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16:23 Mar 26, 2018 |
Polish to English translations [PRO] Science - Mathematics & Statistics | |||||||
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| Selected response from: Frank Szmulowicz, Ph. D. United States Local time: 08:09 | ||||||
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Summary of answers provided | ||||
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3 | observation vector of the response (dependent) variable |
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observation vector of the response (dependent) variable Explanation: Contemporary measuring technology in condition monitoring of critical systems allow us to form diagnostic symptom observation vector, with components different physically, and to extract fault information from such created symptom observation matrix. Wspóáczesne technologie pomiarowe w diagnostyce obiektów krytycznych pozwalają nam formuáowaü bardzo bogaty wektor obserwacji diagnostycznej obiektu, ze skáadowymi o róĪnej naturze fizykalnej. http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztec... cccccccccccccccccccccccccccc Zmienna objaśniana (ang. response variable) Zmienna objaśniana to inaczej zmienna zależna. https://dobrebadania.pl/zmienna-objasniana-ang-response-vari... -------------------------------------------------- Note added at 1 hr (2018-03-26 17:49:07 GMT) -------------------------------------------------- ccccccccccc General linear mixed models, notation and assumptions. Consider the general linear mixed model. (1) y = X β + Z v + ϵ ,. where y is an N × 1 observation vector of the response variable, X and Z are N × p and N × M matrices, respectively, of the explanatory variables, β is a p × 1 unknown vector of the regression coefficients https://www.sciencedirect.com/science/article/pii/S0047259X1... -------------------------------------------------- Note added at 1 hr (2018-03-26 17:51:08 GMT) -------------------------------------------------- cccccc SIS procedure with specific screening threshold in each iteration and the iteration stops automatically, where the threshold in the first iteration is based on the (1 − α) quantile G −1 (1 − α|Y , F ˜ 1, . . . , Fq), where G(·|Y , F ˜ 1, . . . , Fq) is the cumulative distribution function for the maximum of absolute sample correlations between Y˜ : the observation vector for the response variable and observations for q variables that are independent of the response variable, where the q variables are independent and have CDF’s F1, . . ., Fq respectively. When p is not too large, we take q = p and take Fj to be FˆXj , the empirical CDF of Xj , for j = 1, . . ., p for the first iteration https://arxiv.org/pdf/1801.00105.pdf |
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