Modified Ridge Parameters for Seemingly Unrelated Regression Model

In this paper, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine ridge parameters have been modified and compared in terms of the trace mean squared error (TMSE) and (PR) criterion. The results from this extended study are the also compared with those founded by AS. A simulation study has been conducted to compare the performance of the modified ridge parameters. The results showed that under certain conditions the performance of the multivariate ridge regression estimators based on SUR ridge RMSmax is superior to other estimators in terms of TMSE and PR criterion. In large samples and when the collinearity between the explanatory variables is not high the unbiased SUR, estimator produces a smaller TMSEs.Multicollinearity; modified SUR ridge regression; Monte Carlo simulations; TMSE

Developing and Assessing a Social Networking Framework for Universities in Saudi Arabia

The interactive capacities of social networking have unleashed the potential for enhancing teaching and learning in the higher education sector. This research focuses on Saudi Arabia in order to determine the factors that must be considered for developing a social networking framework for the use in universities. The main research outcome is a social networking framework for higher education in Saudi Arabia which can be used by a range of stakeholders within higher educatio

New Liu Estimators for the Poisson Regression Model: Method and Application

A new shrinkage estimator for the Poisson model is introduced in this paper. This method is a generalization of the Liu (1993) estimator originally developed for the linear regression model and will be generalised here to be used instead of the classical maximum likelihood (ML) method in the presence of multicollinearity since the mean squared error (MSE) of ML becomes inflated in that situation. Furthermore, this paper derives the optimal value of the shrinkage parameter and based on this value some methods of how the shrinkage parameter should be estimated are suggested. Using Monte Carlo simulation where the MSE and mean absolute error (MAE) are calculated it is shown that when the Liu estimator is applied with these proposed estimators of the shrinkage parameter it always outperforms the ML. Finally, an empirical application has been considered to illustrate the usefulness of the new Liu estimators.Estimation; MSE; MAE; Multicollinearity; Poisson; Liu; Simulation

Evaluating Morphological Computation in Muscle and DC-motor Driven Models of Human Hopping

In the context of embodied artificial intelligence, morphological computation refers to processes which are conducted by the body (and environment) that otherwise would have to be performed by the brain. Exploiting environmental and morphological properties is an important feature of embodied systems. The main reason is that it allows to significantly reduce the controller complexity. An important aspect of morphological computation is that it cannot be assigned to an embodied system per se, but that it is, as we show, behavior- and state-dependent. In this work, we evaluate two different measures of morphological computation that can be applied in robotic systems and in computer simulations of biological movement. As an example, these measures were evaluated on muscle and DC-motor driven hopping models. We show that a state-dependent analysis of the hopping behaviors provides additional insights that cannot be gained from the averaged measures alone. This work includes algorithms and computer code for the measures.Comment: 10 pages, 4 figures, 1 table, 5 algorithm

A New Liu Type of Estimator for the Restricted SUR Estimator

A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived. The new estimator may have a lower MSE than the traditional estimators. It was shown using simulation techniques the new shrinkage estimator outperforms the commonly used estimators in the presence of multicollinearity

Comparing Three Instructional Modes for an Engineering Economy Course

This study compares three instructional modes in an “Engineering Economy” course: online, face-to-face (FtF), and flipped. Engineering Economy is a core course in this study and incorporates students with diverse backgrounds from different engineering majors. To discern the relation between student characteristics and teaching modality, an online questionnaire was designed for each mode and distributed over a two-year period. Data was collected and several statistical analyses were conducted to study the relationship between pedagogical delivery modes and various student-based factors such as gender, age, course load, living distance from campus, computer skills, work status, and first language. Students’ performance, persistence, and knowledge self-evaluation were also compared in different modes. The statistical analyses of data at 95% confidence level show that among all the factors, only the ratio of native English speakers, course load and work category differ significantly in different instructional modes. No statistically significant difference was observed between different modes for other factors

On developing ridge regression parameters : a graphical investigation

In this paper we review some existing and propose some new estimators for estimating the ridge parameter. All in all 19 different estimators have been studied. The investigation has been carried out using Monte Carlo simulations. A large number of different models have been investigated where the variance of the random error, the number of variables included in the model, the correlations among the explanatory variables, the sample size and the unknown coefficient vector were varied. For each model we have performed 2000 replications and presented the results both in term of figures and tables. Based on the simulation study, we found that increasing the number of correlated variable, the variance of the random error and increasing the correlation between the independent variables have negative effect on the mean squared error. When the sample size increases the mean squared error decreases even when the correlation between the independent variables and the variance of the random error are large. In all situations, the proposed estimators have smaller mean squared error than the ordinary least squares and other existing estimators

Context-based personalization of web services composition and provisioning

This paper presents an approach that aims at personalizing Web services composition and provisioning using context. Composition addresses the situation of a user\u27s request that cannot be satisfied by any available service, and thus requires the combination of several Web services. Provisioning focuses on the deployment of Web services according to users\u27 preferences. A Web service is an accessible application that other applications and humans can discover and trigger. Context is the information that characterizes the interactions between humans, applications, and the surrounding environment. Web services are subject to personalization if there is a need of accommodating users\u27 preferences during service performance and outcome delivery. To be able to track personalization in terms of what happened, what is happening, and what might happen three types of context are devised, and they are referred to as user-, Web service-, and resource-context

Dynamics & Predictions in the Co-Event Interpretation

Sorkin has introduced a new, observer independent, interpretation of quantum mechanics that can give a successful realist account of the 'quantum microworld' as well as explaining how classicality emerges at the level of observable events for a range of systems including single time 'Copenhagen measurements'. This 'co-event interpretation' presents us with a new ontology, in which a single 'co-event' is real. A new ontology necessitates a review of the dynamical & predictive mechanism of a theory, and in this paper we begin the process by exploring means of expressing the dynamical and predictive content of histories theories in terms of co-events.Comment: 35 pages. Revised after refereein