“non-parametric regression”的概念、定义、翻译、参考文献-科学参考

non-parametric regression

Statistics

The situation in which a random variable, Y, has expected value g(x₁, x₂,…, x_m), where x₁, x₂,…, x_m are m explanatory variables (see regression) and g is an unknown function. With m=1 and n observations, y1, y2,…, y_n, estimation may proceed using a scatterplot smoother such as loess, or by using kernel regression. In the latter case, to estimate the function g in the regression equation $non-parametric regression$
a commonly used procedure employs the Nadaraya-Watson estimator given by $non-parametric regression$
where K is the chosen kernel (see kernel method).

Economics

A tool for numerical data analysis where the dependence of the variable of interest on the explanatory variable is estimated without assuming any specific functional form and is entirely driven by the data. The predicted value of the dependent variable at a given point is estimated by smoothing its values over some neighbourhood of this point. This method allows for more flexibility in comparison with a linear regression or a nonlinear regression, but requires large amount of data and intensive computations. See also kernel regression.

单词	non-parametric regression
释义	non-parametric regression Statistics The situation in which a random variable, Y, has expected value g(x₁, x₂,…, x_m), where x₁, x₂,…, x_m are m explanatory variables (see regression) and g is an unknown function. With m=1 and n observations, y1, y2,…, y_n, estimation may proceed using a scatterplot smoother such as loess, or by using kernel regression. In the latter case, to estimate the function g in the regression equation $non-parametric regression$ a commonly used procedure employs the Nadaraya-Watson estimator given by $non-parametric regression$ where K is the chosen kernel (see kernel method). Economics A tool for numerical data analysis where the dependence of the variable of interest on the explanatory variable is estimated without assuming any specific functional form and is entirely driven by the data. The predicted value of the dependent variable at a given point is estimated by smoothing its values over some neighbourhood of this point. This method allows for more flexibility in comparison with a linear regression or a nonlinear regression, but requires large amount of data and intensive computations. See also kernel regression.
随便看	Koopmans’ theorem kopje koppie Kopp’s rule Koptev, Yuri Nikolayevich (1940– ) Koran Korangan Korea Korea Advanced Institute of Science and Technology Korea Aerospace Research Institute Korea Multi-Purpose Satellite Korean Committee of Space Technology Korea, North Korean VLBI Network Korean War (1950–53) Korea, South Korea Space Launch Vehicle Kornberg, Arthur Kornienko, Mikhail (1960– ) Korolev, Sergei Pavlovich (1906–66) Koronas Koronis family Korsch telescope Koryo Korzun, Valeri Grigorievich (1953– )