SRRE

AcronymDefinition
SRRESource Reduction and Recycling Element
SRRESeacoast Region Real Estate (real estate sales and rentals; UK)
SRRESteroid-Resistant Rejection Episodes
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References in periodicals archive ?
Note that the predictors based on the MRE, SRRE, SRAURE, SRLE, SRAULE, SRPCRE, SRrk, and SRrd are denoted by [mathematical expression not reproducible], and [[??].sub.SRrd], respectively.
Table B2 shows the estimated SMSE values of MRE, SRRE, SRAURE, SRLE, SRAULE, SRPCRE, SRrk, and SRrd for the regression model when (l, p) = (4, 0), (l, p) = (3, 1), and (l, p) = (2, 2) with respect to shrinkage parameters (k/d), where I denotes the number of variables in the model and p denotes the number ofmisspecified variables.
From Table B2, we can observe that the MRE is superior to the other estimators when (l, p) = (4, 0) and SRAULE, SRRE, SRLE, and SRAURE outperform the other estimators for (k/d) < 0.2, 0.2 [less than or equal to] (k/d) < 0.5, 0.5 [less than or equal to] (k/d) < 0.7, and (k/d) [greater than or equal to] 0.7, respectively, when (I, p) = (3,1).
From Table B3, we further observe that predictors based on SRLE and SRRE outperform the other predictors for (k/d) < 0.5 and (k/d) [greater than or equal to] 0.5, respectively, when (l, p) = (4, 0) and (l, p) = (3, 1), and predictors based on SRrd and SRrk are superior to the other predictors for (k/d) < 0.5 and (k/d) [greater than or equal to] 0.5, respectively, when (l, p) = (2, 2).
Further, SRLE and SRRE are superior to the other estimators for (k/d) < 0.5 and (k/d) [greater than or equal to] 0.5, respectively, when (l, p) = (3, 2) under [rho] = 0.9.
Similarly, SRAULE, SRRE, SRLE, and SRAURE are superior to the other estimators when (k/d) < 0.2, 0.2 [less than or equal to] (k/d) < 0.5, 0.5 [less than or equal to] (k/d) < 0.7, and (k/d) [greater than or equal to] 0.7, respectively, when (l, p) = (4, 1), and both SRLE and SRRE outperform the other estimators for (k/d) < 0.5 and (k/d) [greater than or equal to] 0.5, respectively, when (l, p) = (3, 2) and [rho] = 0.99.
The results in Table B6 indicate that MRE is superior to the other estimators when (l, p) = (5, 0), and SRAULE, SRRE, SRLE, and SRAURE outperform the other estimators for (k/d) < 0.2, 0.2 [less than or equal to] (k/d) < 0.5, 0.5 [less than or equal to] (k/d) < 0.7, and (k/d) [greater than or equal to] 0.7, respectively, when (I, p) = (4,1).