Deming regressionIn statistics, Deming regression, named after W. Edwards Deming, is an errors-in-variables model which tries to find the line of best fit for a two-dimensional dataset. It differs from the simple linear regression in that it accounts for errors in observations on both the x- and the y- axis. It is a special case of total least squares, which allows for any number of predictors and a more complicated error structure.
Heat recovery ventilationHeat recovery ventilation (HRV), also known as mechanical ventilation heat recovery (MVHR), is an energy recovery ventilation system that operates between two air sources at different temperatures. It's a method that is used to reduce the heating and cooling demands of buildings. By recovering the residual heat in the exhaust gas, the fresh air introduced into the air conditioning system is preheated (or pre-cooled), and the fresh air's enthalpy is reduced before it enters the room, or the air cooler of the air conditioning unit performs heat and moisture treatment.
Multilevel modelMultilevel models (also known as hierarchical linear models, linear mixed-effect model, mixed models, nested data models, random coefficient, random-effects models, random parameter models, or split-plot designs) are statistical models of parameters that vary at more than one level. An example could be a model of student performance that contains measures for individual students as well as measures for classrooms within which the students are grouped.
Peak demandPeak demand on an electrical grid is simply the highest electrical power demand that has occurred over a specified time period (Gönen 2008). Peak demand is typically characterized as annual, daily or seasonal and has the unit of power. Peak demand, peak load or on-peak are terms used in energy demand management describing a period in which electrical power is expected to be provided for a sustained period at a significantly higher than average supply level. Peak demand fluctuations may occur on daily, monthly, seasonal and yearly cycles.
General linear modelThe general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models. In that sense it is not a separate statistical linear model. The various multiple linear regression models may be compactly written as where Y is a matrix with series of multivariate measurements (each column being a set of measurements on one of the dependent variables), X is a matrix of observations on independent variables that might be a design matrix (each column being a set of observations on one of the independent variables), B is a matrix containing parameters that are usually to be estimated and U is a matrix containing errors (noise).
Nonparametric regressionNonparametric regression is a category of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. That is, no parametric form is assumed for the relationship between predictors and dependent variable. Nonparametric regression requires larger sample sizes than regression based on parametric models because the data must supply the model structure as well as the model estimates.
Regression toward the meanIn statistics, regression toward the mean (also called reversion to the mean, and reversion to mediocrity) is the phenomenon where if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer to its mean. Furthermore, when many random variables are sampled and the most extreme results are intentionally picked out, it refers to the fact that (in many cases) a second sampling of these picked-out variables will result in "less extreme" results, closer to the initial mean of all of the variables.
Robust regressionIn robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise (i.e. are not robust to assumption violations).
Canton of UriThe canton of Uri (Kanton Uri ˈuːʁi Chantun Uri; Canton d'Uri; Canton Uri) is one of the 26 cantons of Switzerland and a founding member of the Swiss Confederation. It is located in Central Switzerland. The canton's territory covers the valley of the Reuss between the St. Gotthard Pass and Lake Lucerne. The official language of Uri is (the Swiss variety of Standard) German, but the main spoken dialect is the Alemannic Swiss German called de.
Canton of BernThe canton of Bern or Berne (Kanton Bern; Chantun Berna; canton de Berne; Canton Berna) is one of the 26 cantons forming the Swiss Confederation. Its capital city, Bern, is also the de facto capital of Switzerland. The bear is the heraldic symbol of the canton, displayed on a red-yellow background. Comprising ten districts, Bern is the second-largest canton by both surface area and population. Located in west-central Switzerland, it is surrounded by eleven cantons. It borders the canton of Jura and the canton of Solothurn to the north.
