scholarly journals Two-Sided Generalized Hyperbolic Secant Distribution with Real Data Applications and Model Comparisons

2021 ◽  
Author(s):  
Mustafa Çağatay KORKMAZ ◽  
Christophe CHESNEAU ◽  
Julien MARİE
Keyword(s):  
Real Data ◽  
Model Comparisons ◽  
Generalized Hyperbolic Secant Distribution

Detecting Random Responses in a Personality Scale Using IRT-Based Person-Fit Indices

2019 ◽  
Vol 35 (1) ◽  
pp. 126-136 ◽  
Author(s):  
Tour Liu ◽  
Tian Lan ◽  
Tao Xin
Keyword(s):  
Experimental System ◽  
Real Data ◽  
Fit Indices ◽  
Random Response ◽  
Person Fit ◽  
Index Method ◽  
Single Person ◽  
Person Fit Index ◽  
Random Responses ◽  
Response Behaviors

Abstract. Random response is a very common aberrant response behavior in personality tests and may negatively affect the reliability, validity, or other analytical aspects of psychological assessment. Typically, researchers use a single person-fit index to identify random responses. This study recommends a three-step person-fit analysis procedure. Unlike the typical single person-fit methods, the three-step procedure identifies both global misfit and local misfit individuals using different person-fit indices. This procedure was able to identify more local misfit individuals than single-index method, and a graphical method was used to visualize those particular items in which random response behaviors appear. This method may be useful to researchers in that it will provide them with more information about response behaviors, allowing better evaluation of scale administration and development of more plausible explanations. Real data were used in this study instead of simulation data. In order to create real random responses, an experimental test administration was designed. Four different random response samples were produced using this experimental system.

A Hierarchy of Multinomial Models for Multidimensional Source Monitoring

Methodology ◽  
2005 ◽  
Vol 1 (1) ◽  
pp. 2-17 ◽  
Author(s):  
Thorsten Meiser
Keyword(s):  
Cognitive Processes ◽  
Source Monitoring ◽  
Source Information ◽  
Model Comparisons ◽  
Storage And Retrieval ◽  
Multinomial Processing Tree ◽  
Multinomial Models ◽  
Hierarchical Relationship ◽  
Statistical Framework ◽  
Tree Models

Abstract. Several models have been proposed for the measurement of cognitive processes in source monitoring. They are specified within the statistical framework of multinomial processing tree models and differ in their assumptions on the storage and retrieval of multidimensional source information. In the present article, a hierarchical relationship is demonstrated between multinomial models for crossed source information ( Meiser & Bröder, 2002 ), for partial source memory ( Dodson, Holland, & Shimamura, 1998 ) and for several sources ( Batchelder, Hu, & Riefer, 1994 ). The hierarchical relationship allows model comparisons and facilitates the specification of identifiability conditions. Conditions for global identifiability are discussed, and model comparisons are illustrated by reanalyses and by a new experiment on the storage and retrieval of multidimensional source information.

Exergy and sensibility analysis of each individual effect in a kraft multiple effect evaporator

TAPPI Journal ◽  
2019 ◽  
Vol 18 (10) ◽  
pp. 607-618
Author(s):  
JÉSSICA MOREIRA ◽  
BRUNO LACERDA DE OLIVEIRA CAMPOS ◽  
ESLY FERREIRA DA COSTA JUNIOR ◽  
ANDRÉA OLIVEIRA SOUZA DA COSTA
Keyword(s):  
Optimization Problem ◽  
Real Data ◽  
Kraft Pulping ◽  
Steam Temperature ◽  
Input Flow ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Multiple Effect ◽  
Sensibility Analysis ◽  
Exergetic Analysis

The multiple effect evaporator (MEE) is an energy intensive step in the kraft pulping process. The exergetic analysis can be useful for locating irreversibilities in the process and pointing out which equipment is less efficient, and it could also be the object of optimization studies. In the present work, each evaporator of a real kraft system has been individually described using mass balance and thermodynamics principles (the first and the second laws). Real data from a kraft MEE were collected from a Brazilian plant and were used for the estimation of heat transfer coefficients in a nonlinear optimization problem, as well as for the validation of the model. An exergetic analysis was made for each effect individually, which resulted in effects 1A and 1B being the least efficient, and therefore having the greatest potential for improvement. A sensibility analysis was also performed, showing that steam temperature and liquor input flow rate are sensible parameters.

