Cash Flow Forecasting Using Probabilistic Neural Networks,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
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,
2020
Purdue University
Prerequisite Course Recommendation Based On Course Description And Students’ Grades, Haozhe Zhou
The Journal of Purdue Undergraduate Research
No abstract provided.
