Relevant bibliographies by topics / Forecasting modeling / Dissertations / Theses
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Dissertations / Theses on the topic 'Forecasting modeling'

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Published: 2 June 2025
Last updated: 31 July 2025

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1

Marsilli, Clément. "Mixed-Frequency Modeling and Economic Forecasting." Thesis, Besançon, 2014. http://www.theses.fr/2014BESA2023/document.

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La prévision macroéconomique à court terme est un exercice aussi complexe qu’essentiel pour la définition de la politique économique et monétaire. Les crises financières récentes ainsi que les récessions qu’ont endurées et qu’endurent aujourd’hui encore, en ce début d’année 2014, nombre de pays parmi les plus riches, témoignent de la difficulté d’anticiper les fluctuations économiques, même à des horizons proches. Les recherches effectuées dans le cadre de la thèse de doctorat qui est présentée dans ce manuscrit se sont attachées à étudier, analyser et développer des modélisations pour la prév
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Xu, Huaidong. "Forecasting innovation diffusion : a modeling approach." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/23413.

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3

Ning, Yue. "Modeling Information Precursors for Event Forecasting." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/84486.

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This dissertation is focused on the design and evaluation of machine learning algorithms for modeling information precursors for use in event modeling and forecasting. Given an online stream of information (e.g., news articles, social media postings), how can we model and understand how events unfold, how they influence each other, and how they can act as determinants of future events? First, we study information reciprocity in joint news and social media streams to capture how events evolve. We present an online story chaining algorithm which links related news articles together in a low com
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Shah, Ismail. "Modeling and Forecasting Electricity Market Variables." Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3427110.

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In deregulated electricity markets, accurate modeling and forecasting of different variables, e.g. demand, prices, production etc. have obtained increasing importance in recent years. As in most electricity markets, the daily demand and prices are determined the day before the physical delivery by means of (semi-) hourly concurrent auctions, accurate forecasts are necessary for the efficient management of power systems. However, it is well known that electricity (demand/price) data exhibit some specific features, among which, daily, weekly and annual periodic patterns as well as non-constant m
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Ahmed, Shadman. "Phase-Out Demand Forecasting : Predictive modeling on forecasting product life cycle." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-287446.

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The phase-out stage in a product life cycle can face unpredictable demand. Accurate forecast of the phase-out demand can help supply chain managers to control the number of obsolete inventories. Consequently, having a positive effect in terms of resources and lower scrap costs. In this thesis, we investigated if data-driven forecasting models could improve the accuracy of forecasting the phase-out stage when compared with domain experts. Since the space of available models is vast, a set of 11 best performing models according to literature were investigated. Furthermore, a thorough model selec
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Brendel, Conrad. "Analysis, Modeling, and Forecasting Of Urban Flooding." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/105131.

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As the world becomes more urbanized and heavy precipitation events increase in frequency and intensity, urban flooding is an emerging concern. Urban flooding is caused when heavy rainfall collects on the landscape, exceeding the capacity of drainage systems to effectively convey runoff. Unlike riverine and coastal flooding, urban flooding occurs frequently, and its risks and impacts are not restricted to areas within floodplains or near bodies of water. The objective of this dissertation is to improve our understanding of urban flooding and our capability to predict it through the development
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Shepero, Mahmoud. "Modeling and forecasting the load in the future electricity grid : Spatial electric vehicle load modeling and residential load forecasting." Licentiate thesis, Uppsala universitet, Fasta tillståndets fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-359432.

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The energy system is being transitioned to increase sustainability. This transition has been accelerated by the increased awareness about the adverse effects of the greenhouse gas (GHG) emissions into the atmosphere. The transition includes switching to electricity as the energy carrier in some sectors, e.g., transportation, increasing the contribution of renewable energy sources (RES) to the grid, and digitalizing the grid services. Electric vehicles (EVs) are promoted and subsidized in many countries among the sustainability initiatives. Consequently, the global sales of EVs rapidly increase
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8

Hall, Jeremy T. "Forecasting Marine Corps enlisted attrition through parametric modeling." Thesis, Monterey, Calif. : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/March/09Mar%5FHall_Jeremy.pdf.