THE DEVELOPMENT OF THE MATHEMATICAL MODEL OF PREDICTING THE INDICATORS OF ACCREDITATION OF TECHNICAL UNIVERSITIES IN THE RUSSIAN FEDERATION

2017 ◽  
pp. 27-38
Author(s):  
Olga Mikhaylovna Tikhonova ◽  
Alexander Fedorovich Rezchikov ◽  
Vladimir Andreevich Ivashchenko ◽  
Vadim Alekseevich Kushnikov
Keyword(s):  
Mathematical Model ◽  
System Dynamics ◽  
Regression Model ◽  
Oriented Graph ◽  
Real Data ◽  
Educational Process ◽  
Proposed Model ◽  
Linear Differential ◽  
The University ◽  
The Mathematical Model

The paper presents the system of predicting the indicators of accreditation of technical universities based on J. Forrester mechanism of system dynamics. According to analysis of cause-and-effect relationships between selected variables of the system (indicators of accreditation of the university) there was built the oriented graph. The complex of mathematical models developed to control the quality of training engineers in Russian higher educational institutions is based on this graph. The article presents an algorithm for constructing a model using one of the simulated variables as an example. The model is a system of non-linear differential equations, the modelling characteristics of the educational process being determined according to the solution of this system. The proposed algorithm for calculating these indicators is based on the system dynamics model and the regression model. The mathematical model is constructed on the basis of the model of system dynamics, which is further tested for compliance with real data using the regression model. The regression model is built on the available statistical data accumulated during the period of the university's work. The proposed approach is aimed at solving complex problems of managing the educational process in universities. The structure of the proposed model repeats the structure of cause-effect relationships in the system, and also provides the person responsible for managing quality control with the ability to quickly and adequately assess the performance of the system.

Investigation of Timing Anomalies in the Russian Stock Market in the Post-Crisis Period

2019 ◽  
Vol 12 (3) ◽  
pp. 37-47
Author(s):  
I. Ya. Lukasevich
Keyword(s):  
Stock Market ◽  
Information Technologies ◽  
Real Data ◽  
Weak Form ◽  
Fair Value ◽  
Presidential Decree ◽  
Day Of The Week ◽  
Russian Stock Market ◽  
Economic Growth Rates ◽  
Global And Local

The implementation of the May presidential decree aimed at Russia’s joining the top five global economies and achieving economic growth rates above the world’s average while maintaining macroeconomic stability requires a highly developed and efficient stock market ensuring the accumulation of capital and its deployment in the most promising and productive sectors of the economy.The subject of the research is timing anomalies in the Russian stock market in 2012–2018. The relevance of the research is due to the information inefficiency of the Russian stock market and its imperfections leading to significant price deviations from the «fair» value of assets and depriving investors of the opportunity to form various strategies for deriving additional revenues not related to fundamental economic factors and objective processes occurring in the global and local economies and the economy of an individual business entity. Based on the trend analysis of the Broad Market USD Index (RUBMI), the paper demonstrates a methodology for simulating the analysis of price anomalies on large arrays of real data using statistical data processing methods and modern information technologies. The paper concludes that though the Russian stock market lacks even the weak form of efficiency, such well-known timing anomalies as the “day-of-the-week” effect and the “month” effect have not been observed in the recent years. Therefore, investors could not use these anomalies to derive regular revenues above the market average.

Justifying the data analytical choice in single case research in relation to the expected data pattern

2019 ◽  
Author(s):  
Rumen Manolov
Keyword(s):  
Data Analysis ◽  
Visual Analysis ◽  
Multilevel Models ◽  
Single Case ◽  
Analytical Techniques ◽  
Real Data ◽  
Small Scale ◽  
Data User ◽  
Single Case Research ◽  
User Friendly

The lack of consensus regarding the most appropriate analytical techniques for single-case experimental designs data requires justifying the choice of any specific analytical option. The current text mentions some of the arguments, provided by methodologists and statisticians, in favor of several analytical techniques. Additionally, a small-scale literature review is performed in order to explore if and how applied researchers justify the analytical choices that they make. The review suggests that certain practices are not sufficiently explained. In order to improve the reporting regarding the data analytical decisions, it is proposed to choose and justify the data analytical approach prior to gathering the data. As a possible justification for data analysis plan, we propose using as a basis the expected the data pattern (specifically, the expectation about an improving baseline trend and about the immediate or progressive nature of the intervention effect). Although there are multiple alternatives for single-case data analysis, the current text focuses on visual analysis and multilevel models and illustrates an application of these analytical options with real data. User-friendly software is also developed.

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