Statistical Learning and Big Data
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- ItemFitting Variance Components Model and Fixed Effects Model for One-Way Analysis of Variance to Complex Survey Data(Taylor & Francis, 2012-07-25) Eideh, Abdulhakeem A. H.Under complex survey sampling, in particular when selection probabilities depend on the response variable (informative sampling), the sample and population distributions are different, possibly resulting in selection bias. This article is concerned with this problem by fitting two statistical models, namely: the variance components model (a two-stage model) and the fixed effects model (a single-stage model) for one-way analysis of variance, under complex survey design, for example, two-stage sampling, stratification, and unequal probability of selection, etc. Classical theory underlying the use of the two-stage model involves simple random sampling for each of the two stages. In such cases the model in the sample, after sample selection, is the same as model for the population; before sample selection. When the selection probabilities are related to the values of the response variable, standard estimates of the population model parameters may be severely biased, leading possibly to false inference. The idea behind the approach is to extract the model holding for the sample data as a function of the model in the population and of the first order inclusion probabilities. And then fit the sample model, using analysis of variance, maximum likelihood, and pseudo maximum likelihood methods of estimation. The main feature of the proposed techniques is related to their behavior in terms of the informativeness parameter. We also show that the use of the population model that ignores the informative sampling design, yields biased model fitting.
- ItemGuidelines on Energy Consumption Surveys in the Transport Sector Experiences in Selected Arab Countries(United Nations, 2015-07-01) Eideh, Abdulhakeem; El Gemayel, Therese; Aboul Hosn, WafaIntroduction: Data collection for the 2015 Energy Consumption Survey in Transport Sector (ECSTS) will be conducted between March and May 2015, collecting data for reference year 2014. The goal of the ECSTS is to provide statistical information about energy consumption, expenditures, and energy efficiency in Egypt, Jordan and Palestine, in all modes of transportations, namely: road, railway, maritime, and air. In addition, the goal is to link the resulted statistics to national policies on energy production and consumption based on collected statistics.