Predictive Modeling Using Statistical programs

Logistic regression analysis of factors contributing to bank deposit subscription and direct marketing success.

View project at:

https://github.com/JackKRasmus-Vorrath/Logistic_Regression_Direct-Marketing_Bank-Term-Deposit-Subscription

You yourself, or what is the same, your experience is such ``coin'' that, while you aren't questioned, it rotates all the time in ``free flight''. And only when you answer the question the ``coin'' falls on one of the sides: ``Yes'' or ``No'' with the believability that your experience tells you.

Mathematics plays a critical role in many modeling and simulation applications, and whenever detailed representations of combat phenomenon are required (e.g., attrition, detection, etc.). The required mathematics can seem daunting, but a wealth of problems relevant to the M&S community can be addressed with efficient numerical algorithms and heuristics. We shall present a small sampling of these methods and relevant examples of their usage. Examples include combat attrition, target engagement, detection, and missile defense. Most of these can be implemented with a spreadsheet for demonstration.

Modul ini adalah pedoman atau panduan dalam Proses Belajar dan Mengajar yang merupakan penunjang Praktikum mata Kuliah Probabilitas dan Statistika menggunakan Microsoft Excel dan R-Software, bagi mahasiswa Sekolah Tinggi Manajemen & Informatika (STMIK) Sumedang. Modul ini diharapkan dapat membantu mahasiswa dalam mempersiapkan dan mengikuti proses belajar dan mengajar dengan baik, terarah dan terencana.

Forecasting economic growth for developing countries is a problematic task, peculiarly because of particularities they face. The model identification process in this paper yielded a random walk model for the Gross Domestic Product (GDP) series. We applied ARIMA models to get empirical results and bring to a close that the models obtained are suitable for forecasting the economic output of Africa. The adequate models were used for each of 20 Africa's largest economies to forecast future time series values. Based on the estimation results, we concluded that from 1990 looking forward to 2030, there will be an increasing GDP growth where the average speed of the economy of Africa will be of 5.52%, and the GDP could achieve $2185.21 billion to $10186.18 billion.

Assessment of convergent validity of latent variables is one of the steps in conducting structural equation modeling via partial least squares (PLS-SEM). In this paper, we illustrate such an assessment using a loadings-driven approach. The analysis employs WarpPLS, a leading PLS-SEM software tool.

The road pavement network is a major component of a country’s transport and communications infrastructure.  A key input to the management of the road pavement network is its condition.  Over the last 50 years, high speed, network level devices have been developed that routinely monitor pavement condition in a more objective, repeatable, reproducible and cost - effective manner.  Typical of the condition parameters monitored in this fashion are roughness, rutting, macro texture and visually assessed pavement surface items via imaging systems.

Pavement structural capacity is an important condition measure of the load carrying ability of the subgrade and pavement in combination.  In practice, structural capacity has been monitored at the specific project rather than network level, chiefly because of the high cost of using low speed monitoring processes. Given the cost of acquiring structural capacity data, other pavement condition parameters, readily collected at the network level using high-speed devices, are used to identify possible project level areas of investigation.  The subsequent project level investigation may result in the use structural capacity testing devices.

Pavement transverse profile shape is commonly monitoring at both the project and network levels and reported as rutting.  Whilst the transverse profile shape is monitored, the collected data is reduced to a level comparable to the manually collected 1.2 or 2 metre straight edge or the 3 point rut index.  The author suggests that the exchange of knowledge and the possibilities available with this more sophisticated measuring process have not been fully explored.  Rather, a ‘number of standards’ have been established over time and the data collection advances made, have aided in delivering these ‘standards’ in a faster, repeatable, cheaper and safer manner, but not aided in providing an improved insight to pavement behaviour and especially structural capacity.

There is a body of qualitative evidence to indicate a relationship between pavement transverse profile shape and structural capacity.  The literature review undertaken suggested that pavement distress affects the shape of the transverse profile, it is also recognised that pavement distress affects structural capacity.  The literature suggested that modelling the pavement transverse profile shape could provide a better insight to pavement structural capacity and overall performance, than what is currently achieved by simply reporting rutting.

