Taxicab non-symmetrical correspondence analysis

EnNon Symmetrical correspondence analysis (NSCA) is a variant of the classical Correspondence Analysis (CA) for analyze two-way contingency table with a structure of dependence between two variables. In order to overcome the influence due to the presence of outlier, in this paper, it is presented Taxicab Non Symmetrical Correspondence Analysis (TNSCA), based on the taxicab singular value decomposition. It will show that TNSCA it is more robust than the ordinary NSCA, because it gives uniform weights to all the points. The visual map constructed by TNSCA offers a clearer perspective than the map obtained by correspondence analysis. Examples are provided

On Fuzzy Regression Adapting Partial Least Squares

Partial Least Squared (PLS) regression is a model linking a dependent variable y to a set of X (numerical or categorical) explanatory variables. It can be obtained as a series of simple and multiple regressions of simple and multiple regressions. PLS is an alternative to classical regression model when there are many variables or the variables are correlated. On the other hand, an alternative method to regression in order to model data has been studied is called Fuzzy Linear Regression (FLR). FLR is one of the modelling techniques based on fuzzy set theory. It is applied to many diversified areas such as engineering, biology, finance and so on. Development of FLR follows mainly two paths. One of which depends on improving the parameter estimation methods. This enables to compute more reliable and more accurate parameter estimation in fuzzy setting. Second of which is related to applying these methods to data, which usually do not follow strict assumptions. The application point of view of FLR has not been examined widely except outlier case. For example, it has not been widely examined how FLR behaves under the multivariate case. To overcome such a problem in classic setting, one of the methods that are practically useful is PLS. In this paper, FLR is examined based on application point of view when it has several explanatory variables by adapting PLS

Full range autoregressive time series models

EnA new family of time series models, called the Full Range Autoregressive model, is introduced which avoids the difficult problem of order determination in time series analysis. Some of the basic statistical properties of the new model are studied

Renewable energy, institutional stability, environment and economic growth nexus of D-8 countries

The anthropogenic impact of conventional energy sources encourages the utilization of renewable energy, as it has become a strategic commodity for economic growth. On the other hand, institutional stability is the pre-requisite without which environmental quality cannot be assured and the economy cannot function. However, in recent literature, very little consideration has been given to this important phenomenon. This study is set to analyze the energy-institutional stability-economic growth nexus, as well as the energy-institutional stability-environmental quality nexus, by incorporating the Cobb Douglas production function and the Diet and Rosa environmental function respectively. The sample consists of the D-8 countries and the time period spans 1990 to 2016. To analyze the developed models, Autoregressive Distributive Lag (ARDL), Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) tests are applied, along with other econometric techniques. The panel ARDL statistics indicate significant cointegration among all variables of both functions, while the FMOLS test reveals that consumption of both nonrenewable and renewable energy has a positive impact on economic growth, as well as on environmental degradation. Further, results indicate that institutional stability is crucial for establishing a nation on a sound footing and protecting environmental quality. Based on these results, the study suggests a blend of both types of energy and a gradual transition toward renewable energy sources, with better implementation of policies and technological advances, to produce, preserve, and transmit renewable energy production

TRANS-ADRIATIC PIPELINE PROJECT AND ITS POTENTIAL EFFECTS ON ALBANIA

The aim of this paper is to explain the exploration and the production of natural gas in Albania, which has an important impact on the country's economy. The development of the natural gas sector in Albania is one of the priorities set out inthe National Strategy of Energy. The research on this paper is based on regulatory authority of the energy sector and on our actual data and survey made on Albanian citizens according to socio-economic judgments about the Trans-Adriatic pipeline project (TAP).In the first part of this paper, it will be explained that the development of natural gas production process in Albania. The natural gas production in Albania started in 1968 at Divjaka gas field with an annual domestic production of 70 million Nm3.Up to 1990 this resource was used to furnish different industries as the fertilizer industry, the oil industry, electricity industry and residential sector. Actually it serves only for the oil industry.As Albania is the only country in Europe which is not connected to the international gas network, in the second part of this paper, It will be explained how Albania iscreating a network to international gas supply. Emphasis will be on the TAP projectand the Albanian citizens' perceptions on socio-economic reasoning about this project. TAP is an important project because it will link Albania with other Balkan,European and Asian countries and our analyses will be on Albanian people's perceptions about this project. Collected data analyzed by SPSS package programme

A New Model to Identify the Reliability and Trust of Internet Banking Users Using Fuzzy Theory and Data-Mining

As a result of changes in approach from traditional to virtual banking system, security in data exchange has become more important; thus, it seems essentially necessary to present a pattern based on smart models in order to reduce fraud in this field. A new algorithm has been provided in this article to improve security and to specify the limits of giving special services to Internet banking users in order to pave appropriate ground for virtual banking. In addition to identifying behavioral models of customers, this algorithm compares the behaviors of any customer with this model and finally computes the rate of trust in customer’s behavior. The hybrid data-mining and knowledge based structure has been adapted in this algorithm according to fuzzy systems. In this research, qualitative data was gathered from interviews with banking experts, analyzed by Expert Choice to identify the most important variables of customer behavior analysis, and to analyze customer behavior and customer bank Internet transaction data for a period of one year by MATLAB and Clementine. The results of this survey indicate that the potential of the given structure to recognize the rate of trust in Internet bank user’s behavior might be at reasonable level for experts in this area

Calendar anomalies in Pakistan stock market

Anomalies are those irregularities that cannot be defined by the standard finance theories. In this paper, we examined the existence of an intra-month effect and weekend effect in stock returns of Pakistan stock exchange. Data has been gathered from KSE-100 index which is largest and most liquid stock market in Pakistan. Daily stock index data has been gathered from November 2, 1991, through December 31, 2014, which approximates to about 23 years data. Returns on this data were calculated and calendar anomalies were examined. Our results show that there exists an intra-month effect. Similarly, the existence of the weekend effect in the stock market is also observed. Hence, Karachi stock market shows anomalous behavior in the returns

How do students evaluate instructors’ performance? implication of teaching abilities, physical attractiveness and psychological factors

One instrument regularly seen as a basic resource in assessing pedagogical knowledge and vivid learning in different circumstances is through the method of conducting student assessment appraisal of their instructors. Nevertheless, deciding the nature of instructional abilities requires as rationale an unbiased judgment. The concern is that there are no formal techniques or formulas that would prompt accurate responses from the students. In spite of the contention surrounding students’ rating on instructors, this study aims to investigate how university students in Malaysia would evaluate instructors based on non-instructional factors, such as physical attractiveness and psychological factors, which in turn may affect students’ perceptions towards instructors’ performance. PLS-SEM was appropriated to perform the path modelling analysis. Practical implication is discussed