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Cash Flow Forecasting Using Probabilistic Neural Networks, Marwan Ashour 2020 University of Baghdad - Iraq

Cash Flow Forecasting Using Probabilistic Neural Networks, Marwan Ashour

Journal of the Arab American University مجلة الجامعة العربية الامريكية للبحوث

This paper aimed to compare the modern methods of cash flow forecasting with the traditional ones. In other words, the researcher compared between the Probabilistic Neural Networks and Transfer Function. It is worth mentioning that cash flow forecasting , nowadays, is very important and helps the upper management plan, control, assess the performance and make decisions. More specifically, in this paper, the Artificial Neural networks were used to diagnose the nature of the cash flow for the next period of time and then forecast the cash flow. The experiment was conducted in The General company for Electricity Distribution in Baghdad. …


Interval Estimation Of Proportion Of Second-Level Variance In Multi-Level Modeling, Steven Svoboda 2020 University of Nebraska-Lincoln

Interval Estimation Of Proportion Of Second-Level Variance In Multi-Level Modeling, Steven Svoboda

The Nebraska Educator: A Student-Led Journal

Physical, behavioral and psychological research questions often relate to hierarchical data systems. Examples of hierarchical data systems include repeated measures of students nested within classrooms, nested within schools and employees nested within supervisors, nested within organizations. Applied researchers studying hierarchical data structures should have an estimate of the intraclass correlation coefficient (ICC) for every nested level in their analyses because ignoring even relatively small amounts of interdependence is known to inflate Type I error rate in single-level models. Traditionally, researchers rely upon the ICC as a point estimate of the amount of interdependency in their data. Recent methods utilizing an …


Robustness Of The Ewma Sampling Plan To Non-Normality, Uttama Mishra, S. Siddiqui, J. R. Singh 2020 Vikram University, Ujjain, India

Robustness Of The Ewma Sampling Plan To Non-Normality, Uttama Mishra, S. Siddiqui, J. R. Singh

Journal of Modern Applied Statistical Methods

The effect of non-normality on the OC function of the sampling plan under EWMA is studied by deriving the OC function for a non-normal population represented by the first four terms of an Edgeworth series.


Misguided Opposition To Multiplicity Adjustment Remains A Problem, Andrew V. Frane 2020 University of California, Los Angeles

Misguided Opposition To Multiplicity Adjustment Remains A Problem, Andrew V. Frane

Journal of Modern Applied Statistical Methods

Fallacious arguments against multiplicity adjustment have been cited with increasing frequency to defend unadjusted tests. These arguments and their enduring impact are discussed in this paper.


Economic Design Of X̅ Control Chart Under Double Ewma, Manzoor A. Khanday, J. R. Singh 2020 Vikram University Ujjain

Economic Design Of X̅ Control Chart Under Double Ewma, Manzoor A. Khanday, J. R. Singh

Journal of Modern Applied Statistical Methods

Designing of parameters plays an important role in economic design of control charts for lowering the cost and time. Manipulating sample size (n) and sampling interval (h), the effect of double exponentially weighted moving average (DEWMA) model was studied for the Economic Design (ED) of X̅ control chart. Optimum sizes and level were obtained when the characteristics of an item possesses DEWMA model. When shifts are uncertain the optimal design for DEWMA chart should be more conservative and should be implemented for benefiting the consumers as well as producers.


An Investigation Of Chi-Square And Entropy Based Methods Of Item-Fit Using Item Level Contamination In Item Response Theory, William R. Dardick, Brandi A. Weiss 2020 The George Washington University

An Investigation Of Chi-Square And Entropy Based Methods Of Item-Fit Using Item Level Contamination In Item Response Theory, William R. Dardick, Brandi A. Weiss

Journal of Modern Applied Statistical Methods

New variants of entropy as measures of item-fit in item response theory are investigated. Monte Carlo simulation(s) examine aberrant conditions of item-level misfit to evaluate relative (compare EMRj, X2, G2, S-X2, and PV-Q1) and absolute (Type I error and empirical power) performance. EMRj has utility in discovering misfit.