Eventology of multivariate statistics
Eventology and mathematical eventology
Philosophical eventology and philosophy of probability
Practical eventology
Eventology of safety
Eventological economics and psychology
Mathematics in the humanities, socio-economic and natural sciences
Financial and actuarial mathematics
Multivariate statistical analysis
Multivariate complex analysis
Decision-making under risk and uncertainty
Risk measurement and risk models
Theory of fuzzy events and generalized theory of uncertainty
System analysis and events management

EEC'2016 ~ workshop on axiomatizing experience and chance, and Hilbert's sixth problem

With topics from quantum physics, probability and believability to economics, sociology and psychology, the workshop will be intended for an interdisciplinary discussion on mathematical theories of experience and chance. Topics of discussion include the results, thoughts and ideas on axiomatization of the eventological theory of experience and chance in the framework of the decision of Hilbert sixth problem.
Eventology of experience and chance
Beleivability theory and statistics of experience
Probability theory and statistics of chance
Axiomatizing experience and chance

It has been suggested, by Michael Bishop, that empirical evidence on human reasoning poses a threat to the internalist account of epistemic responsibility, which he takes to associate being epistemically responsible with coherence, evidence-fitting and reasons-responsiveness. Bishop claims that the empirical data challenges the importance of meeting these criteria by emphasising how it is possible to obtain true beliefs by diverging from them. He suggests that the internalist conception of responsibility should be replaced by one that properly reflects how we can reliably obtain true beliefs. In this paper I defend the internalist account by arguing that Bishop has misinterpreted the relevance of the empirical evidence to the philosophical theory. I argue that the empirical data actually provides support for the idea that, if we want to obtain true beliefs by being responsible, we should aim to meet the criteria that internalists associate with epistemic responsibility.

Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascapetopography was quantified from high resolution bathymetry at five spatial scales (5–300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt).

The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided ‘outstanding’ model predictions (AUC =.0.9) for three of five fish species. MaxEnt provided ‘outstanding’ model predictions for two of five species, with the remaining three models considered ‘excellent’ (AUC = 0.8–0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation prioritization in marine protected area design, zoning in marine spatial planning, and ecosystem-based fisheries management

"USING PREDICTIVE MODELLING METHODS AS A WAY OF EXAMINING PAST SETTLEMENT PATTERNS:AN EXAMPLE FROM SOUTHERN POLAND, Anna Łuczak
Undoubtedly, spatial analysis using GIS applications has become increasingly important in archaeological research. Archaeological Predictive Modelling (APM) plays a crucial role among those GIS techniques. The main goal of APM is to create predictive distribution maps of occurrence of archaeological sites on the basis of known archaeological records and their link to environmental or cultural predictors used in modelling. This gives to CRM (Cultural Resource Management) a real opportunity to protect archaeological remains and to prevent them from damage. That is the main concept of North American predictive modelling approaches. On the other hand, developing Archaeological Sensitivity Maps also helps scientists to plan for field surveys. The use of predictive modelling has a different methodological approach in Europe, where it is an attempt to understand settlement patterns and factors that may have influenced site location in the past. The aim of this presentation is to show how valuable a combination of the two mentioned concepts of predictive modelling (North Americans and European) can be to simulate and visualize prediction maps. This is why I chose for this project an area in southern Poland that lies between two river basins: the ones of the Oława and the Ślęza. The examined area is morphometrically quite diversified – from the flat area in the North and close to river valleys, to the hilly area in the central and eastern part. These features of the selected territory suit the predictive modelling method well and give an opportunity to study complex environmental factors that may have influenced past settlement. The archaeological dataset used in modelling comes from the field survey record stored in the database of the Polish Archaeological Record (PAR /Polish name: Archeologiczne Zdjęcie Polski, AZP). For modelling purposes I selected two datasets representing sites from different periods: Neolithic and Medieval (Early and Late). This approach allows to minimize the modelling and analysing effort and also to examine the differences between settlement patterns in these periods. In the preliminary process a variety of environmental and cultural factors obtained using typical GIS procedures were used to determine past settlement preferences. Variables were examined to identify their potential influence on site location. Statistical analysis (e.g. density plots, correlation coefficients, etc.) was used for this purpose. The best subset of factors was selected and included in different types of statistical modelling procedures. After comparing the accuracy of the models, the best modelling method (with stronger predictive power) was chosen. As a result of the analysis the predictive distribution maps of archaeological sites were obtained."