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Thesis (M.S. in )--Naval Postgraduate School, March 2009.<br>Thesis Advisor(s): Buttrey, Samuel E. "March 2009." Description based on title screen as viewed on April 23, 2009. Author(s) subject terms: Forecasting, attrition, Marine Corps NEAS losses, Gompertz Model, survival analysis. Includes bibliographical references (p. 67). Also available in print.
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AJMAL, KHAN, and MAHMOOD HASHMI TAHIR. "Daily Calls Volume Forecasting." Thesis, Högskolan Dalarna, Statistik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4852.

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A massive amount has been written about forecasting but few articles are written about the development of time series models of call volumes for emergency services. In this study, we use different techniques for forecasting and make the comparison of the techniques for the call volume of the emergency service Rescue 1122 Lahore, Pakistan. For the purpose of this study data is taken from emergency calls of Rescue 1122 from 1st January 2008 to 31 December 2009 and 731 observations are used. Our goal is to develop a simple model that could be used for forecasting the daily call volume. Two differ
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10

Akter, Lutfa. "Modeling, forecasting and resource allocation in cognitive radio networks." Diss., Manhattan, Kan. : Kansas State University, 2010. http://hdl.handle.net/2097/3892.

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11

Yan, Tsz-leung, and 甄子良. "Spatio-temporal modeling and forecasting of air quality data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/197498.

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Respirable Suspended Particulate (RSP) time series data sampled in an air quality monitoring network are found strongly correlated and they are varying in highly similar patterns. This study provides a methodology for spatio-temporal modeling and forecasting of multiple RSP time series, in which the dynamic spatial correlations amongst the series can be effectively utilized. 　　The efficacy of the Spatio-Temporal Dynamic Harmonic Regression (STDHR) model is demonstrated. Based on the decomposition of the observed time series into the trend and periodic components, the model is capable of maki
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Wu, Hao. "Theory of Ensemble Forecasting - - with Applications in Transport Modeling." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/26252.

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Ensemble forecasting is a modeling approach that internalizes uncertainties, combining models with different assumptions or pattern recognition methods, data from different sources, and different methods of combining models. Compared to the prevalent single-model procedure, ensemble model predictions are more useful as decision support tools. The use of ensemble forecasting has significantly improved forecast accuracy in weather forecasting, and is increasingly adopted in other fields. We find a lack of awareness, or application of ensemble models in transport, so the benefits of ensemble
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Moudiki, Thierry. "Interest rates modeling for insurance : interpolation, extrapolation, and forecasting." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSE1110/document.

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L'ORSA Own Risk Solvency and Assessment est un ensemble de règles définies par la directive européenne Solvabilité II. Il est destiné à servir d'outil d'aide à la décision et d'analyse stratégique des risques. Dans le contexte de l'ORSA, les compagnies d'assurance doivent évaluer leur solvabilité future, de façon continue et prospective. Pour ce faire, ces dernières doivent notamment obtenir des projections de leur bilan (actif et passif) sur un certain horizon temporel. Dans ce travail de thèse, nous nous focalisons essentiellement sur l'aspect de prédiction des valeurs futures des actifs. Pl
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Li, Siu-hang, and 李兆恆. "Modeling mortality assumptions in actuarial science." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30289622.

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Khajehei, Sepideh. "A Multivariate Modeling Approach for Generating Ensemble Climatology Forcing for Hydrologic Applications." PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2403.

