Cross elasticity of demandIn economics, the cross (or cross-price) elasticity of demand measures the effect of changes in the price of one good on the quantity demanded of another good. This reflects the fact that the quantity demanded of good is dependent on not only its own price (price elasticity of demand) but also the price of other "related" good. The cross elasticity of demand is calculated as the ratio between the percentage change of the quantity demanded for a good and the percentage change in the price of another good, ceteris paribus:The sign of the cross elasticity indicates the relationship between two goods.
Régression des moindres carrés partielsLa régression des moindres carrés partiels a été inventée en 1983 par Svante Wold et son père Herman Wold ; on utilise fréquemment l'abréviation anglaise régression PLS ( et/ou ). La régression PLS maximise la variance des prédicteurs (Xi) = X et maximise la corrélation entre X et la variable à expliquer Y. Cet algorithme emprunte sa démarche à la fois à l'analyse en composantes principales (ACP) et à la régression.
Binomial proportion confidence intervalIn statistics, a binomial proportion confidence interval is a confidence interval for the probability of success calculated from the outcome of a series of success–failure experiments (Bernoulli trials). In other words, a binomial proportion confidence interval is an interval estimate of a success probability p when only the number of experiments n and the number of successes nS are known. There are several formulas for a binomial confidence interval, but all of them rely on the assumption of a binomial distribution.
Tolerance intervalA tolerance interval (TI) is a statistical interval within which, with some confidence level, a specified sampled proportion of a population falls. "More specifically, a 100×p%/100×(1−α) tolerance interval provides limits within which at least a certain proportion (p) of the population falls with a given level of confidence (1−α)." "A (p, 1−α) tolerance interval (TI) based on a sample is constructed so that it would include at least a proportion p of the sampled population with confidence 1−α; such a TI is usually referred to as p-content − (1−α) coverage TI.
Elasticity of a functionIn mathematics, the elasticity or point elasticity of a positive differentiable function f of a positive variable (positive input, positive output) at point a is defined as or equivalently It is thus the ratio of the relative (percentage) change in the function's output with respect to the relative change in its input , for infinitesimal changes from a point . Equivalently, it is the ratio of the infinitesimal change of the logarithm of a function with respect to the infinitesimal change of the logarithm of the argument.
Covariance matrixIn probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between each pair of elements of a given random vector. Any covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the covariance of each element with itself). Intuitively, the covariance matrix generalizes the notion of variance to multiple dimensions.
Coverage probabilityIn statistics, the coverage probability, or coverage for short, is the probability that a confidence interval or confidence region will include the true value (parameter) of interest. It can be defined as the proportion of instances where the interval surrounds the true value as assessed by long-run frequency. The fixed degree of certainty pre-specified by the analyst, referred to as the confidence level or confidence coefficient of the constructed interval, is effectively the nominal coverage probability of the procedure for constructing confidence intervals.
Distance correlationIn statistics and in probability theory, distance correlation or distance covariance is a measure of dependence between two paired random vectors of arbitrary, not necessarily equal, dimension. The population distance correlation coefficient is zero if and only if the random vectors are independent. Thus, distance correlation measures both linear and nonlinear association between two random variables or random vectors. This is in contrast to Pearson's correlation, which can only detect linear association between two random variables.
Regularized least squaresRegularized least squares (RLS) is a family of methods for solving the least-squares problem while using regularization to further constrain the resulting solution. RLS is used for two main reasons. The first comes up when the number of variables in the linear system exceeds the number of observations. In such settings, the ordinary least-squares problem is ill-posed and is therefore impossible to fit because the associated optimization problem has infinitely many solutions.
Rank correlationIn statistics, a rank correlation is any of several statistics that measure an ordinal association—the relationship between rankings of different ordinal variables or different rankings of the same variable, where a "ranking" is the assignment of the ordering labels "first", "second", "third", etc. to different observations of a particular variable. A rank correlation coefficient measures the degree of similarity between two rankings, and can be used to assess the significance of the relation between them.
Cote Z (statistiques)La cote Z correspond au nombre d'écarts types séparant un résultat de la moyenne. Au Québec, cette cote était la cote principalement utilisée pour évaluer le rendement des étudiants collégiaux par les universités. Elle existe toujours en tant que composante de la cote R. La cote Z se calcule de la même façon que la variable centrée réduite : où différence entre le résultat et la moyenne, divisé par l'écart-type valeur Moyenne du groupe Écart type du groupe Les universités du Québec utilisaient la cote Z jusqu'en 1994 pour sélectionner les étudiants.
Price elasticity of supplyThe price elasticity of supply (PES or Es) is a measure used in economics to show the responsiveness, or elasticity, of the quantity supplied of a good or service to a change in its price. Price elasticity of supply, in application, is the percentage change of the quantity supplied resulting from a 1% change in price. Alternatively, PES is the percentage change in the quantity supplied divided by the percentage change in price. When PES is less than one, the supply of the good can be described as inelastic.