Coral reef ecosystems are topographically complex environments and this structural heterogeneity influences the distribution, abundance and behavior of marine organisms. Airborne hydrographic lidar (Light Detection and Ranging) provides high resolution digital bathymetry from which topographic complexity can be quantified at multiple spatial scales. To assess the utility of lidar data as a predictor of fish and coral diversity and abundance, seven different morphometrics were applied to a 4 m resolution bathymetry grid and then quantified at multiple spatial scales (i.e., 15, 25, 50, 100, 200 and 300 m radii) using a circular moving window analysis. Predictive models for nineteen fish metrics and two coral metrics were developed using the new statistical learning technique of stochastic gradient boosting applied to regression trees. Predictive models explained 72% of the variance in herbivore biomass, 68% of parrotfish biomass, 65% of coral species richness and 64% of fish species richness. Slope of the slope (a measure of the magnitude of slope change) at relatively local spatial scales (15-100 m radii) emerged as the single best predictor. Herbivorous fish responded to topographic complexity at spatial scales of 15 and 25 m radii, whereas broader spatial scales of between 25 and 300 m radii were relevant for piscivorous fish. This study demonstrates great utility for lidar-derived bathymetry in the future development of benthic habitat maps and faunal distribution maps to support ecosystem-based management and marine spatial planning.

Marine spatial planning and ecosystem-based approaches to marine environmental management require spatially and temporally explicit information describing the distributions of key marine organisms and their linkages with the environment at relatively broad scales (10-100 km2 and intra- and inter-annual patterns).  Even for data rich areas like the Gulf of Maine (Northeast Atlantic) much of the biological survey data is patchy at the scales relevant to resource management decision making.  We addressed this problem for the Stellwagen Bank National Marine Sanctuary (SBNMS) and southern Gulf of Maine region by developing a spatial eco-informatics approach for modeling cetacean-environment relationships.  This approach coupled biological survey data with in situ oceanographic measurements and satellite remote sensing data using a suite of Geographical Information System (GIS) tools and machine learning algorithms for predictive modeling (CART and MARS).  Interpolations of cetacean distributions were mapped for seven cetacean species including the endangered North Atlantic Right Whale.  Predictive models were developed to examine ecological relationships between cetacean distributions and their environment using 29 spatially continuous environmental variables including geographic setting, prey distributions, sea surface conditions, bathymetric features, water depth and water stratification.  This project was undertaken as part of a broader ecological characterization of the Gulf of Maine, and the results have contributed to several management strategies including: (1) the SBNMS management review process, (2) assessing threats to cetaceans from a proposed liquified natural gas installation, and (3) identification of important marine areas to support implementation of the 2008 Massachusetts Ocean Act.

In recent years, various academic studies have proposed crime forecasting models based on the concept of repeat victimization. Some of them have been modelled from the area of differential equations and others from the perspective of spatio-temporal statistics, within the framework of point processes. These models have tended towards a certain sophistication in their formulation, which at times impedes understanding of the predictive mechanism and how it adapts to different realities. Predictive models that function well in one environment or society do not appear to do so in others. In this article, the possibility of crime forecasting for burglaries with forced entry in Catalonia is studied from the perspective of near repeat victimization on a larger territorial scale than is usual. To this effect, the explicative and predictive possibilities of this criminological theory are explored and a predictive system that does not require mathematical or statistical models is proposed. We...

This paper introduces GIS-based statistical methods for the study of settlement patterning in an archaeological context. The main aspect is an improvement over suboptimal stepwise statistical model selection procedures, with the introduction of a Deletion/Substitution/Addition (DSA) algorithm, a systematic model selection algorithm that provides an optimal model choice. The paper also introduces the combined use of Receiving Operator Characteristic (ROC) curves, and variable ranking as key tools aimed at an understanding of settlement patterning causation. An illustrative case study is provided whereby both a purely environmental and a mixed environmental/historical model (based on settlement hierarchy considerations) are investigated.► GIS-based statistical methodological approach to the study of archaeological settlement patterning. ► Deletion/Substitution/Addition (DSA) selection algorithm provides an optimal archaeological model choice. ► Combined use of Receiving Operator Characteristic (ROC) curves, and variable ranking facilitate understanding of settlement patterning causation.