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Reliability and accuracy of the forcing data plays a vital role in the Hydrological Streamflow Prediction. Reliability of the forcing data leads to accurate predictions and ultimately reduction of uncertainty. Currently, Numerical Weather Prediction (NWP) models are developing ensemble forecasts for various temporal and spatial scales. However, it is proven that the raw products of the NWP models may be biased at the basin scale; unlike model grid scale, depending on the size of the catchment. Due to the large space-time variability of precipitation, bias-correcting the ensemble forecasts has
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Lubitz, William David. "Near real time wind energy forecasting incorporating wind tunnel modeling /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2005. http://uclibs.org/PID/11984.

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Khodatalab, Newsha, and Newsha Khodatalab. "Distributed hydrologic modeling for flow forecasting using high-resolution data." Thesis, The University of Arizona, 2002. http://hdl.handle.net/10150/626927.

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The recent availability of NEXRAD rainfall data, along with high-resolution Digital Elevation Maps (DEM), soil, land-use, and land-cover data, has motivated the use of such data to improve distributed hydrologic modeling. The National Weather Service Hydrologic Lab (NWSHL) is promoting the Distributed Modeling Intercomparison Project (DMIP) to encourage the use of spatially distributed data to improve flow modeling and prediction along the entire river system The main goal of DMIP is to promote the development of models and modeling systems that best utilize NEXRAD and other spat
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18

Gribisch, Bastian [Verfasser]. "Modeling and Forecasting of Multivariate Stock Market Volatility / Bastian Gribisch." Kiel : Universitätsbibliothek Kiel, 2013. http://d-nb.info/1031914897/34.

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19

Saltmarsh, Elizabeth. "A modeling trade-off forecasting environment for military aircraft sustainment." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53587.

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One of the overarching goals for military aircraft sustainment is to keep a high proportion of aircraft available despite the need for maintenance. Traditional solutions to this problem require conservative resource estimates, but this is costly. In recent years an overall paradigm shift towards affordability has created pressure to find other options for achieving high values of fleet level metrics. Past efforts at increasing affordability have had mixed success, and as a result such strategies need to be tested early on in the lifetime of a product, ideally before the product is ever fielded
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Bajracharya, Dinesh. "Econometric Modeling vs Artificial Neural Networks : A Sales Forecasting Comparison." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20400.

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Econometric and predictive modeling techniques are two popular forecasting techniques. Both ofthese techniques have their own advantages and disadvantages. In this thesis some econometricmodels are considered and compared to predictive models using sales data for five products fromICA a Swedish retail wholesaler. The econometric models considered are regression model,exponential smoothing, and ARIMA model. The predictive models considered are artificialneural network (ANN) and ensemble of neural networks. Evaluation metrics used for thecomparison are: MAPE, WMAPE, MAE, RMSE, and linear correla
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Petraru, Oren. "Airline passenger cancellations : modeling, forecasting and impacts on revenue management." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104325.

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Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 123-125).<br>Passenger demand forecasting, and subsequently passenger cancellation forecasting, are important components in any airline revenue management (RM) system. Passenger cancellations can potentially lead to flights leaving with empty seats and thus to loss of revenues. Airlines need accurate cancellation forecasting tools in order to properly compensate for cancellations, o
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Safari, Amir. "Volatility and correlation Modeling and forecasting using Support Vector Machines /." [S.l. : s.n.], 2008. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000009069.

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23

Singleton, Patrick Allen. "A Theory of Travel Decision-Making with Applications for Modeling Active Travel Demand." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/1494.

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The continuing evolution of urban travel patterns and changing policy goals and priorities requires that transportation researchers and practitioners improve their abilities to plan and forecast the demand for travel. Walking and bicycling - the primary forms of active travel - are generating increasing interest for their potential to reduce automobile use, save governmental and consumer costs, and improve personal and social health outcomes. Yet, current transportation planning tools, namely regional travel demand forecasting models, poorly represent these active travel modes, if at all. More
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Garen, David Charles. "Modeling Techniques for Water Supply Forecasting in the Western United States." PDXScholar, 1992. https://pdxscholar.library.pdx.edu/open_access_etds/1323.

