Empirical distribution functionIn statistics, an empirical distribution function (commonly also called an empirical cumulative distribution function, eCDF) is the distribution function associated with the empirical measure of a sample. This cumulative distribution function is a step function that jumps up by 1/n at each of the n data points. Its value at any specified value of the measured variable is the fraction of observations of the measured variable that are less than or equal to the specified value.
Independence (probability theory)Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically independent, or stochastically independent if, informally speaking, the occurrence of one does not affect the probability of occurrence of the other or, equivalently, does not affect the odds. Similarly, two random variables are independent if the realization of one does not affect the probability distribution of the other.
Elementary eventIn probability theory, an elementary event, also called an atomic event or sample point, is an event which contains only a single outcome in the sample space. Using set theory terminology, an elementary event is a singleton. Elementary events and their corresponding outcomes are often written interchangeably for simplicity, as such an event corresponding to precisely one outcome. The following are examples of elementary events: All sets where if objects are being counted and the sample space is (the natural numbers).
Probability theoryProbability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expressing it through a set of axioms. Typically these axioms formalise probability in terms of a probability space, which assigns a measure taking values between 0 and 1, termed the probability measure, to a set of outcomes called the sample space.
WasteWaste (or wastes) are unwanted or unusable materials. Waste is any substance discarded after primary use, or is worthless, defective and of no use. A by-product, by contrast is a joint product of relatively minor economic value. A waste product may become a by-product, joint product or resource through an invention that raises a waste product's value above zero. Examples include municipal solid waste (household trash/refuse), hazardous waste, wastewater (such as sewage, which contains bodily wastes (feces and urine) and surface runoff), radioactive waste, and others.
Arc routingArc routing problems (ARP) are a category of general routing problems (GRP), which also includes node routing problems (NRP). The objective in ARPs and NRPs is to traverse the edges and nodes of a graph, respectively. The objective of arc routing problems involves minimizing the total distance and time, which often involves minimizing deadheading time, the time it takes to reach a destination.
Kerbside collectionKerbside collection or curbside collection is a service provided to households, typically in urban and suburban areas, of collecting and disposing of household waste and recyclables. It is usually accomplished by personnel using specially built vehicles to pick up household waste in containers that are acceptable to, or prescribed by, the municipality and are placed on the kerb. Before the 20th century, the amount of waste produced by a household was relatively small.
Biodegradable wasteBiodegradable waste includes any organic matter in waste which can be broken down into carbon dioxide, water, methane, compost, humus, and simple organic molecules by micro-organisms and other living things by composting, aerobic digestion, anaerobic digestion or similar processes. It mainly includes kitchen waste (spoiled food, trimmings, inedible parts), ash, soil, dung and other plant matter. In waste management, it also includes some inorganic materials which can be decomposed by bacteria.
Empirical processIn probability theory, an empirical process is a stochastic process that describes the proportion of objects in a system in a given state. For a process in a discrete state space a population continuous time Markov chain or Markov population model is a process which counts the number of objects in a given state (without rescaling). In mean field theory, limit theorems (as the number of objects becomes large) are considered and generalise the central limit theorem for empirical measures.
Routing loopA routing loop is a common problem with various types of networks, particularly computer networks. They are formed when an error occurs in the operation of the routing algorithm, and as a result, in a group of nodes, the path to a particular destination forms a loop. In the simplest version, a routing loop of size two, node A thinks that the path to some destination (call it C) is through its neighbouring node, node B. At the same time, node B thinks that the path to C starts at node A.
