All the models were estimated by using a full information maximum
likelihood estimator.
The performance of the full information maximum
likelihood estimator in multiple regression models with missing data
All models were analysed in Mplus v7.11 using the maximum
likelihood estimator [48].
Multilevel autoregressive model with restricted maximum
likelihood estimator was utilized in order to explore cross-lagged associations between schema modes and personality psychopathology scores over subsequent measurements at baseline, 6, 12, 18, 24 and 36 months.
A maximum
likelihood estimator robust for skewness was used.
While a meta - analysis on nine studies is fairly reliable, a meta - analysis including only three studies may provide a less accurate estimate of the overall effect.64 We therefore applied the random - effects model using the profile -
likelihood estimator.
-- We plotted telemetry fixes in location of a signal (LOAS 2.07; Ecological Software Solutions, Urnäsch, Switzerland) using the maximum
likelihood estimator (MLE) algorithm, with best biangulation as the default estimator when MLE failed.
SUMMARY OF TECHNICAL SKILLS * Data Science / Statistics - Statistics I: Machine Learning / Data Mining / Predictive Modeling, Time Series, Regressions, - Statistics II / Statistical programming languages: SAS, R, Spark, Python (Numpy, Pandas, IPython,), Scala, MatLab - Database querying language: SQL - Statistics III: Null hypothesis, P - Value, Maximum
Likelihood Estimators, Confidence Intervals,.
Not exact matches
In this study, at - site Gumbel MOM and GEV extreme value analyses based on L - moment, maximum
likelihood (MLE), and generalized maximum
likelihood (GML)
estimators are compared against RFA with L - moment methods at stations in southern British Columbia, Canada via cross-validation and Monte Carlo simulations.