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Water supply forecasting in the western United States is the prediction of the volume of water passing a given point on a stream during the primary snowmelt runoff season. Most water supply forecasts are produced from multiple linear regression models using snowpack, precipitation, and streamflow measurements as independent variables. In recent years, conceptual watershed simulation models, typically using a time step of one day, have also been used to produce these forecasts. This study examines model usage for: water supply forecasting in the West and has three specific purposes. The first i
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Ramez, Andraus Junior. "The Brazilian Air Force health system workforce-needs estimation using system dynamics." Thesis, Monterey, Calif. : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/March/09Mar%5FRamez.pdf.

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Thesis (M.S. in Management)--Naval Postgraduate School, March 2009.<br>Thesis Advisor(s): Abdel-Hamid, Tarek ; Ferrer, Geraldo. "March 2009." Description based on title screen as viewed on April 24, 2009. Author(s) subject terms: Manpower Forecasting; Brazilian Air Force Health System Manpower; Systems Dynamics; System Thinking; Modeling and Simulation; Multivariate Analysis. Includes bibliographical references (p. 65-66). Also available in print.
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Vasudevan, Sneha. "One-Step-Ahead Load Forecasting for Smart Grid Applications." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1323312608.

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Stockhammar, Pär. "Some contributions to filtering, modeling and forecasting of heteroscedastic time series." Stockholm : Department of Statistics, Stockholm University, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-38627.

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Stockhammar, Pär. "Some Contributions to Filtering, Modeling and Forecasting of Heteroscedastic Time Series." Doctoral thesis, Stockholms universitet, Statistiska institutionen, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-38627.

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Heteroscedasticity (or time-dependent volatility) in economic and financial time series has been recognized for decades. Still, heteroscedasticity is surprisingly often neglected by practitioners and researchers. This may lead to inefficient procedures. Much of the work in this thesis is about finding more effective ways to deal with heteroscedasticity in economic and financial data. Paper I suggest a filter that, unlike the Box-Cox transformation, does not assume that the heteroscedasticity is a power of the expected level of the series. This is achieved by dividing the time series by a movin
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Desaling, Germay Meron. "Modeling and Forecasting Unemployment Rate In Sweden using various Econometric Measures." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-51425.

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Yan, Hongxiang. "From Drought Monitoring to Forecasting: a Combined Dynamical-Statistical Modeling Framework." PDXScholar, 2016. http://pdxscholar.library.pdx.edu/open_access_etds/3292.

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Drought is the most costly hazard among all natural disasters. Despite the significant improvements in drought modeling over the last decade, accurate provisions of drought conditions in a timely manner is still one of the major research challenges. In order to improve the current drought monitoring and forecasting skills, this study presents a hybrid system with a combination of remotely sensed data assimilation based on particle filtering and a probabilistic drought forecasting model. Besides the proposed drought monitoring system through land data assimilation, another novel aspect of this
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Vander, Elst Harry-Paul. "Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data." Doctoral thesis, Universite Libre de Bruxelles, 2016. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/228960.

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This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexi
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Aronsson, Henrik. "Modeling strategies using predictive analytics : Forecasting future sales and churn management." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-167130.

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This project was carried out for a company named Attollo, a consulting firm specialized in Business Intelligence and Corporate Performance Management. The project aims to explore a new area for Attollo, predictive analytics, which is then applied to Klarna, a client of Attollo. Attollo has a partnership with IBM, which sells services for predictive analytics. The tool that this project is carried out with, is a software from IBM: SPSS Modeler. Five different examples are given of what and how the predictive work that was carried out at Klarna consisted of. From these examples, the different pr
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Kalotychou, Elena. "Modeling and forecasting international credit risk : the case of sovereign loans." Thesis, City University London, 2004. http://openaccess.city.ac.uk/8432/.

