Approved for public release; distribution is unlimited / This thesis presents a statistical analysis of the monthly rainfall for the Monterey Peninsula and the Carmel Valley in Central California. The analysis begins with the simple first-order autoregressive Markov model, which is found to be weak. Next, 2X2 contingency tables are used to identify predictors, one of which is found to be January rainfall. Finally, logistic analysis is used to quantify the predictive ability of January. This paper attempts to analyze rainfall time series in the statistical sense. No attempt is made to provide a physical explanation of the findings from the point of view of a meteorologist. / http://archive.org/details/statisticalanaly00davi / Captain, United States Army

De meados da década de 80 até a atualidade as atividades básicas que fazem parte da logística deixaram de ser somente consolidadoras de uma relação de compra e venda, e passaram a ter uma importância estratégica bastante grande em busca de uma maior vantagem competitiva. Esta nova importância para a logística surgiu com a abertura econômica e o acirramento da competitividade mundial. Assim, empresas se especializaram em projetar, implantar e gerenciar as atividades de logística para outras empresas (Operadores Logísticos). A tomada de decisão entre realizar as atividades logísticas através de competência interna da empresa ou repassa-las aos operadores logísticos se tornou mais freqüente nos dias de hoje. O trabalho propõe um procedimento de auxílio a tomada de decisão para empresas em fase de análise da viabilidade da utilização de operadores logísticos. Por fim o procedimento é testado no campo com dados reais uma empresa de grande porte. / From the middle of 80\'s until today, the basic logistic activities are not only to consolidate buy and sales relationship, these activities became important in strategic planning, being important to reach new markets. This new logistic importance started with openning of Brazilian economy and with the increase in world competitiveness. For this reason, enterprises improvement the logistic activities techniques, as project, implementation an management and starting to execute these activities to another enterprises with do not have logistic as core competence, these enterprises are called Third Party Logistic Provider. The decision make between insourcing or outsourcing logistic activities became more frequently nowadays. This thesis propose a procedure to help enterprises in the viability analysis phase to use third party logistic provider in its supply chain. In the end the procedure is tested in a global company with real data.

Incorporating survey weights into likelihood-based analysis is a controversial issue because the sampling weights are not simply equal to the reciprocal of selection probabilities but they are adjusted for various characteristics such as age, race, etc. Some adjustments are based on nonresponses as well. This adjustment is accomplished using a combination of probability calculations. When we build a logistic regression model to predict categorical outcomes with survey data, the sampling weights should be considered if the sampling design does not give each individual an equal chance of being selected in the sample. We rescale these weights to sum to an equivalent sample size because the variance is too small with the original weights. These new weights are called the adjusted weights. The old method is to apply quasi-likelihood maximization to make estimation with the adjusted weights. We develop a new method based on the correct likelihood for logistic regression to include the adjusted weights. In the new method, the adjusted weights are further used to adjust for both covariates and intercepts. We explore the differences and similarities between the quasi-likelihood and the correct likelihood methods. We use both binary logistic regression model and multinomial logistic regression model to estimate parameters and apply the methods to body mass index data from the Third National Health and Nutrition Examination Survey. The results show some similarities and differences between the old and new methods in parameter estimates, standard errors and statistical p-values.

