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Titlebook: Disturbances in the linear model, estimation and hypothesis testing; Estimation and Hypot C. Dubbelman Book 1978 H. E. Stenfert Kroese B.V.

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發(fā)表于 2025-3-21 19:14:32 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Disturbances in the linear model, estimation and hypothesis testing
副標(biāo)題Estimation and Hypot
編輯C. Dubbelman
視頻videohttp://file.papertrans.cn/283/282045/282045.mp4
圖書封面Titlebook: Disturbances in the linear model, estimation and hypothesis testing; Estimation and Hypot C. Dubbelman Book 1978 H. E. Stenfert Kroese B.V.
描述1. 1. The general linear model All econometric research is based on a set of numerical data relating to certain economic quantities, and makes infer- ences from the data about the ways in which these quanti- ties are related (Malinvaud 1970, p. 3). The linear relation is frequently encountered in applied econometrics. Let y and x denote two economic quantities, then the linear relation between y and x is formalized by: where {31 and {32 are constants. When {31 and {32 are known numbers, the value of y can be calculated for every given value of x. Here y is the dependent variable and x is the explanatory variable. In practical situations {31 and {32 are unknown. We assume that a set of n observations on y and x is available. When plotting the ob- served pairs (x l‘ YI)‘ (x ‘ Y2)‘ . . . , (x , Y n) into a diagram with x 2 n measured along the horizontal axis and y along the vertical axis it rarely occurs that all points lie on a straight line. Generally, no b 1 and b exist such that Yi = b + b x for i = 1,2, . . . ,n. Unless 2 l 2 i the diagram clearly suggests another type of relation, for instance quadratic or exponential, it is customary to adopt linearity in order to keep the ana
出版日期Book 1978
關(guān)鍵詞econometrics; research; value-at-risk
版次1
doihttps://doi.org/10.1007/978-1-4684-6956-1
isbn_softcover978-90-207-0772-4
isbn_ebook978-1-4684-6956-1
copyrightH. E. Stenfert Kroese B.V. 1978
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沙發(fā)
發(fā)表于 2025-3-21 20:27:39 | 只看該作者
disturbance estimation,, as we shall see. We are, of course, interested in the vector which gives best testing results, i.e. maximal power. Unfortunately, we did not succeed in translating the maximal power criterion into a manageable optimality criterion for .. Therefore we adopt a criterion based on other considerations.
板凳
發(fā)表于 2025-3-22 02:07:40 | 只看該作者
https://doi.org/10.1007/978-981-19-3132-1and . is formalized by:.where .. and .. are constants. When .. and .. are known numbers, the value of . can be calculated for every given value of .. Here . is the dependent variable and . is the explanatory variable.
地板
發(fā)表于 2025-3-22 08:16:23 | 只看該作者
5#
發(fā)表于 2025-3-22 12:36:07 | 只看該作者
https://doi.org/10.1007/978-1-4684-6956-1econometrics; research; value-at-risk
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發(fā)表于 2025-3-22 14:47:34 | 只看該作者
978-90-207-0772-4H. E. Stenfert Kroese B.V. 1978
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發(fā)表于 2025-3-22 18:55:45 | 只看該作者
8#
發(fā)表于 2025-3-23 00:28:29 | 只看該作者
https://doi.org/10.1007/978-981-19-3132-1and . is formalized by:.where .. and .. are constants. When .. and .. are known numbers, the value of . can be calculated for every given value of .. Here . is the dependent variable and . is the explanatory variable.
9#
發(fā)表于 2025-3-23 02:52:13 | 只看該作者
The Wiedemann-Franz Law in YbRh2Si2,, as we shall see. We are, of course, interested in the vector which gives best testing results, i.e. maximal power. Unfortunately, we did not succeed in translating the maximal power criterion into a manageable optimality criterion for .. Therefore we adopt a criterion based on other considerations
10#
發(fā)表于 2025-3-23 08:27:08 | 只看該作者
Thermal and Statistical Physicsurpose, we developed the . estimator . of .′.; see (3.2). The estimator depends on the following matrices: the . × . matrix ., the . × . matrix ., the . × . matrix Ω = . ′, the . × . matrix Г, the . × . matrix ., and the .-element vector y. Both . and y are specified by observation and it is assumed
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