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The information filter is then run backwards to form the prior backward estimates.
The forward and backward estimates were then statistically combined to obtain a smoothed estimate.
The forward and backward estimates are then optimally combined to generate the smoothed estimates.
The final model was then reached by using stepwise backward estimates, removing all variables with P > 0.15.
We applied these formulas to backward-estimate both the maternal serum PCB and DDE concentrations at the time of each pregnancy.
But the progress has made it difficult for statisticians to calculate backward to estimate time of infection.
In these cases, we used the PBB decay model to extrapolate backward to estimate maternal PBB at conception.
Next, multivariate linear regression models with backward elimination estimated conditional associations between childhood circumstances and each health outcome.
A multivariate linear regression model with backward elimination estimated conditional associations between childhood circumstances and adult educational attainment (SES); explanatory variables with p values ≤0.20 were retained; all models forced inclusion of demographic variables age, sex and race/ethnicity (Model 1).
The forward-backward estimation-maximization algorithm is used to estimate the modeling parameters for HMM.
The modified spatial smoothing processing (MSSP) method exploits the translation invariance and the backward propagation to estimate the covariance matrix.
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