Buried pipelines are vulnerable to the threat of corrosion. Hence, they are normally coated with a protective coating to isolate the metal substrate from the surrounding environment with the addition of CP current being applied to the pipeline surface to halt any corrosion activity that might be taking place. With time, this barrier will deteriorate which could potentially lead to corrosion of the pipe. The External Corrosion Direct Assessment (ECDA) methodology was developed with the intention of upholding the structural integrity of pipelines. Above ground indirect inspection techniques such as the DCVG which is an essential part of an ECDA, is commonly used to determine coating defect locations and measure the defect's severity. This is followed by excavation of the identified location for further examination on the extent of pipeline damage. Any coating or corrosion defect found at this stage is repaired and remediated. The location of such excavations is determined by the measurements obtained from the DCVG examination in the form of %IR and subjective inputs from experts which bases their justification on the environment and the physical characteristics of the pipeline. Whilst this seems to be a straight forward process, the factors that comes into play which gave rise to the initial %IR is not fully understood. The lack of understanding with the additional subjective inputs from the assessors has led to unnecessary excavations being conducted which has put tremendous financial strain on pipeline operators. Additionally, the threat of undiscovered defects due to the erroneous nature of the current method has the potential to severely compromise the pipeline's safe continual operation. Accurately predicting the coating defect size (TCDA) and interpretation of the indication signal (%IR) from an ECDA is important for pipeline operators to promote safety while keeping operating cost at a minimum. Furthermore, with better estimates, the uncertainty from the DCVG indication is reduced and the decisions made on the locations of excavation is better informed. However, ensuring the accuracy of these estimates does not come without challenges. These challenges include (1) the need of proper methods for large data analysis from indirect assessment and (2) uncertainty about the probability distribution of quantities. Standard mean regression models e.g. the OLS, were used but fail to take the skewness of the distributions involved into account. The aim of this thesis is thus, to come up with statistical models to better predict TCDA and to interpret the %IR from the indirect assessment of an ECDA more precisely. The pipeline data used for the analyses is based on a recent ECDA project conducted by TWI Ltd. for the Middle Eastern Oil Company (MEOC). To address the challenges highlighted above, Quantile Regression (QR) was used to comprehensively characterise the underlying distribution of the dependent variable. This can be effective for example, when determining the different effect of contributing variables towards different sizes of TCDA (different quantiles). Another useful advantage is that the technique is robust to outliers due to its reliance on absolute errors. With the traditional mean regression, the effect of contributing variables towards other quantiles of the dependent variable is ignored. Furthermore, the OLS involves the squaring of errors which makes it less robust to outliers. Other forms of QR such as the Bayesian Quantile Regression (BQR) which has the advantage of supplementing future inspection projects with prior data and the Logistic Quantile Regression (LQR) which ensures the prediction of the dependent variable is within its specified bounds was applied to the MEOC dataset. The novelty of research lies in the approaches (methods) taken by the author in producing the models highlighted above. The summary of such novelty includes: * The use of non-linear Quantile Regression (QR) with interacting variables for TCDA prediction. * The application of a regularisation procedure (LASSO) for the generalisation of the TCDA prediction model.* The usage of the Bayesian Quantile Regression (BQR) technique to estimate the %IR and TCDA. * The use of Logistic Regression as a guideline towards the probability of excavation * And finally, the use of Logistic Quantile Regression (LQR) in ensuring the predicted values are within bounds for the prediction of the %IR and POPD. Novel findings from this thesis includes: * Some degree of relationship between the DCVG technique (%IR readings) and corrosion dimension. The results of the relationship between TCDA and POPD highlights a negative trend which further supports the idea that %IR has some relation to corrosion. * Based on the findings from Chapter 4, 5 and 6 suggests that corrosion activity rate is more prominent than the growth of TCDA at its median depth. It is therefore suggested that for this set of pipelines (those belonging to MEOC) repair of coating defects should be done before the coating defect has reached its median size. To the best of the Author's knowledge, the process of employing such approaches has never been applied before towards any ECDA data. The findings from this thesis also shed some light into the stochastic nature of the evolution of corrosion pits. This was not known before and is only made possible by the usage of the approaches highlighted above. The resulting models are also of novelty since no previous model has ever been developed based on the said methods. The contribution to knowledge from this research is therefore the greater understanding of relationship between variables stated above (TCDA, %IR and POPD). With this new knowledge, one has the potential to better prioritise location of excavation and better interpret DCVG indications. With the availability of ECDA data, it is also possible to predict the magnitude of corrosion activity by using the models developed in this thesis. Furthermore, the knowledge gained here has the potential to translate into cost saving measures for pipeline operators while ensuring safety is properly addressed.

This thesis deals with the study of logistics and supply chain management in the manufacturing company in České Budějovice. In the introductory part of the thesis there are mentioned theoretical basis of logistics, logistic control and logistic technology. In the practical part of the thesis there is made the analysis of examined company. The analysis was focused on the preparation of the production plan and the ability to identify the main factors affecting the running of production. The next part is focused on monitoring the production line technological planning and the ability to analyze the plan. After the detection of deviations, were proposed solutions for improvements.

