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Dissertations / Theses on the topic 'State forecasting'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Key, Peter Bernard. "Bayesian forecasting with state space models." Thesis, Royal Holloway, University of London, 1986. http://repository.royalholloway.ac.uk/items/87d86ed9-b2e7-4393-9fef-696f8c0cd147/1/.

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This thesis explores the use of State-Space models in Time Series Analysis and Forecasting, with particular reference to the Dynamic Linear Model (DLM) introduced by Harrison and Stevens. Concepts from Control Theory are employed, especially those of observability, controllability and filtering, together with Bayesian inference and classical forecasting methodology. First, properties of state-space models which depart from the usual Gaussian assumptions are examined, and the predictive consequences of such models are developed. These models can lead to new phenomena, for example it is shown th

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2

Lawson, Richard. "Adaptive state-space forecasting of gas demand." Thesis, Lancaster University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358799.

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3

AMARAL, MARCELO RUBENS DOS SANTOS DO. "STATE SPACE MODELS: MULTIVARIATE FORMULATION APPLIED TO LOAD FORECASTING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1996. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8707@1.

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CENTRO DE PESQUISA DE ENERGIA ELÉTRICA<br>Os métodos de análise de séries temporais têm se revelado uma importante ferramenta de apoio à tomada de decisões, com importância crescente em um mundo cada vez mais globalizado. Esse fato pode ser ilustrado, entre muitos outros, através de um convênio firmado entre o CEPEL, o Núcleo de Estatística Computacional da PUC/RJ e a Eletrobrás, para se avaliar a utilidade dessas ferramentas nas etapas do planejamento do setor elétrico brasileiro. A metodologia em Espaço de Estado proporcionou o surgimento de duas importantes classes de modelos de pr

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4

Marshall, Richard Carel. "A state space forecasting approach to commodity futures trading." Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/185667.

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State space forecasting originated in the mid-1970's from engineering models based upon the Kalman filter. To date, the application of state space forecasting to commodity and financial markets has been limited. This study examines a system for trading futures contracts using state space forecasts of commodity futures prices. The system is evaluated for a speculative asset (gold) and a nonspeculative commodity (copper). Price forecasts are developed from multivariate state space models, and the variables considered in the models are those which, according to economic theory, may influence pric

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5

Bae, Kyungcho. "Energy consumption forecasting: Econometric model vs state space model." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/187010.

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This study examines the forecasting performance of two major multivariate methodologies: econometric modeling and multivariate state space modeling. The same variables are used in both models to facilitate comparison. They are evaluated by both expost and exante accuracy of U.S. energy consumption forecasts. Econometric models are highly simplified and a model selection procedure is applied to the models. Two different formats of multivariate state space models are examined: economic structure and identity structure. Goodrich's algorithm is employed to estimate the state space models. The stat

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6

Li, Ying. "Forecasting Long Term Highway Staffing Requirements for State Transportation Agencies." UKnowledge, 2016. http://uknowledge.uky.edu/ce_etds/42.

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The transportation system is vital to the nation’s economic growth and stability, as it provides mobility for commuters while supporting the United States’ ability to compete in an increasingly competitive global economy. State Transportation Agencies across the country continue to face many challenges to repair and enhance highway infrastructure to meet the rapid increasing transportation needs. One of these challenges is maintaining an adequate and efficient agency staff. In order to effectively plan for future staffing levels, State Transportation Agencies need a method for forecasting long

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naz, saima. "Forecasting daily maximum temperature of Umeå." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112404.

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The aim of this study is to get some approach which can help in improving the predictions of daily temperature of Umeå. Weather forecasts are available through various sources nowadays. There are various software and methods available for time series forecasting. Our aim is to investigate the daily maximum temperatures of Umeå, and compare the performance of some methods in forecasting these temperatures. Here we analyse the data of daily maximum temperatures and find the predictions for some local period using methods of autoregressive integrated moving average (ARIMA), exponential smoothing

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8

Chen, Yu. "FORECASTING WITH MIXED FREQUENCY DATA:MIDAS VERSUS STATE SPACE DYNAMIC FACTOR MODEL : AN APPLICATION TO FORECASTING SWEDISH GDP GROWTH." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-29475.

