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Recursive estimation is an essential procedure in econometrics which appears in many applications when the underlying dataset or model is modi ed. Data arrive consecutively and thus already estimated models will have to be updated with new available information. Moreover, in many cases, data will have to be deleted from a model in order to remove their effect, either because they are old (obsolete) or because they have been detected to be outliers or extreme values and further investigation is required. The aim of this thesis is to develop numerically stable and computationally efficient methods for the recursive estimation of large-scale linear econometric models. Estimation of multivariate linear models is a computationally costly procedure even for moderate-sized models. In particular, when the model needs to be estimated recursively, its estimation will be even more computationally demanding. Moreover, conventional methods yield often, misleading results. The aim is to derive new methods which effectively utilise previous computations, in order to reduce the high computational cost, and which provide accurate results as well. Novel numerical methods for the recursive estimation of the general linear, the seemingly unrelated regressions, the simultaneous equations, the univariate and multivariate timevarying parameters models are developed. The proposed methods are based on numerically stable strategies which provide accurate and precise results. Moreover, the new methods estimate the unknown parameters of the modi ed model even when the variance covariance matrix is singular.

Panel data analysis has become an important tool in applied econometrics and the respective statistical techniques are well described in several recent textbooks. However, for an analyst using these methods there remains the task of choosing a reasonable model for the behavior of the panel data. Of special importance is the choice between so-called fixed and random coefficient models. This choice can have a crucial effect on the interpretation of the analyzed phenomenon, which is demonstrated by an application on research and development spillover. (author's abstract) / Series: Forschungsberichte / Institut für Statistik

Does an increase of elderly employment cause a decline in youth employment? A simplified view of a demand driven economy would give a positive answer to this question. Econometric studies based on a single equation approach deliver little support for this belief. However, these studies typically suffer from identification problems to which no attention is paid in most cases. We therefore use a general equilibrium framework when trying to quantify these effects. Using yearly and quarterly Austrian labor and gdp data, we estimate two model variants by Bayesian methods: a) a standard equilibrium model where the degree of complementarity between old, young and primary labor is crucial for the sign and strength of the relevant effects and b) a simple, solely demand driven model which always leads to a crowding out of young through an increase in employment of the old. It turned out that the demand driven model is inferior in fitting the data compared to the standard model. Further, the degree of complementarity is estimated to be strong enough to lead to a small positive effect of elderly employment on youth employment. (authors' abstract) / Series: Department of Economics Working Paper Series

This thesis deals with rotation estimation of 3D model of human jaw. It describes and compares methods for direct analysis od 3D models as well as method to analyze model using rasterization. To evaluate perfomance of proposed method, a metric that computes number of cases when prediction was less than 30° from ground truth is used. Proposed method that uses rasterization, takes  three x-ray views of model as an input and processes it with convolutional network. It achieves best preformance, 99% with described metric. Method to directly analyze polygonal model as a sequence uses attention mechanism to do so and was inspired by transformer architecture. A special pooling function was proposed for this network that decreases memory requirements of the network. This method achieves 88%, but does not use rasterization and can process polygonal model directly. It is not as good as rasterization method with x-ray display, byt it is better than rasterization method with model not rendered as x-ray.  The last method uses graph representation of mesh. Graph network had problems with overfitting, that is why it did not get good results and I think this method is not very suitable for analyzing plygonal model.

Tinklalapis turi didelę įtaką komerciniam įmonės įvaizdžiui. Projektuojant tinklapį tikimasi, jog jis pagerins įmonės ir kliento tarpusavio supratimą. Magistro baigiamojo darbo tema yra labai aktuali, kadangi internetas yra viena populiariausių ir sparčiausiai plėtojamų praktinio kompiuterių panaudojimo sričių, kuri atveria neribotas informacijos paieškos, savišvietos, bendravimo ir naujų veiklos rūšių paieškos galimybes. Tokių paslaugų šiandien daugumai interneto vartotojų nebepakanka. Pageidaujama ne tiktai naudotis internete esančiais duomenimis, bet ir patiems pateikti savo turimą informaciją tinklalapio pagalba. Tačiau tam, kad pateikti informaciją tinkle, reikia įvairiais lygmenimis bei aspektais išnagrinėti tinklalapio efektyvumą. Tyrimo problematika slypi tame, kad yra randama labai mažai tyrimų ir medžiagos apie tinklalapio efektyvumo vertinimo modelius. Dažniausiai yra apsiribojama išvadomis, todėl pastebimas fragmentiškumas, trūksta rezultatų sujungimo į vieną sistemą. Tai leidžia tvirtinti, kad teorija ir empiriniu tyrimu pagrįstos tinklalapio efektyvumo vertinimo modelio studijos yra aktualios bei savalaikės. Darbo pabaigoje, remiantis teorinėmis studijomis bei empiriniu tyrimu bus sukurtas tinklalapio efektyvumo vertinimo modelis, kuris padės svetainės projektuotojams lengviau suprasti svarbiausius tinklalapio elementus. Darbo objektas yra internetinės svetainės bei jų efektyvumo vertinimo modeliai. Tyrimo tikslas yra atlikus svetainių efektyvumo vertinimo... [toliau žr. visą tekstą] / Website has a significant impact on the company's commercial image. It is expected that the design of a website will improve the company’s and customer’s mutual understanding. Master's final paper topic is very relevant, because the Internet is one of the most popular and fastest growing areas of the practical use of computers, which opens unlimited information search engines, self-education, communication and new activities search options. Such services for the majority of Internet users are no longer adequate today. It is desired not only to use the Internet data, but also to provide its information with the site assistance. However, in order to provide the information in the network, the different levels and aspects of the site's performance analysed. The problem of the research is that only the very little research and materials on site the effectiveness of the models can be found. It is usually confined to the findings, therefore the fragmentation and lack of results placed together in one system is observed. This suggests that the theory and the model studies based on the site the effectiveness empirical researches are relevant and timely. At the end of the paper on the basis of theoretical studies and empirical research the site the effectiveness of the model will be created, which will help for the web site designers to understand the key elements of the site easier. The paper subject is the internet sites and evaluation of their effectiveness models. The purpose of... [to full text]

Forecasting is an important analysis task and there is a need of integrating time series models and estimation methods in database systems. The main issue is the computationally expensive maintenance of model parameters when new data is inserted. In this paper, we examine how an important class of time series models, the AutoRegressive Integrated Moving Average (ARIMA) models, can be maintained with respect to inserts. Therefore, we propose a novel approach, on-demand estimation, for the efficient maintenance of maximum likelihood estimates from numerically implemented estimators. We present an extensive experimental evaluation on both real and synthetic data, which shows that our approach yields a substantial speedup while sacrificing only a limited amount of predictive accuracy.