Doctor of Philosophy / Department of Civil Engineering / Sunanda Dissanayake / Young drivers are over-represented in crashes when compared to other age group drivers. Distracted driving is one of the major causes of traffic crashes by young drivers. The objective of this study was to assess the hazards of distracted driving among teenage (15–20 year old) and young-adult (21–26 year old) drivers in Kansas. This study used five years of crash data from the Kansas Crash and Analysis Reporting System (KCARS) database from 2011 to 2015. A multinomial logit modeling was used to identify the odds that a driver with a certain type of distraction would be involved in one of the three most common crash types: rear-end, angular, and single-vehicle crashes. Furthermore, ordered logistic modeling was used to analyze the crash data to identify the odds of more severe injuries for teenage and young-adult distracted drivers and their passengers involved in crashes. Survey data was used to develop a structural equation model (SEM) to define the relationship among young drivers’ characteristics (e.g., participants’ socioeconomic and demographic status), attitudes, and behaviors associated with distracted driving and cell phone use while driving. Preliminary analysis showed that more than 12% of the total young drivers’ crashes were distraction-affected crashes. According to the multinomial logit model results, most distraction types for teenage and young-adult drivers are related to rear-end or angular collisions. However, when distracted by cell phones at night, teenage drivers had a greater probability of being involved in single-vehicle crashes. In addition, when teenage drivers drove with their peers as front-seat passengers and were distracted in/on vehicle or by other electronic devices, they were more likely to be involved in single-vehicle crashes. Young-adult drivers distracted in/on vehicle or by cell phones under different conditions such as while driving old or sport utility vehicles, on curved roads, or at intersections, they were more likely to be involved in single-vehicle or angular crashes. Whereas, when they were inattentive during the weekend, rear-end collisions were the most likely collision type. According to the results of the ordered logistic model, teenage and young-adult drivers were more likely to be severely injured in cell phone-related crashes. More specifically, female teenage drivers had a greater probability of being severely injured than male teenage drivers when they were distracted by a cell phone, inside the vehicle, or were inattentive. Young-adult drivers that were distracted on road construction work zones by a cell phone or inside the vehicle, they and their passengers had a greater likelihood of sustaining a severe injury. The SEM results revealed that teenage drivers are more prone than young-adult drivers to drive while distracted and are less likely to support the Kansas laws that ban cell phone use while driving. Also, the model results showed that young drivers who have been involved in crashes or near-crashes during the previous year are more likely to drive while distracted. These results indicate that distractions create threats to the lives of young Kansas drivers, their passengers, and other road users.

De meados da década de 80 até a atualidade as atividades básicas que fazem parte da logística deixaram de ser somente consolidadoras de uma relação de compra e venda, e passaram a ter uma importância estratégica bastante grande em busca de uma maior vantagem competitiva. Esta nova importância para a logística surgiu com a abertura econômica e o acirramento da competitividade mundial. Assim, empresas se especializaram em projetar, implantar e gerenciar as atividades de logística para outras empresas (Operadores Logísticos). A tomada de decisão entre realizar as atividades logísticas através de competência interna da empresa ou repassa-las aos operadores logísticos se tornou mais freqüente nos dias de hoje. O trabalho propõe um procedimento de auxílio a tomada de decisão para empresas em fase de análise da viabilidade da utilização de operadores logísticos. Por fim o procedimento é testado no campo com dados reais uma empresa de grande porte. / From the middle of 80\'s until today, the basic logistic activities are not only to consolidate buy and sales relationship, these activities became important in strategic planning, being important to reach new markets. This new logistic importance started with openning of Brazilian economy and with the increase in world competitiveness. For this reason, enterprises improvement the logistic activities techniques, as project, implementation an management and starting to execute these activities to another enterprises with do not have logistic as core competence, these enterprises are called Third Party Logistic Provider. The decision make between insourcing or outsourcing logistic activities became more frequently nowadays. This thesis propose a procedure to help enterprises in the viability analysis phase to use third party logistic provider in its supply chain. In the end the procedure is tested in a global company with real data.

Hurricanes have been considered one of the most costly disasters in United State, which lead to both economic loss and human fatalities. Therefore, understanding the characteristics of those who evacuated and of those who did not evacuate have been principal focus of some previous researches related to hurricane evacuation behavior. This research presents two sets of decision-making models for analyzing hurricane evacuation behavior, using two statistical methods: standard logistic model and mixed logistic model.The receipt of evacuation order, elevation, expenditure, the presence of children and elderly people, ownership of a house, and receipt of hurricane warning are found to be extremely important in evacuation decision making. When the mixed logistic model is applied, the rate of concern about hurricane threat is assumed to be random according to normal distribution. Mixed logistic models which account for the heterogeneity of household responses are found to perform better than standard logistic model.

The diploma thesis deals with the hospital logistics and current utilization of the logistic methods and principles by the regional hospital in Jičín. The aim of the thesis is to describe and analyse of current form of logistic system of the hospital and logistic processes in connection with the ensurance of material flows; to make the questionnaire; to identify the problems and to suggest solutions of optimalization of logistic processes and logistic chains that can lead to effective logistic system of the hospital.

The aim of this work is to decide the real usage of logistic regression in the market research tasks respecting the needs of final users of research results. The main argument for the final decision is the comparison of its output to the output of an alternative classification method used in practice -- a classification tree method. The topic is divided into three parts. The first part describes the theoretical framework and approaches linked to logistic regression (chapter 2 and 3). The second part analyses the experience with the usage of logistic regression in Czech market research companies (chapter 4) and the topic is closed by applying the method on real data and comparing the output to the classification tree output (chapter 5 and 6).