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Most macroeconomic activity series such as Swedish GDP growth are collected quarterly while an important proportion of time series are recorded at a higher frequency. Thus, policy and business decision makers are often confront with the problems of forecasting and assessing current business and economy state via incomplete statistical data due to publication lags. In this paper, we survey a few general methods and examine different models for mixed frequency issues. We mainly compare mixed data sampling regression (MIDAS) and state space dynamic factor model (SS-DFM) by the comparison experime

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9

Hassanzadeh, Mohammadtaghi. "A New State Transition Model for Forecasting-Aided State Estimation for the Grid of the Future." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64407.

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The grid of the future will be more decentralized due to the significant increase in distributed generation, and microgrids. In addition, due to the proliferation of large-scale intermittent wind power, the randomness in power system state will increase to unprecedented levels. This dissertation proposes a new state transition model for power system forecasting-aided state estimation, which aims at capturing the increasing stochastic nature in the states of the grid of the future. The proposed state forecasting model is based on time-series modeling of filtered system states and it takes spati

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10

Scott, Paul J. "Minimal dimension state space identification, theory and applications in climate forecasting." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ57193.pdf.

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11

Unosson, Måns. "A Mixed Frequency Steady-State Bayesian Vector Autoregression: Forecasting the Macroeconomy." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297406.

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This thesis suggests a Bayesian vector autoregressive (VAR) model which allows for explicit parametrization of the unconditional mean for data measured at different frequencies, without the need to aggregate data to the lowest common frequency. Using a normal prior for the steady-state and a normal-inverse Wishart prior for the dynamics and error covariance, a Gibbs sampler is proposed to sample the posterior distribution. A forecast study is performed using monthly and quarterly data for the US macroeconomy between 1964 and 2008. The proposed model is compared to a steady-state Bayesian VAR m

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12

Pasquali, Flavia. "State space models for the analysis and forecasting of climatic time series." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23081/.

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We analyse climatic time series with state space models in order to compute the forecast distribution. The task is challenging since the temperature series are characterised by large temporal and cross-sectional dimensions. We modify and apply the three-step method proposed in Li et al. Journal of Econometrics 2020, which exploit the cross information in order to improve prediction. We fit the linear Gaussian state space model to different univariate time series, estimating the model parameters with the Kalman filter and computing the prediction errors. The prediction error time series are t

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13

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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14

Deen, Gary T., and Glenn G. Buni. "Development of a steady state model for forecasting U.S. Navy Nurse Corps personnel." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1699.

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Approved for public release; distribution is unlimited<br>This thesis developed a deterministic Markov state model to provide the U.S. Navy Nurse Corps a tool to more accurately forecast recruiting goals and future years force structure. Nurse Corps data was provided by the Nurse Corps Community Manager's office covering fiscal years 1990 to 2003. The probabilities used in the Markov model were derived from the fiscal year data. Transitions used in this model were stay at present grade, move up one grade or exit the system. Backward movement was not allowed and individuals could only move up o

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15

Buni, Glenn G. Deen Gary T. "Development of a steady state model for forecasting U.S. Navy Nurse Corps personnel /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Mar%5FBuni.pdf.

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16

Owaniyi, Kunle Meshach. "Geostatistical Interpolation and Analyses of Washington State AADT Data from 2009 – 2016." Thesis, North Dakota State University, 2019. https://hdl.handle.net/10365/31649.

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Annual Average Daily Traffic (AADT) data in the transportation industry today is an important tool used in various fields such as highway planning, pavement design, traffic safety, transport operations, and policy-making/analyses. Systematic literature review was used to identify the current methods of estimating AADT and ranked. Ordinary linear kriging occurred most. Also, factors that influence the accuracy of AADT estimation methods as identified include geographical location and road type amongst others. In addition, further analysis was carried out to determine the most apposite kriging a

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17

Quinn, Niall. "Forecasting of ocean state in a complex estuarine environment : the Solent-Southampton Water Estuarine System." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/359671/.