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This thesis investigates the relative merits of econometric modeling, statistical and judgmental techniques for predicting debt crises and assessing the risk of credit migration. The increased reliance on econometric or statistical approaches and credit rating systems in risk management has intensified the need for more rigorous analysis of their finite sample properties. A better understanding of the available tools has implications for credit risk management, regulation and policy decision-making. The thesis contributes to the extant sovereign risk literature in three areas. First, it addres
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Petersen, Brian J. (Brian Jude). "Reverse supply chain forecasting and decision modeling for improved inventory management." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/80988.

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Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 69-71).<br>This thesis details research performed during a six-month engagement with Verizon Wireless (VzW) in the latter half of 2012. The key outcomes are a forecasting model and decision-support framework to improve management of VzW's reverse supply chain inventory. The
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Al-Marwani, Hamed Ahmed. "An approach to modeling and forecasting real estate residential property market." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/10005.

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This thesis aims to provide an approach to real estate residential modeling and forecasting covering property types’ correlation, time series attributes within a region or a city, and socio-economic attributes of preferred real estate locations. The thesis covers residential estate markets and concentrates on property types, while previous studies that have considered country wide house price indices. There is a gap identified in the literature in the need to study correlations between property types within a region or a city and whether they will provide diversification benefits for real esta
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Kandil, Nahi A. "Unit Response Modeling and Forecasting for a Large Electric Power System." Ohio University / OhioLINK, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1239730577.

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Nanzad, Bolorchimeg. "EVALUATION OF STATISTICAL METHODS FOR MODELING HISTORICAL RESOURCE PRODUCTION AND FORECASTING." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/theses/2192.

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This master’s thesis project consists of two parts. Part I of the project compares modeling of historical resource production and forecasting of future production trends using the logit/probit transform advocated by Rutledge (2011) with conventional Hubbert curve fitting, using global coal production as a case study. The conventional Hubbert/Gaussian method fits a curve to historical production data whereas a logit/probit transform uses a linear fit to a subset of transformed production data. Within the errors and limitations inherent in this type of statistical modeling, these methods provide
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Bachour, Roula. "Modeling and forecasting evapotranspiration for better management of irrigation command areas." DigitalCommons@USU, 2013. https://digitalcommons.usu.edu/etd/2077.

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It has become very crucial to manage water resources to meet the needs of the growing population. In irrigation command areas, and in order to build a better plan to manage service delivery from canals and reservoirs, it is important to build appropriate knowledge of water needs on a field basis. There is often a lag between the order and delivery of water to the field. Knowledge of the crop water requirement at the field level helps the decision maker to make the right choices leading to more efficient handling of the available water. The purpose of this study was to develop methodologies and
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BERNARDINI, EMMANUELA. "On the use of shrinkage estimators in macroeconometric modeling and forecasting." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2010. http://hdl.handle.net/2108/207742.

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In the last years a growing °ow of information in the ¯eld of macroeconomy has been collected in very large databases. It is well known nevertheless that, when a large number of series is available standard statistical tools do not work well. This thesis proposes new estimators for high dimensional systems, that are an optimally weighted average of two already existing estimators, a traditional unbiased one, su®ering of a large estimation error, and a target one, having a lot of bias coming from a misspeci¯ed structural assumption, but little in terms of variance. This method is generall
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NIU, LINLIN. "Interest rate term structure modeling and forecasting with macro-finance models." Doctoral thesis, Università Bocconi, 2008. https://hdl.handle.net/11565/4051223.

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Simmons, Laurette Poulos. "The Development and Evaluation of a Forecasting System that Incorporates ARIMA Modeling with Autoregression and Exponential Smoothing." Thesis, North Texas State University, 1985. https://digital.library.unt.edu/ark:/67531/metadc332047/.

