least squares fitting
21Least-Square — Die Methode der kleinsten Quadrate (bezeichnender auch: der kleinsten Fehlerquadrate; englisch: Least Squares Method) ist das mathematische Standardverfahren zur Ausgleichungsrechnung. Es ist eine Wolke aus Datenpunkten gegeben, die physikalische …
22Least Square — Die Methode der kleinsten Quadrate (bezeichnender auch: der kleinsten Fehlerquadrate; englisch: Least Squares Method) ist das mathematische Standardverfahren zur Ausgleichungsrechnung. Es ist eine Wolke aus Datenpunkten gegeben, die physikalische …
23Curve fitting — best fit redirects here. For placing ( fitting ) variable sized objects in storage, see fragmentation (computer). Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points,… …
24Lack-of-fit sum of squares — In statistics, a sum of squares due to lack of fit, or more tersely a lack of fit sum of squares, is one of the components of a partition of the sum of squares in an analysis of variance, used in the numerator in an F test of the null hypothesis… …
25Iterative proportional fitting — The iterative proportional fitting procedure (IPFP, also known as biproportional fitting in statistics, RAS algorithm[1] in economics and matrix raking or matrix scaling in computer science) is an iterative algorithm for estimating cell values of …
26curve fitting — curve fitting, adj. Statistics. the determination of a curve that fits a specified set of points: The method of least squares is commonly used for curve fitting. [1920 25] * * * …
27curve fitting — noun : the determination of a curve of assigned character (as an exponential curve) that approaches most closely or fits best a number of points in a plane * * * curve fitting, adj. Statistics. the determination of a curve that fits a specified… …
28Trend estimation — is a statistical technique to aid interpretation of data. When a series of measurements of a process are treated as a time series, trend estimation can be used to make and justify statements about tendencies in the data. By using trend estimation …
29Singular value decomposition — Visualization of the SVD of a 2 dimensional, real shearing matrix M. First, we see the unit disc in blue together with the two canonical unit vectors. We then see the action of M, which distorts the disk to an ellipse. The SVD decomposes M into… …
30Scale-invariant feature transform — Feature detection Output of a typical corner detection algorithm …