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Coastal flooding is a natural hazard causing devastation to many regions throughout the world, induced by the coincidence of high spring tides, large storm surges and waves. To reduce the risk posed by coastal inundation, warning systems have been developed to enable preparations to an expected threat. Although current operational predictions provide invaluable warnings, uncertainty in model formulations and input datasets, can lead to errors in forecasts. In order to provide coastal managers with the best possible information with which to make decisions, recent research has begun to focus on

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18

Bollinger, Julie R. 1952. "Forecasting Future Events Affecting One Institution of Higher Education in the State of Texas: A Delphi Application." Thesis, North Texas State University, 1987. https://digital.library.unt.edu/ark:/67531/metadc331648/.

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The purpose of this study was to investigate the possible events in the external environment between 1987 and 1997 that may affect the future of North Texas State University. Two groups of experts participated in the study, a group of individuals from outside North Texas State University and a group of experts from the university.

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19

Hotz-Behofsits, Christian, Florian Huber, and Thomas Zörner. "Predicting crypto-currencies using sparse non-Gaussian state space models." Wiley, 2018. http://dx.doi.org/10.1002/for.2524.

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In this paper we forecast daily returns of crypto-currencies using a wide variety of different econometric models. To capture salient features commonly observed in financial time series like rapid changes in the conditional variance, non-normality of the measurement errors and sharply increasing trends, we develop a time-varying parameter VAR with t-distributed measurement errors and stochastic volatility. To control for overparameterization, we rely on the Bayesian literature on shrinkage priors that enables us to shrink coefficients associated with irrelevant predictors and/or perform model

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20

Liao, Kai. "Modeling Intrastate Air Travel: A Case Study of the State of Florida." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5983.

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Florida is a state in the southeastern region of the United States. Its infrastructure allows for several travel modes including: rail, automobile, bus, aircraft, and ship. However, most intrastate travelers in Florida are limited to two practical choices: travel by car (ground mode) or travel by air (air primary mode). Due to the dramatic growth of Florida’s population over recent years, traffic has become a critical factor that impacts Florida’s development. This thesis focuses on intrastate air primary mode and develops decision making models that could aid government and airline companies

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21

Shafiei, Mehdi. "Distribution network state estimation, time dependency and fault detection." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/124659/2/Mehdi_Shafiei_Thesis.pdf.

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In this research work, the combination of three novel approaches is established to estimate the states of three-phase balanced and unbalanced distribution networks and using the developed methods for high impedance fault detection. The effectiveness of the developed methods are proposing a fast real-time state estimator with a low number of measurement devices, avoiding bad data detection in state estimation, and dynamically updating fault current thresholds to detect high impedance faults in the distribution networks.

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22

Wang, Shuchun. "Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/19753.

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Despite their success and widespread usage in industry and business, ES methods have received little attention from the statistical community. We investigate three types of statistical models that have been found to underpin ES methods. They are ARIMA models, state space models with multiple sources of error (MSOE), and state space models with a single source of error (SSOE). We establish the relationship among the three classes of models and conclude that the class of SSOE state space models is broader than the other two and provides a formal statistical foundation for ES methods. To better u

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23

Vogel, Vance T. "Determining personnel accession requirements for Medical Service Corps Health Care Administrators using a steady state analysis /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Mar%5FVogel.pdf.

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Thesis (M.S. in Business Administration)--Naval Postgraduate School, March 2006.<br>Thesis Advisor(s): Anke Richter, Kathryn M. Kocher. Includes bibliographical references (p. 113-114 ). Also available online.

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24

Huber, Sandra [Verfasser], Harry [Akademischer Betreuer] Haupt, and Heinrich [Akademischer Betreuer] Oberreuter. "The role of polls for election forecasting in German state elections / Sandra Huber ; Harry Haupt, Heinrich Oberreuter." Passau : Universität Passau, 2018. http://d-nb.info/1162697695/34.

