Sentence examples for models for indices from inspiring English sources

Exact(2)

Adjustment of BMI models for indices of central obesity did not affect the estimation of diabetes risk in men, but led to an attenuation of risk estimates in women.

Note that models for indices will inevitably have relatively large RSDs because the outcome includes two sources of measurement error (e.g., BMI includes measurement error in weight and height).

Similar(58)

The TLCF i index sharing model for the effective failed component j is given by TLCF_{i} (D to j) = sumlimits_{t in D} {frac{{F_{t} }}{{m_{t} }}} (3). 3) Tracing model for indices TLCC i-max and TLCE i.

2) Tracing model for index SCF.

Goh [8] formulated a security model for indexes known as semantic security (or indistinguishability) against an adaptive chosen keyword attack (IND-CKA), and they also proposed an secure index scheme in the model.

Lawder et al. [21] efficiently executed range queries in data indexed by the Hilbert curve, while Faloutsos [22] presented a mathematical model for indexing the multi-attribute records of a data collection, using Gray-codes instead of binary values.

The SCF tracing model for the effective failed component j is given by SCF(S to j) = sumlimits_{t in S} {frac{{F_{t} }}{{m_{t} }}} (7). 3) Tracing model for index SCC max and SCE.

According to the PSP described above, the TLCP i index tracing model for the effective failed component j is given by TLCP_{i} (D to j) = sumlimits_{t in D} {frac{{P_{t} }}{{m_{t} }}} (2 where m t is the number of effective failed components in the t th TC state t. 2) Tracing model for index TLCF i.

Similarly, the TLCC i-max and TLCE i sharing models for the effective failed component j are given by TLC C_{i-hbox{max } (D to j) = frac{{TLCC_{i-hbox{max} } }}{{m_{t} }} (4) TLCE_{i} (D to j) = sumlimits_{t in D} {frac{{TLCt} }}{{m_{t} }}} times TLCC_{{_{it} }} times 8760 (5). 1) Tracing model for index SCP.

(2013) and Kim (2003) use different SVR models for stock index forecasting.

Multivariate logistic regression determines the performance of the models for each index as measured by the c-statistic and Hosmer-Lemeshow chi square.

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