A Monte Carlo Analysis Of Ordinary Least Squares Versus Equal Weights, James Brewer Ayres 2020 Western Kentucky University

A Monte Carlo Analysis Of Ordinary Least Squares Versus Equal Weights, James Brewer Ayres

Masters Theses & Specialist Projects

Equal weights are an alternative weighting procedure to the optimal weights offered by ordinary least squares regression analysis. Also called units weights, equal weights are formed by standardizing scores on the predictor variables and averaging these standardized scores to create a composite score. Research is limited regarding the conditions under which equal weights result in cross-validated 𝑅𝑅2 values that meet or exceed optimal weights. In this study, I explored the effect of various predictor-criterion correlations, predictor intercorrelations, and sample sizes to determine the relative performance of equal and optimal weighting schemes upon cross-validation. Results indicated that optimally weighted predictors explained …


Logistic Regression Under Sparse Data Conditions, David A. Walker, Thomas J. Smith 2020 Northern Illinois University

Logistic Regression Under Sparse Data Conditions, David A. Walker, Thomas J. Smith

Journal of Modern Applied Statistical Methods

The impact of sparse data conditions was examined among one or more predictor variables in logistic regression and assessed the effectiveness of the Firth (1993) procedure in reducing potential parameter estimation bias. Results indicated sparseness in binary predictors introduces bias that is substantial with small sample sizes, and the Firth procedure can effectively correct this bias.


Estimating A Multilevel Model With Complex Survey Data: Demonstration Using Timss, Julie Lorah 2020 Indiana University Bloomington

Estimating A Multilevel Model With Complex Survey Data: Demonstration Using Timss, Julie Lorah

Journal of Modern Applied Statistical Methods

Analysis of complex survey data is demonstrated for the multilevel model. Description of specific aspects of analysis, including plausible values, sampling weights, and replicate weights is provided. Following this, example TIMSS data and models are described and results are presented.


Concomitant Of Order Statistics From New Bivariate Gompertz Distribution, Sumit Kumar, M. J. S. Khan, Surinder Kumar 2020 Babasaheb Bhimrao Ambedkar University

Concomitant Of Order Statistics From New Bivariate Gompertz Distribution, Sumit Kumar, M. J. S. Khan, Surinder Kumar

Journal of Modern Applied Statistical Methods

For the new bivariate Gompertz distribution, the expression for probability density function (pdf) of rth order statistics and pdf of concomitant arising from rth order statistics are derived. The properties of concomitant arising from the corresponding order statistics are used to derive these results. The exact expression for moment generating function (mgf) of concomitant of order rth statistics is derived. Also, the mean of concomitant arising from rth order statistics is computed using the mgf of concomitant of rth order statistics, and the exact expression for joint density of concomitant of two non-adjacent order statistics …


Time Series Analysis Of Offshore Buoy Light Detection And Ranging (Lidar) Windspeed Data, Aditya Garapati, Charles J. Henderson, Carl Walenciak, Brian T. Waite 2020 Southern Methodist University

Time Series Analysis Of Offshore Buoy Light Detection And Ranging (Lidar) Windspeed Data, Aditya Garapati, Charles J. Henderson, Carl Walenciak, Brian T. Waite

SMU Data Science Review

In this paper, modeling techniques for the forecasting of wind speed using historical values observed by Light Detection and Ranging (LIDAR) sensors in an offshore context are described. Both univariate time series and multivariate time series modeling techniques leveraging meteorological data collected simultaneously with the LIDAR data are evaluated for potential contributions to predictive ability. Accurate and timely ability to predict wind values is essential to the effective integration of wind power into existing power grid systems. It allows for both the management of rapid ramp-up / down of base production capacity due to highly variable wind power inputs and …


The Effect Of Corporate Governance Mechanisms And Their Interactions On Earnings Quality, Nasrin Azar 2020 Universiti Malaya

The Effect Of Corporate Governance Mechanisms And Their Interactions On Earnings Quality, Nasrin Azar

Student Works (2020-2029)

Corporate governance (CG) mechanisms play an essential role in improving financial reporting quality, especially earnings quality. Due to corporate failures around the world, there has been a renewed interest in the effect of CG on earnings quality. The primary objectives of this thesis are to (1) investigate the impact of CG characteristics on earnings quality, and (2) examine whether the interactions between CG mechanisms influence earnings quality. Based on the agency and resource dependence theories, this study develops and examines ten main hypotheses (23 sub-hypotheses) to achieve these objectives. This study identifies CG mechanisms such as the board of directors, …


Simple Unequal Allocation Procedure For Ranked Set Sampling With Skew Distributions, Dinesh Bhoj, Girish Chandra 2020 Rutgers University

Simple Unequal Allocation Procedure For Ranked Set Sampling With Skew Distributions, Dinesh Bhoj, Girish Chandra

Journal of Modern Applied Statistical Methods

A practical unbalanced Ranked Set Sampling (RSS) model is proposed to estimate the population mean of positively skewed distributions. The gains in the relative precisions of the population mean based on the proposed model for chosen distributions are uniformly higher than those based on balanced RSS and the t-model proposed in Kaur et al. (1997). The relative precisions of the simple unequal allocation model are, with one exception, better than (s, t)-model which is better than t-model. The relative precision of the proposed model is very close or equal to the optimal Neyman allocation model.