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25

Nguyen, Van O. "Analysis of the U.S. Marine Corps' steady state Markov model for forecasting annual first-term enlisted classification requirements." Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/25685.

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Approved for public release; distribution is unlimited.<br>The Marine Corps accesses approximately 29,000 to 36,000 new recruits annually. Determining how to classify these new enlistees into more than 200 Military Occupational Specialties is a critical task. These classification estimates must be precise, so the units within the Fleet Marine Force will have the necessary personnel to accomplish their mission. At the same time, these manpower planners must also balance the force structure to minimize personnel overages which could lead to excessive labor and training costs as well as promotion

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26

RUEDA, CAMILO VELASCO. "ESNPREDICTOR: TIME SERIES FORECASTING APPLICATION BASED ON ECHO STATE NETWORKS OPTIMIZED BY GENETICS ALGORITHMS AND PARTICLE SWARM OPTIMIZATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24785@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>A previsão de séries temporais é fundamental na tomada de decisões de curto, médio e longo prazo, em diversas áreas como o setor elétrico, a bolsa de valores, a meteorologia, entre outros. Tem-se na atualidade uma diversidade de técnicas e modelos para realizar essas previsões, mas as ferramentas estatísticas são as mais utilizadas principalmente por apresentarem um maior grau d

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27

Erasmus, Magdel. "Formation and Development of Tropical Temperate Troughs across Southern Africa as Simulated by a State-of-the-art Coupled Model." Diss., University of Pretoria, 2019. http://hdl.handle.net/2263/73478.

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A Tropical Temperate Trough (TTT) is a type of weather system that links the tropics and the extra-tropics across southern Africa. TTT events have been studied statistically in detail, but very little research has been done to study this phenomenon dynamically and especially on a seasonal scale. This study therefore focuses on the predictability of the characteristics of TTTs across southern Africa on a seasonal scale, by using a state-of-the-art seasonal forecasting model, namely the GloSea5 developed by the UK Met Office. Gridded hindcast data for the months of November, December, January an

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28

McCarthy, Theresa Helen. "The best predictors of medical claims costs at Ball State University." Virtual Press, 1999. http://liblink.bsu.edu/uhtbin/catkey/1125589.

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The purpose of this study was to explore, from readily available data, the best predictors of medical claims costs at Ball State University (BSU). Multiple regression equations were developed to predict BSU's medical claims costs from selected demographic and health-related measures among 1,799 BSU employees. The predictors were chosen from data previously collected during the three-year study period: July 1, 1995 to June 30, 1998. Regression equations were developed for the entire BSU population and the high-cost population. The linear composite of number of emergency room visits, number of c

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29

Tysyachnaya, Yunna. "Information tools of modeling and forecasting the state of the territory of ukraine according to the level of environmental protection." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/10264.

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30

Ukrainets, I., and N. Karaeva. "Information tools of modeling and forecasting the state of the territory of ukraine according to the level of environmental protection." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/10275.

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31

Gendre, Victor Hugues. "Predicting short term exchange rates with Bayesian autoregressive state space models: an investigation of the Metropolis Hastings algorithm forecasting efficiency." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437399395.

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32

Paramygin, Vladimir A. "Towards a real-time 24/7 storm surge, inundation and 3-D baroclinic circulation forecasting system for the state of Florida." [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024729.

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33

Steed, Chad A. "Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis." Diss., Mississippi State : Mississippi State University, 2008. http://library.msstate.edu/etd/show.asp?etd=etd-10252008-080937.

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34

Grohmann, Alexander. "Influences of marketing response time on sales planning and forecasting in the industrial context." Thesis, Bloemfontein : Central University of Technology, Free State, 2012. http://hdl.handle.net/11462/166.

