Kriging techniques are regression methods used for evaluation of continuous spatial processes. If the covariance structure of process is unknown, then it's necessary to estimate it from the data. The first part of this Master's thesis is devoted to description the kriging method and to estimate of a variogram fuction, which describes the covariance structure of considered process. The second part includes the implementation of kriging method in MATLAB for simulated and real data.

MENVSC / Department of Geography and Geo-Information Sciences

The population in the Central Bohemian manor of Škvorec from the middle of the 18th to the end of the 19th century. Abstract The aim of this study is to analyze the reproductive behavior (nuptiality, natality, female and male fertility, mortality) and the social structure of selected groups of the population of the Škvorec manor in the 18th and 19th century. The Škvorec manor which is located in the territory of today's Central Bohemia was an important agricultural area in given period. The complete nominal excerpts from parish registers were used to find numbers of all births, marriages and deaths. In addition to traditional historical- demography methods (especially the family reconstitution method and subsequent calculation of demographic indicators from family leaves), advanced statistical methods (survival analysis, Cox regression model) were also used for data analysis. These approaches are new in Czech historical demography and bring many advantages, which are presented in the work. The natural change of population development at the manor is compared with the Czech lands as a whole and in more detail with selected rural and urban localities. The results mostly correspond with the population development which was observed in the Czech lands. The number of inhabitants of the manor in the years...

In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with severities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.

Fastigheter beläggs med olika pris beroende på en mängd olika faktorer. Denna uppsats syftartill att analysera hur några av dessa prispåverkande faktorer och hur de förhåller sig tillsmåhusfastigheter i Helsingborg. Utöver detta kommer även en faktor, kallad njutningsfaktorn,analyseras för att försöka fastställa hur individers preferenser påverkar värdet. Analysenbaseras på statistiska underlag som kommer att behandlas med hjälp av den hedoniskaprismodellen. Bid-rent modellen kommer att appliceras på staden Helsingborg och dessområden för att skapa en bild av lägesfaktorn. En fördjupning i psykologi och urban ekonomikommer att bidra till analysen av både fysiska och psykologiska aspekter. Resultaten vi fåttfram är att det inte enbart kan tas hänsyn till fysiska aspekter i förhållande till pris på fastigheterutan det är även viktigt att behandla de psykologiska aspekterna för varje individ. / Different real estates have different value, depending upon several factors. This essay aims toanalyse some of these values bearing factors and how they relate to properties in Helsingborg.Beside these factors another factor, called the pleasure factor, will be analysed in an attempt todetermine how individual preferences affects the value. The analysis will be based on statisticmaterial that will be processed with the hedonic price model. The bid-rent model will beapplied to the city and to its areas, to help create an understanding of the location factor. Adepression of psychology and urban economics will contribute to both physical andpsychological aspects of the analysis. The results that will be presented will show that inconsideration to price we can't just tend to the physical aspects but must also consider thepsychological aspects for each individual.

This dissertation is focused on proposal for simplified data analyze approach for sport-car vehicle dynamic evaluation with relationship to possibility for qualified estimation of set-up parameters influence for overall vehicle performance. In common practice can be usual overlapping effect caused by concurrent changes of car setup elements if performed in the same moment with resulting in not correct or hardly definable process determination for evaluation and decision about next steps in car development. For analyze of these multidimensional data is then chosen process with approach by Linear Regression Model (LRM). In dissertation is proposed basic philosophy with concern on specificity of car vehicle dynamics, performed experiment with defined inputs including analyze and interpretation method of obtained outputs. This methodic take into account also possibility for general application of multidimensional data analyses not only in motorsport, but as well for dynamic behavior diagnostics of technical systems where finding of optimal running condition depends on multi-parametric setup whose combination must reflect often changes of outer conditions too.

Manufacturers of saw chains continuously strive to increase the performance of their products by reducing cutting times and minimising the energy consumption required for cutting. However, the evaluation process through testing is problematic as several uncontrollable factors impact the results. A large source of uncontrollable factors is the material used as a workpiece. Historically, wood has been used as a workpiece material since it is often what the end user will use it for. As a natural material, each stem contains a unique structure and can have a high variation in mechanical properties. Consequently, the analysis of older cutting efficiency is problematic since the result is linked to the specific stem being sawn, which is destroyed during the testing process. The current work aims to improve the repeatability of these tests by increasing the understanding of which material characteristics and material properties impact the variance during cutting efficiency measurements. An experiment was performed using pine as a workpiece material. It was found that the wood structure, density and hardness or moisture content could explain approximately 80% of the variation in the final tests. A more homogeneous material polyethylene was used to explore if a decrease in variation within these factors resulted in lower variance between cutting efficiency results. The variance between results was found to be lowest in pine when knots were excluded. The variance in polyethylene was slightly higher but showed promising evidence for being a suitable alternative material for long-term testing.

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Det har länge pågått diskussioner om hur förhållandet mellan inflation och ekonomisk tillväxt ser ut och vilken påverkan, inflation har på ekonomisk tillväxt. I denna uppsats analyseras relationen mellan inflation och ekonomisk tillväxt inom OECD-länder samt Subsahariska Afrika med hjälp av paneldata från tidperioden 2002–2021. Studien använder BNP per capita tillväxt som beroende variabel samt sju oberoende variabler (inflation, initial BNP per capita, befolkningstillväxt, handel, investeringar, statliga utgifter och finansiellt djup) för att utforma en regressionsmodell.  Regressionsmodellen genomfördes med fixed effects för att kontrollera icke observerade länder med specifika egenskaper och tidsrelaterade chocker. Resultaten i studien visar att det finns ett negativ samband mellan inflation och ekonomisk tillväxt som är statistik signifikant. / There have long been discussions about what the relationship between inflation and economic growth looks like and what impact inflation have on economic growth. In this essay, the relationship between inflation and economic growth is analysed within OECD countries and Sub-saharan Africa in the time period 2002 – 2021 using paneldata. The thesis uses GDP per capita growth as the dependent variable as well as seven independent variables (inflation, initial GDP per capita, population growth, trade, investment, government expenditures and financial depth) to design a regression model. The regression is carried out with fixed effects to control for unobserved countries specifics charactheritstics and time related shocks . The results in the study shows that there exist a negativ relationship between inflation and economic growth which is statistical significant.

<p>  </p> <p>During the construction of a bridge, more specifically a concrete bridge deck, there are sometimes defects in materials or workmanship, resulting in what is called a construction defect. These defects can have a large impact on the lifecycle performance of the bridge deck, potentially leading to more preventative and reactive maintenance actions over time and thus a larger monetary investment by the bridge owner. Bridge asset managers utilize prediction software to inform their annual budgetary needs, however this prediction software traditionally relies only on historical condition rating data for its predictions. When attempting to understand how deterioration of a bridge deck changes with the influence of construction defects, utilizing the current prediction software is not appropriate as there is not enough historical data available to ensure accuracy of the prediction. There are numerical modeling approaches available that capture the internal physical and chemical deterioration processes, and these models can account for the change in deterioration when construction defects are present. There are also numerical models available that capture the effect of external factors that may be affecting the deterioration patterns of the bridge deck, in parallel to the internal processes. The goal of this study is to combine a mechanistic model capturing the internal physical and chemical processes associated with deterioration of a concrete bridge deck, with a model that is built strictly from historical condition rating data, in order to predict the changes in condition rating prediction of a bridge deck for a standard construction case versus a substandard construction case. Being able to measure the change in prediction of deterioration when construction defects are present then allows for quantifying the additional cost that would be required to maintain the defective bridge deck which is also presented. </p>