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This research was designed to develop and evaluate an automated alternative to the Box-Jenkins method of forecasting. The study involved two major phases. The first phase was the formulation of an automated ARIMA method; the second was the combination of forecasts from the automated ARIMA with forecasts from two other automated methods, the Holt-Winters method and the Stepwise Autoregressive method. The development of the automated ARIMA, based on a decision criterion suggested by Akaike, borrows heavily from the work of Ang, Chuaa and Fatema. Seasonality and small data set handling were some
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McKenzie, Donald. "Modeling large-scale fire effects : concepts and applications /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/5602.

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Han, Yang. "Modeling and forecasting volatility of Shanghai Stock Exchange with GARCH family models." Thesis, Uppsala universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-155066.

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This paper discusses the performance of modeling and forecasting volatility ofdaily stock returns of A-shares in Shanghai Stock Exchange. The volatility is modeledby GARCH family models which are GARCH, EGARCH and GJR-GARCHmodels with three distributions, namely Gaussian distribution, student-t distributionand generalized error distribution (GED). In order to determine the performanceof forecasting volatility, we compare the models by using the Root MeanSquared Error (RMSE). The results show that the EGARCH models work so wellin most of daily stock returns and the symmetric GARCH models are be
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Bush, Sarah 1973. "Forecasting 65+ travel : an integration of cohort analysis and travel demand modeling." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/29941.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2003.<br>Includes bibliographical references (leaves 96-104).<br>Over the next 30 years, the Boomers will double the 65+ population in the United States and comprise a new generation of older Americans. This study forecasts the aging Boomers' travel. Previous efforts to forecast 65+ travel are lacking in key two respects: they have failed to incorporate generation differences and have forecasted only broad travel characteristics (e.g. vehicle miles traveled). Drawing on the theory of generatio
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Anand, Chaoba Nikkie. "Internet traffic modeling and forecasting using non-linear time series model GARCH." Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/2229.

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Gehman, Andrew J. "The Effects of Spatial Aggregation on Spatial Time Series Modeling and Forecasting." Diss., Temple University Libraries, 2016. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/382669.

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Statistics<br>Ph.D.<br>Spatio-temporal data analysis involves modeling a variable observed at different locations over time. A key component of space-time modeling is determining the spatial scale of the data. This dissertation addresses the following three questions: 1) How does spatial aggregation impact the properties of the variable and its model? 2) What spatial scale of the data produces more accurate forecasts of the aggregate variable? 3) What properties lead to the smallest information loss due to spatial aggregation? Answers to these questions involve a thorough examination of two co
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Tang, Fan. "Structural time series clustering, modeling, and forecasting in the state-space framework." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/6002.

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This manuscript consists of two papers that formulate novel methodologies pertaining to time series analysis in the state-space framework. In Chapter 1, we introduce an innovative time series forecasting procedure that relies on model-based clustering and model averaging. The clustering algorithm employs a state-space model comprised of three latent structures: a long-term trend component; a seasonal component, to capture recurring global patterns; and an anomaly component, to reflect local perturbations. A two-step clustering algorithm is applied to identify series that are both globally and
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48

Watkins, Arica. "Successful Demand Forecasting Modeling Strategies for Increasing Small Retail Medical Supply Profitability." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/7576.

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The lack of effective demand forecasting strategies can result in imprecise inventory replenishment, inventory overstock, and unused inventory. The purpose of this single case study was to explore successful demand forecasting strategies that leaders of a small, retail, medical supply business used to increase profitability. The conceptual framework for this study was Winters's forecasting demand approach. Data were collected from semistructured, face-to-face interviews with 8 business leaders of a private, small, retail, medical supply business in the southeastern United States and the review
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Dickerson, Susan E. Mitchell Robert. "Modeling the effects of climate change forecasts on streamflow in the Nooksack River Basin /." Online version, 2010. http://content.wwu.edu/cdm4/item_viewer.php?CISOROOT=/theses&CISOPTR=366&CISOBOX=1&REC=1.

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Das, Barnali. "Global covariance modeling : a deformation approach to anisotropy /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/8955.

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