Diverse classifier ensemble creation based on heuristic dataset modification

Bagging and Boosting are two main ensemble approaches consolidating the decisions of several hypotheses. The diversity of the ensemble members is considered to be a significant element to obtain generalization error. Here, an inventive method called EBAGTS (ensemble-based artificially generated training samples) is proposed to generate ensembles. It manipulates training examples in three ways in order to build various hypotheses straightforwardly: drawing a sub-sample from training set, reducing/raising error-prone training instances, and reducing/raising local instances around error-prone regions. The proposed method is a straightforward, generic framework utilizing any base classifier as its ensemble members to assemble a powerfully built combinational classifier. Decision-tree classifier and multilayer perceptron classifier as some basic classifiers have been employed in the experiments to indicate the proposed method accomplish higher predictive accuracy compared to meta-learning algorithms like Boosting and Bagging. Furthermore, EBAGTS outperforms Boosting more impressively as the training data set gets broader. It is illustrated that EBAGTS can fulfill better performance comparing to the state of the art.     

Classification rules for identifying individuals at high risk of developing myocardial infarction based on ApoB,ApoA1 and the ratio were determined using a Bayesian approach

We have developed a new approach to determine the threshold of a biomarker that maximizes the classification accuracy of a disease. We consider a Bayesian estimation procedure for this purpose and illustrate the method using a real data set. In particular, we determine the threshold for Apolipoprotein B (ApoB), Apolipoprotein A1 (ApoA1) and the ratio for the classification of myocardial infarction (MI). We first conduct a literature review and construct prior distributions. We then develop classification rules based on the posterior distribution of the location and scale parameters for these biomarkers. We identify the threshold for ApoB and ApoA1, and the ratio as 0.908 (gram/liter), 1.138 (gram/liter) and 0.808, respectively. We also observe that the threshold for disease classification varies substantially across different age and ethnic groups. Next, we identify the most informative predictor for MI among the three biomarkers. Based on this analysis, ApoA1 appeared to be a stronger predictor than ApoB for MI classification. Given that we have used this data set for illustration only, the results will require further investigation for use in clinical applications. However, the approach developed in this article can be used to determine the threshold of any continuous biomarker for a binary disease classification.     

A new adaptive EWMA control chart using auxiliary information for monitoring the process mean

The adaptive memory-type control charts, including the adaptive exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts, have gained considerable attention because of their excellent speed in providing overall good detection over a range of mean shift sizes. In this paper, we propose a new adaptive EWMA (AEWMA) chart using the auxiliary information for efficiently monitoring the infrequent changes in the process mean. The idea is to first estimate the unknown process mean shift using an auxiliary information based mean estimator, and then adaptively update the smoothing constant of the EWMA chart. Using extensive Monte Carlo simulations, the run length profiles of the AEWMA chart are computed and explored. The AEWMA chart is compared with the existing control charts, including the classical EWMA, CUSUM, synthetic EWMA and synthetic CUSUM charts, in terms of the run length characteristics. It turns out that the AEWMA chart performs uniformly better than these control charts when detecting a range of mean shift sizes. An illustrative example is also presented to demonstrate the working and implementation of the proposed and existing control charts.     

A Predictive Model for Financial Literacy among the Educated Youth in Kerala,India

ABSTRACT

The economic importance of financial literacy among individuals necessitates policy intervention. Estimation of financial literacy is a prerequisite for strategies to improve financial literacy. This paper, using data collected from the educated young adults in Kerala, the most literate state in India, builds a predictive model for financial literacy employing logistic regression. The study reveals the low level of financial literacy in the state. The model points to the significance of gender, age, religion, discipline of study, occupation, and personal income as determinants of financial literacy. The findings have implications for policies aimed at improving the financial literacy of young adults in India.     

External Assets as Predictors of Positive Emotions Among At‐Risk Youth in Malaysia

The present study is among the first to examine external assets as predictors of positive emotions among at‐risk youth. The study aims to examine the associations of external assets with positive emotions, determine external assets as a predictor of positive emotions in phase 1, and see if these predictors were consistently established in phase 2. At first contact, 403 participants from low‐income apartments in the suburbs of Kuala Lumpur, aged 13–25 years were asked to complete the 25 Developmental Assets, Malaysian version. The participants were also invited to participate in social activities organized by the PERMATA community. The same participants were approached four months later to examine the stability of measures. Multiple regression analysis revealed support is the most significant predictor of positive emotions at phase 1 whilst positive peer influence, family boundaries and caring neighborhood are the significant predictors at phase 2. Results suggested that the presence of other external assets can enhance the positive development of at‐risk youth, however, the support must be present to some extent in the first place.     