A Primer On Statistical Inferences For Finite Populations, Thomas R. Knapp 2020 University of Rochester

A Primer On Statistical Inferences For Finite Populations, Thomas R. Knapp

Journal of Modern Applied Statistical Methods

This primer is intended to provide the basic information for sampling without replacement from finite populations.


Almost All Missing Data Are Mnar, Thomas R. Knapp 2020 University of Rochester

Almost All Missing Data Are Mnar, Thomas R. Knapp

Journal of Modern Applied Statistical Methods

Rubin (1976, and elsewhere) claimed that there are three kinds of “missingness”: missing completely at random; missing at random; and missing not at random. He gave examples of each. The article that now follows takes an opposing view by arguing that almost all missing data are missing not at random.


Jmasm 54: A Comparison Of Four Different Estimation Approaches For Prognostic Survival Oral Cancer Model, Wan Muhamad Amir, Muhammad Azeem, Masitah Hayati Harun, Zalila Ali, Mohamad Shafiq 2020 Universiti Sains Malaysia

Jmasm 54: A Comparison Of Four Different Estimation Approaches For Prognostic Survival Oral Cancer Model, Wan Muhamad Amir, Muhammad Azeem, Masitah Hayati Harun, Zalila Ali, Mohamad Shafiq

Journal of Modern Applied Statistical Methods

Four types of estimation approaches for prognostic survival oral cancer model building are considered via a SAS algorithm: Efron’s Method, Exact Method, Breslow’s Method, and Discrete Method. Each method is illustrated separately and compared according to their coefficient parameter. An approach is considered by adding a bootstrapping technique for each handling ties method and a complete SAS algorithm is supplied for each proposed method, including methods for handling ties.


Student Preclass Preparation By Both Reading The Textbook And Watching Videos Online Improves Exam Performance In A Partially Flipped Course, Kaleb Bassett, Gayla R. Olbricht, Katie Shannon 2020 Missouri University of Science and Technology

Student Preclass Preparation By Both Reading The Textbook And Watching Videos Online Improves Exam Performance In A Partially Flipped Course, Kaleb Bassett, Gayla R. Olbricht, Katie Shannon

Mathematics and Statistics Faculty Research & Creative Works

The flipped classroom has the potential to improve student performance. Because flipping involves both preclass preparation and problem solving in the classroom, the means by which increased learning occurs and whether the method of delivering content matters is of interest. In a partially flipped cell biology course, students were assigned online videos before the flipped class and textbook reading before lectures. Low-stakes assessments were used to incentivize both types of preclass preparation. We hypothesized that more students would watch the videos than read the textbook and that both types of preparation would positively affect exam performance. A multiple linear regression …


Integrating Affect Perception Tasks From The New York Emotion Battery Into A Comprehensive Measure Of Neuropsychological Change Across The Lifespan, Melinda A. Cornwell 2020 CUNY Graduate Center

Integrating Affect Perception Tasks From The New York Emotion Battery Into A Comprehensive Measure Of Neuropsychological Change Across The Lifespan, Melinda A. Cornwell

Dissertations, Theses, and Capstone Projects

Background: The ability to perceive others’ emotions is a vital skill for social competency, impacting the success of personal and professional relationships (Brinton & Fujiki, 2011; Cassidy et al., 1992; Côté & Miners, 2006). According to Socioemotional Selectivity Theory (SST; Carstensen, 1991), human motivation develops to become more discerning in choosing milieus that yield the most gratifying return on the investment of personal resources (e.g., time, attention, and effort), perhaps explaining why some research findings indicate that older adults may demonstrate an affect perception (AP) bias described as a positivity effect (Reed et al., 2014). Moreover, AP predicts cognitive and …


Role Of Influence In Complex Networks, Nur Dean 2020 CUNY Graduate Center

Role Of Influence In Complex Networks, Nur Dean

Dissertations, Theses, and Capstone Projects

Game theory is a wide ranging research area; that has attracted researchers from various fields. Scientists have been using game theory to understand the evolution of cooperation in complex networks. However, there is limited research that considers the structure and connectivity patterns in networks, which create heterogeneity among nodes. For example, due to the complex ways most networks are formed, it is common to have some highly “social” nodes, while others are highly isolated. This heterogeneity is measured through metrics referred to as “centrality” of nodes. Thus, the more “social” nodes tend to also have higher centrality.

In this thesis, …


Prerequisite Course Recommendation Based On Course Description And Students’ Grades, Haozhe Zhou 2020 Purdue University

Prerequisite Course Recommendation Based On Course Description And Students’ Grades, Haozhe Zhou

The Journal of Purdue Undergraduate Research

No abstract provided.


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