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Thesis (D. Tech.(Marketing)) - Central University of Technology, Free state, 2012<br>A reliable sales plan and forecast is the basis for good cash flow management and capacity planning. If the sales figures are below plan, the sales manager will increase the sales efforts in order to compensate these deviations. Usually, it can be expected that these efforts should be at least partly successful in the consumer markets. This situation is expected to be different in the industrial markets, as usually the generation of sales turnover can only be achieved by either new customers or new products s

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35

Hartkopf, Jan Patrick [Verfasser], Roman [Gutachter] Liesenfeld, and Jörg [Gutachter] Breitung. "Modeling and Forecasting of Realized Covariance Matrices of Asset Returns using State-Space Models / Jan Patrick Hartkopf ; Gutachter: Roman Liesenfeld, Jörg Breitung." Köln : Universitäts- und Stadtbibliothek Köln, 2021. http://d-nb.info/1234655144/34.

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36

Ben-Belhassen, Boubaker. "Econometric models of the Argentine cereal economy : a focus on policy simulation analysis /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9842508.

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Oliveira, Silvia Fernanda. "Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara." Universidade Federal do CearÃ, 2011. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7387.

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The timeliness with which economic agents make their decisions encourages the development of tools in order to anticipate changes in economic aggregates. Following this, the study analyses and develops models to forecast the industrial production from CearÃ energy consumption measured by COELCE. Vector Autoregressive models (VAR) are estimated and scenarios are constructed for the period 2011-2012. The estimates were robust and the simulations indicated an increase of 3.9% in industrial production CearÃ until 2012, comparing with the values observed in 2010, without seasonal effects.<br>A temp

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38

Alshalan, Abdullah. "Cyber-crime fear and victimization." Diss., Mississippi State : Mississippi State University, 2006. http://library.msstate.edu/etd/show.asp?etd=etd-01232006-095728.

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Bahiigwa, Godfrey. "The Brazilian soybean industry : an econometric framework for policy impact analysis /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9841261.

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40

Nyewe, Papomile Mphathi. "Design of a framework for implementing strategic foresight at South African state owned enterprises." Thesis, Stellenbosch : Stellenbosch University, 2011. http://hdl.handle.net/10019.1/18163.

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Thesis (MPhil)--Stellenbosch University, 2011.<br>In many spheres of life, humanity is finally coming to terms with the fact that our world has changed beyond the limits of our industrial-era ways of thinking. Linear and reductionist approaches to strategy and problem-solving are no longer sufficient for dealing with the realities of our modern world, which are characterised by the certainty of change; not least of all due to technological change and environmental factors such as resource scarcity and global warming. Some of the changes that humanity has experienced include; • Uncertaint

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Філатова, Ганна Петрівна, Анна Петровна Филатова та Hanna Petrivna Filatova. "Прогнозування державного боргу з використанням ARIMA моделі". Thesis, ЦФЕНД, 2020. https://essuir.sumdu.edu.ua/handle/123456789/84293.

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Державний борг як важливий фактор соціально-економічного розвитку держави виступає свого роду індикатором і критерієм ефективності провадження виваженої боргової політики держави, а його прогнозування займає одне з ключових місць в процесі забезпечення економічної безпеки держави. У сучасній статистичній теорії існує безліч різноманітних методів прогнозування економічної інформації. Значна їх частина стосується прогнозування часових рядів, без додаткової інформації, тобто без аналізу впливу інших факторів. Звичайно, такий аналіз є доволі неповним, але досить часто результати таких прогнозів є

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Mansoor, Shaheer. "System Surveillance." Thesis, Linköpings universitet, Statistik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-98189.

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In recent years, trade activity in stock markets has increased substantially. This is mainly attributed to the development of powerful computers and intranets connecting traders to markets across the globe. The trades have to be carried out almost instantaneously and the systems in place that handle trades are burdened with millions of transactions a day, several thousand a minute. With increasing transactions the time to execute a single trade increases, and this can be seen as an impact on the performance. There is a need to model the performance of these systems and provide forecasts to giv

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Razroev, Stanislav. "AUTOMATED OPTIMAL FORECASTING OF UNIVARIATE MONITORING PROCESSES : Employing a novel optimal forecast methodology to define four classes of forecast approaches and testing them on real-life monitoring processes." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-165990.

