A statistical technique used to establish the relationship of a dependent variable (fund or portfolio) and an independent variable (index) This shows how similar or dissimilar the selected component, less the risk free proxy, is to the market proxy
Usually linear regression is used to explain and/or predict The general form is Y = a + bX + u, where Y is the variable that we are trying to predict; X is the variable that we are using to predict Y, a is the intercept; b is the slope and u is the regression residual The a and b are chosen in a way to minimize the squared sum of the residuals The ability to fit or explain is measured by the R-squared
A statistical technique for relating the sensitivity of the detector array to a constant value that compensates for any irregularities in the detector A least squares fit is performed to determine the regression model In a two-dimensional graphical representation this regression model would be a line that minimizes the sum of the squares of the vertical distances of the intensity values from the line
A form of statistical modelling that attempts to evaluate the relationship between one variable (termed the dependent variable) and one or more other variables (termed the independent variables) It is a form of global analysis as it only produces a single equation for the relationship thus not allowing any variation across the study area Geographically Weighted Regression is a local analysis form of regression
(psychiatry) a defense mechanism in which you flee from reality by assuming a more infantile state
the analysis or measure of the association between a dependent variable and one or more independent variables, usually formulated as an equation in which the independent variables have parametric coefficients, which may enable future values of the dependent variable to be predicted
A statistical technique used to establish the relationship of a dependent variable (e g excess return) and one or more independent variables (e g exposure to market, size, and value risks) Slope coefficients measure the sensitivity of the dependent variable to changes in the independent variables By measuring exactly how large and significant each independent variable has historically been in its relation to the dependent variable, the future value of the dependent variable can be estimated Essentially, regression analysis attempts to measure the degree of correlation between the dependent and independent variables, thereby establishing the latter's predictive values
the slow lowering of sea level and/or raising of the edge of a contin-ent such that the shoreline slowly moves away from the center of the continent, exposing more land above sea level Marine sediments deposited during regres-sion get coarser in size as you move vertically upward through the pile
The statistical counterpart or analog of the functional expression, in ordinary mathematics, on one variable in terms of others Thus, regression curve, regression coefficient
A psychotherapeutic method whereby healing is facilitated by inducing the patient to act out behaviour typical of a an earlier developmental stage
A statistical procedure that is used to describe linear relationships between dependent variables and independent variables
A withdrawal of the sea from the land, due to uplift or a eustatic (qv) drop in sea level See transgression