This study employs existing data sources to develop a new measure of intensive care unit (ICU) admission risk for heart failure patients. Outcome measures were constructed from laboratory, accounting, and medical record data for 973 adult inpatients with primary or secondary heart failure. Several scoring interpretations of the laboratory indicators were evaluated relative to their measurement and predictive properties. Cases were restricted to tests within first lab draw that included at least 15 indicators. After optimizing the original clinical observations, a satisfactory heart failure severity scale was calibrated on a 0-1000 continuum. Patients with unadjusted CHF severity measures of 550 or less were 2.7 times more likely to be admitted to the ICU than those with higher measures. A nomogram facilitates routine clinical application. Existing computerized data systems could be programmed to automatically structure clinical laboratory reports using the results of studies like this one to reduce data volume with no loss of information, make laboratory results more meaningful to clinical end users, improve the quality of care, reduce errors and unneeded tests, prevent unnecessary ICU admissions, lower costs, and improve patient satisfaction. Existing data typically examined piecemeal form a coherent scale measuring heart failure severity sensitive to increased likelihood of ICU admission. Marked improvements in ROC curves were found for the aggregate measures relative to individual clinical indicators.

There is a significant body of evidence to at least, on a qualitative level, demonstrate a relationship between pavement rutting and structural capacity. Further investigation of this relationship could lead to a better characterisation of pavement rutting, and a more efficient method of estimating structural capacity, especially at the network level. The objective of the research program was to investigate the relationship between pavement structural capacity and transverse profile shape and where suitable develop structural capacity prediction models. Five broad flexible pavement types, pertinent to this research program were adopted, comprising one unbound and four differing bound flexible pavements. This research program provided an opportunity to 'stand-back' from the day-today measurement of pavement condition and to reflect on the 'big picture'. It is the authors' belief that, if this research program has been able to provide a refocusing of the underlying issues and assumptions behind rut measurement and elevated the debate to quantification of transverse profile shape and its relationship with structural capacity, then it has served its purpose.

Leafy greens, including spinach, have potential for human norovirus transmission through improper handling and/or contact with contaminated water. Inactivation of norovirus prior to consumption is essential to protect public health. Because of the inability to propagate human noroviruses in vitro, murine norovirus (MNV-1) and feline calicivirus (FCV-F9) have been used as surrogates to model human norovirus behavior under laboratory conditions. The objectives of this study were to determine thermal inactivation kinetics of MNV-1 and FCV-F9 in spinach, compare first-order and Weibull models, and measure the uncertainty associated with the process. D-values were determined for viruses at 50, 56, 60, 65, and 72°C in 2-ml vials. The D-values calculated from the first-order model (50 to 72°C) ranged from 0.16 to 14.57 min for MNV-1 and 0.15 to 17.39 min for FCV-9. Using the Weibull model, the tD for MNV-1 and FCV-F9 to destroy 1 log (D = 1) at the same temperatures ranged from 0.22 to 15....

This study assessed the construct validity of the Hiring Agent Survey regarding Selection of Qualified Autistic Candidates (HASSQAC) through factor and reliability analysis. Empirical evidence demonstrated the HASSQAC effectively measures Ajzen’s theory of planned behavior regarding beliefs influencing hiring selection of autistics.KMO = .831demonstrated factor analysis sample adequacy (n = 212). The Bartlett test for sphericity was significant (p < .001). The first four factors explained 57% of the variance. A principal factor analysis with a forced 3 factor extraction using varimax orthogonal rotation constructed a clear conceptual picture of the relationships between items (factor loadings > .40). The 3 factors explained over 50% of the variance among the 45 items. Reliability analysis demonstrated significant Cronbach’s alpha (control = .923; normative = .846; behavioral = .901). Analysis of the 45-item scale demonstrated all but four factors were convergent with prior fin...

This study assessed the construct validity of the Hiring Agent Survey regarding Selection of Qualified Autistic Candidates (HASSQAC) through factor and reliability analysis. Empirical evidence demonstrated the HASSQAC effectively measures Ajzen’s theory of planned behavior regarding beliefs influencing hiring selection of autistics.KMO = .831demonstrated factor analysis sample adequacy (n = 212). The Bartlett test for sphericity was significant (p < .001). The first four factors explained 57% of the variance. A principal factor analysis with a forced 3 factor extraction using varimax orthogonal rotation constructed a clear conceptual picture of the relationships between items (factor loadings > .40). The 3 factors explained over 50% of the variance among the 45 items. Reliability analysis demonstrated significant Cronbach’s alpha (control = .923; normative = .846; behavioral = .901). Analysis of the 45-item scale demonstrated all but four factors were convergent with prior findings.

This paper introduces GIS-based statistical methods for the study of settlement patterning in an archaeological context. The main aspect is an improvement over suboptimal stepwise statistical model selection procedures, with the introduction of a Deletion/Substitution/Addition (DSA) algorithm, a systematic model selection algorithm that provides an optimal model choice. The paper also introduces the combined use of Receiving Operator Characteristic (ROC)