Sentence examples for missing data estimating from inspiring English sources

For the steam processing part, a correlation base technique was chosen as such techniques are able to correlate well among sensors and are able to efficiently handle missing data (estimating missing values by way of linear regression models using other sensors during that period of time).

Rasch model is based on item response theory (IRT) and it allows missing data estimate examinee' stress resistant ability [ 37, 38].

Indeed, adjusting for missing data, estimated trends showed evidence of decreases in some reported sexual risk behaviour between 2005 and 2011, including fewer men and women reporting multiple sexual partnerships and concurrency.

The pooled estimates of the treatment group effect with imputed data were −1.295%5% confidence interval −4.2 to 1.9) for PRWE and −3.2 (−6.2 to −0.1) for DASH, with the percentage of the variability attributable to the uncertainty caused by the missing data, estimated at 5.8% and 5.5% for the two outcome measures, respectively.

All imputation methods that do not relay on physical models must base their missing data estimates on the signals' characteristics and behavior.

After data are cleaned, the missing values analysis procedure in SPSS Version 22 will be used to: describe the pattern of missing data; estimate means, standard deviations, covariance and correlations for different missing value methods; and impute the missing values with estimated means from regression or expectation minimization methods.

Few missing data were estimated using the linear regression method [18].

Zhuang et al. (2017) discuss the effects of newly developed replenishments of the missing data on estimated parameters of the epidemic-type aftershock sequence (ETAS) model.

The unknown continuous states are regarded as missing data and estimated with a fixed-interval Kalman smoother in the E step.

For schools with data missing for only one of the four years, the year of missing data is estimated as the average debt of the three other years for which data is available.

The algorithm is composed of two steps: E-step: On this step, the missing data are estimated using the observed data and the actual status of the model parameters.