- error sum squares
- 误差平方和
English-Chinese Dictionary of Agriculture (英汉农业大词典). 2013.
error sum squares
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Sum of squares — is a concept that permeates much of inferential statistics and descriptive statistics. More properly, it is the sum of the squared deviations . Mathematically, it is an unscaled, or unadjusted measure of dispersion (also called variability). When … Wikipedia
Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… … Wikipedia
Lack-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… … Wikipedia
Linear least squares/Proposed — Linear least squares is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to observations obtained from experiments. Mathematically, it can be stated as the problem of… … Wikipedia
Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… … Wikipedia
Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression … Wikipedia
Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… … Wikipedia
Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… … Wikipedia
Total least squares — The bivariate (Deming regression) case of Total Least Squares. The red lines show the error in both x and y. This is different from the traditional least squares method which measures error parallel to the y axis. The case shown, with deviations… … Wikipedia
Mean squared error — In statistics, the mean squared error (MSE) of an estimator is one of many ways to quantify the difference between values implied by a kernel density estimator and the true values of the quantity being estimated. MSE is a risk function,… … Wikipedia
Explained sum of squares — In statistics, an explained sum of squares (ESS) is the sum of squared predicted values in a standard regression model (for example y {i}=a+bx {i}+epsilon {i}), where y {i} is the response variable, x {i} is the explanatory variable, a and b are… … Wikipedia