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This work aims to explore practical one-step-ahead forecasting of structurally changing data, an unstable behaviour, that real-life data connected to human activity often exhibit. This setting can be characterized as monitoring process. Various forecast models, methods and approaches can range from being simple and computationally "cheap" to very sophisticated and computationally "expensive". Moreover, different forecast methods handle different data-patterns and structural changes differently: for some particular data types or data intervals some particular forecast methods are better than th

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Nigrini, Lucas Bernardo. "Developing a neural network model to predict the electrical load demand in the Mangaung municipal area." Thesis, [Bloemfontein?] : Central University of Technology, Free State, 2012. http://hdl.handle.net/11462/176.

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Thesis (D. Tech. (Engineering: Electric)) -- Central University of technology, 2012<br>Because power generation relies heavily on electricity demand, consumers are required to wisely manage their loads to consolidate the power utility‟s optimal power generation efforts. Consequently, accurate and reliable electric load forecasting systems are required. Prior to the present situation, there were various forecasting models developed primarily for electric load forecasting. Modelling short term load forecasting using artificial neural networks has recently been proposed by researchers.

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Fore, Todd A. "Predicting Workers' Compensation Claims and On-the-Job Injuries Using Four Psychological Measures." Thesis, University of North Texas, 1998. https://digital.library.unt.edu/ark:/67531/metadc278884/.

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This study assessed the predictive validity of four independent factors (Rotter Locus of Control Scale, Safety Locus of Control, Organizational Attribution Style Questionnaire, and Rosenburg Self-Esteem Scale) in the establishment of a measure of safety consciousness in predicting on-the-job injuries and the filing of workers' compensation claims. A 125-item questionnaire was designed and administered to assess participants' disposition on each of the four psychological dimensions, demographic data and on-the-job injury information.

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Bender, Fabiani Denise. "Verificação da previsão do tempo em São Paulo com o modelo operacional WRF." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/14/14133/tde-19122012-120128/.

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Este estudo tem como objetivo a verificação das previsões diárias, das temperaturas máxima e mínima e precipitação acumulada, realizadas pelo modelo operacional de previsão numérica do tempo WRF (Weather Research Forecasting) para o estado de São Paulo. As condições iniciais e de fronteira fornecidas pela análise e previsão das 00UTC do modelo Global Forecast System (GFS), são usados no processamento do WRF, para previsões de 72 horas, em duas grades aninhadas (espaçamentos horizontais de grade de 50 km, D1, e 16,6 km, D2). O período avaliado foi de abril de 2010 a março de 2011. As comparaçõe

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Blyth, Karl Anthony. "A computer model that forecats the cash flow of building projects at the tender stage using stage payments." Thesis, University of Liverpool, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288114.

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Emery, Nathan N. "Forecasting United States Marine Corps Selected Reserve end strength." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Mar/10Mar%5FEmery.pdf.

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Thesis (M.S. in Management)--Naval Postgraduate School, March 2010.<br>Thesis Advisor(s): Hatch, William H. ; Buttrey, Samuel E. ; Dolfini-Reed, Michelle. "March 2010." Description based on title screen as viewed on April 26, 2010. Author(s) subject terms: Forcasting, Accessions, Losses, Manpower, Enlisted, Officer, Reserve, Modeling, Exponential Smoothing, Marine Corps. Includes bibliographical references (p. 31). Also available in print.

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Schumacher, Joseph F. "Forecasting retention in the United States Marine Corps Reserve." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FSchumacher.pdf.

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Pilström, Patrick, and Sebastian Pohl. "Forecasting GDP Growth : The Case of The Baltic States." Thesis, Jönköping University, JIBS, Economics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-9776.

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<p>The purpose of this thesis is to identify a general model to forecast GDP growth for the Baltic States, Estonia, Latvia and Lithuania. If the model provides reliable results for these states, then the model should be able to forecast GDP growth for other countries of interest. Forecasts are made by using a reduced vector autoregressive (VAR) model. The VAR models make use of past values of Gross Domestic Product-Inflation-Unemployment as explanatory variables.</p><p>The performed forecasts have provided good results for horizons up to t+8. The forecasts for 2009 (t+12) are in line with thos

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