Disablement, Disability and the Nigerian Society

This paper seeks to examine the question of disability in developing countries, particularly Nigeria. Most of the diseases causing disabilities are preventable. Many of these are infections which could be prevented with medical care.

The perception of handicapping conditions by most Nigerians it is argued, are greatly influenced by myth and superstition, which in turn influences the negative attitude of people towards disabled people.

The lack of medical facilities has contributed to the spread of common diseases which otherwise would have been controlled or eradicated, as is the case in developed countries like Britain and America.

Rights of disabled people are emphasized. This includes the right to an education and the right of access into buildings. Fortunately, there are moves towards the attainment of these basic rights in various sectors, particularly the University of Jos which has the largest concentration of blind students in one single institution of higher learning.     

A new lifetime model with decreasing,increasing, bathtub-shaped,and upside-down bathtub-shaped hazard rate function

A new three-parameter distribution with decreasing, increasing, bathtub-shaped and upside-down bathtub-shaped hazard rate function is proposed. The new distribution encompasses some previously known distributions as special cases. Basic mathematical properties of the new distribution (including the moment-generating function, moments, order statistics properties, Rényi entropy and stress–strength parameter) are derived. Its parameters are estimated by the method of maximum likelihood. An application is illustrated using a real data set.     

STRATEGIC ENFORCEMENT,INTELLECTUAL PROPERTY RIGHTS,AND CONTRACTUAL R&D

This study examines the role of intellectual property rights (IPRs) in contractual research and development (R&D) in developing countries. We find that strong IPRs provide incentives for firms, both multinational and local, to specialize in R&D activities in which they have competitive advantage (the specialization effect). They also facilitate the switching process from imitators to potential innovators for local firms (the switching effect). Moreover, we also demonstrate that a multinational firm's strategic IPRs enforcement behavior can be an effective instrument for subsidizing contractual R&D in developing countries (the subsidizing effect). We further illustrate how a policy mix of IPRs and a foreign direct investment subsidy in these countries affects R&D activities by adding an offshore R&D subsidiary as an additional organizational form. (JEL L13, O31, O34)     

New Economic Policy and the Malaysian multiethnic middle class

Generally the processes of modernisation, industrialisation and urbanisation that took place especially after the National Economic Policy (NEP) was implemented in 1971, had transformed the economic structure and the Malaysian society. This transformation took place during an era of rapid economic growth and prosperity in Malaysia. One of the more important phenomena resulting from this transformation is the emergence, growth and expansion of the multiethnic middle class in the country, but particularly the Malay middle class. The emergence of this multiethnic middle class is significant economically, socially and politically. The growth and expansion of this middle class shows that it is very much a dynamic entity. It also shows that the class has yet to consolidate. This paper briefly traces the emergence and growth of the Malaysian multiethnic middle class, followed by a discussion on the roles they play in effecting changes in the Malaysian society.     

Regime-specific impact of financial reforms on economic growth in Pakistan

This study uses and proposes a new methodological approach to construct a financial liberalization index on the basis of the dynamic factor model technique. The resulting index is used to investigate the impact of the financial sector reforms in Pakistan on economic growth. Using the Markov regime-switching model over the period 1972–2015, the empirical results showed that the examined relationship is nonlinear, nonmonotonic, state-dependent, and better described by the two-state Markov switching model characterized by the high growth regime and low growth regime. Despite the positive impact of financial liberalization on economic growth in both the high and low growth regimes, financial liberalization relatively strongly affects real GDP growth in the high growth regime. The results further demonstrate that transition probabilities establish an inordinate episode of the low growth regime. Furthermore, the high growth regime is relatively short-lived than the low growth regime. Among the other variables, trade openness and physical capital stock have a positive impact on economic growth, while labor force and government expenditure exert a negative effect on economic growth. Several economic policies are proposed and discussed for better functioning of financial sector development in Pakistan.