S. Dually, a lower bound or minorant of S is defined to be an element of K that is less than or equal to every element of S. A set with an upper (respectively, lower) bound is said to be bounded from above or majorized (respectively bounded from below or minorized) by that bound.
Least-upper-bound propertyIn mathematics, the least-upper-bound property (sometimes called completeness or supremum property or l.u.b. property) is a fundamental property of the real numbers. More generally, a partially ordered set X has the least-upper-bound property if every non-empty subset of X with an upper bound has a least upper bound (supremum) in X. Not every (partially) ordered set has the least upper bound property. For example, the set of all rational numbers with its natural order does not have the least upper bound property.
Infimum and supremumIn mathematics, the infimum (abbreviated inf; plural infima) of a subset of a partially ordered set is the greatest element in that is less than or equal to each element of if such an element exists. In other words, it is the greatest element of that is lower or equal to the lowest element of . Consequently, the term greatest lower bound (abbreviated as ) is also commonly used. The supremum (abbreviated sup; plural suprema) of a subset of a partially ordered set is the least element in that is greater than or equal to each element of if such an element exists.
Amortized analysisIn computer science, amortized analysis is a method for analyzing a given algorithm's complexity, or how much of a resource, especially time or memory, it takes to execute. The motivation for amortized analysis is that looking at the worst-case run time can be too pessimistic. Instead, amortized analysis averages the running times of operations in a sequence over that sequence. As a conclusion: "Amortized analysis is a useful tool that complements other techniques such as worst-case and average-case analysis.
Asymptotic analysisIn mathematical analysis, asymptotic analysis, also known as asymptotics, is a method of describing limiting behavior. As an illustration, suppose that we are interested in the properties of a function f (n) as n becomes very large. If f(n) = n2 + 3n, then as n becomes very large, the term 3n becomes insignificant compared to n2. The function f(n) is said to be "asymptotically equivalent to n2, as n → ∞". This is often written symbolically as f (n) ~ n2, which is read as "f(n) is asymptotic to n2".
Stirling's approximationIn mathematics, Stirling's approximation (or Stirling's formula) is an approximation for factorials. It is a good approximation, leading to accurate results even for small values of . It is named after James Stirling, though a related but less precise result was first stated by Abraham de Moivre. One way of stating the approximation involves the logarithm of the factorial: where the big O notation means that, for all sufficiently large values of , the difference between and will be at most proportional to the logarithm.
Uniform convergenceIn the mathematical field of analysis, uniform convergence is a mode of convergence of functions stronger than pointwise convergence. A sequence of functions converges uniformly to a limiting function on a set as the function domain if, given any arbitrarily small positive number , a number can be found such that each of the functions differs from by no more than at every point in .
