Type space on a purely measurable parameter space

Several game theoretical topics require the analysis of hierarchical beliefs, particularly in incomplete information situations. For the problem of incomplete information, Hars´anyi suggested the concept of the type space. Later Mertens & Zamir gave a construction of such a type space under topological assumptions imposed on the parameter space. The topological assumptions were weakened by Heifetz, and by Brandenburger & Dekel. In this paper we show that at very natural assumptions upon the structure of the beliefs, the universal type space does exist. We construct a universal type space, which employs purely a measurable parameter space structure.

A diszkrét kiválasztási modell becslése Cox-regresszióval (Parameter estimation for multinomial discrete choice model using Cox-regression)

Considering the so-called "multinomial discrete choice" model the focus of this paper is on the estimation problem of the parameters. Especially, the basic question arises how to carry out the point and interval estimation of the parameters when the model is mixed i.e. includes both individual and choice-specific explanatory variables while a standard MDC computer program is not available for use. The basic idea behind the solution is the use of the Cox-proportional hazards method of survival analysis which is available in any standard statistical package and provided a data structure satisfying certain special requirements it yields the MDC solutions desired. The paper describes the features of the data set to be analysed.

Környezeti kockázatok felmérése. Paraméterek bizonytalanságának hatása a kockázatkezelési döntéshozatalra = Assessment of environmental risks – effects of parameter uncertainty to the risk management decisions

A környezeti kockázatok megfelelő felmérése és kezelése napjaink egyik legfontosabb kérdése, nemcsak a szakmai, hanem a széles értelemben vett közvélemény számára. A szerző cikkében azt vizsgálja, hogy a környezeti kockázatok felmérésének milyen megközelítései vannak. Kulcskérdésként pedig arra koncentrál, hogy a kockázatkezelési döntéseket hogyan befolyásolja a becslések bizonytalansága. Először a környezeti kockázat definícióját adja meg, majd azt mutatja be, hogy a környezeti kockázatok kezelésére vonatkozó megközelítések milyen párhuzamban állnak a pénzügyi rendszerrel, mint komplex rendszerre vonatkozó megközelítésekkel. Végül a jelenleg legnagyobb kockázatoknak tartott környezeti kockázatokat ismerteti röviden. A cikk második részében kockázatkezelési alternatívákat mutat be, és azt, hogy a kockázatkezelési lépések kiválasztását befolyásolja a bizonytalanság. Ezt illusztrálandó Brouwer-Blois (2008) modelljét használva a soklépéses szimulációt és alternatív döntési kritériumot – a kritikus (extrém) költség-hatás mutatót – alkalmazza. _____________ Adequate assessment and management of environmental risks is a key question nowadays also for professional experts and also for the overall public. In this article the author examines the different approaches concerning environmental risks. He concentrates as a key question the influence on risk management decisions of uncertainties raised by our estimations. First he analyses the definition of environmental risks, and he shows the similarities and differences between approaches concerning environmental risks and risks threatening financial system, and finally he gives short overview on the most current environmental risks. In the second part of the paper he presents risk management alternatives and analyses the influential power of uncertainty on risk management decisions. In order to illustrate this phenomenon the author applies the model of Brouwer-Blois (2008) with multistep simulation and an alternative decisive criterion, the ranking based on critical (extreme) cost to effect measure.

Magyarország hét régiójának új gazdaságföldrajzi modellje – paraméterbecslés (The new economic-geography model of Hungary's seven regions - a parameter estimate)

Az új gazdaságföldrajz – amely napjaink egy igen népszerű közgazdaságtani tudományága – modelljének majdnem minden paramétere előállítható közvetlenül külső adatok segítségével. A helyettesítési rugalmassághoz azonban más módszerre van szükség. Puga [1999] által felvázolt új gazdaságföldrajzi modellt követve, egy regressziós egyenlettel megbecsülhetővé válik a kívánt paraméter, amit Magyarország hét régiójára vonatkozó béregyenlet becsléséből nyertünk. A helyettesítési rugalmasság értéke eltér a szakirodalomhoz képest, aminek magyarázata Magyarország fejlettségi szintjével állhat összefüggésben. ____ The model of the new economic geography - very popular material for economic study these days - allows almost every parameter to be presented directly with the aid of outside data. However, another method is required for substitution flexibility. With the new economic-geography model devised by Puga [1999], a regression equation allows an estimate to be made for the desired parameter, which yielded the wage equation for the six regions of Hungary. The value for substitution flexibility differs from that of the literature, the explanation for which may lie in Hungary's level of development.

Parameter design considerations in precision engineering

Parameter design is an experimental design and analysis methodology for developing robust processes and products. Robustness implies insensitivity to noise disturbances. Subtle experimental realities, such as the joint effect of process knowledge and analysis methodology, may affect the effectiveness of parameter design in precision engineering; where the objective is to detect minute variation in product and process performance. In this thesis, approaches to statistical forced-noise design and analysis methodologies were investigated with respect to detecting performance variations. Given a low degree of process knowledge, Taguchi's methodology of signal-to-noise ratio analysis was found to be more suitable in detecting minute performance variations than the classical approach based on polynomial decomposition. Comparison of inner-array noise (IAN) and outer-array noise (OAN) structuring approaches showed that OAN is a more efficient design for precision engineering. ^

Improving the predictability of time series by chaotic parameter estimation

Limited literature regarding parameter estimation of dynamic systems has been identified as the central-most reason for not having parametric bounds in chaotic time series. However, literature suggests that a chaotic system displays a sensitive dependence on initial conditions, and our study reveals that the behavior of chaotic system: is also sensitive to changes in parameter values. Therefore, parameter estimation technique could make it possible to establish parametric bounds on a nonlinear dynamic system underlying a given time series, which in turn can improve predictability. By extracting the relationship between parametric bounds and predictability, we implemented chaos-based models for improving prediction in time series. ^ This study describes work done to establish bounds on a set of unknown parameters. Our research results reveal that by establishing parametric bounds, it is possible to improve the predictability of any time series, although the dynamics or the mathematical model of that series is not known apriori. In our attempt to improve the predictability of various time series, we have established the bounds for a set of unknown parameters. These are: (i) the embedding dimension to unfold a set of observation in the phase space, (ii) the time delay to use for a series, (iii) the number of neighborhood points to use for avoiding detection of false neighborhood and, (iv) the local polynomial to build numerical interpolation functions from one region to another. Using these bounds, we are able to get better predictability in chaotic time series than previously reported. In addition, the developments of this dissertation can establish a theoretical framework to investigate predictability in time series from the system-dynamics point of view. ^ In closing, our procedure significantly reduces the computer resource usage, as the search method is refined and efficient. Finally, the uniqueness of our method lies in its ability to extract chaotic dynamics inherent in non-linear time series by observing its values. ^

Reduced-parameter model of head-related transfer functions for synthesized spatial audio

Digital systems can generate left and right audio channels that create the effect of virtual sound source placement (spatialization) by processing an audio signal through pairs of Head-Related Transfer Functions (HRTFs) or, equivalently, Head-Related Impulse Responses (HRIRs). The spatialization effect is better when individually-measured HRTFs or HRIRs are used than when generic ones (e.g., from a mannequin) are used. However, the measurement process is not available to the majority of users. There is ongoing interest to find mechanisms to customize HRTFs or HRIRs to a specific user, in order to achieve an improved spatialization effect for that subject. Unfortunately, the current models used for HRTFs and HRIRs contain over a hundred parameters and none of those parameters can be easily related to the characteristics of the subject. This dissertation proposes an alternative model for the representation of HRTFs, which contains at most 30 parameters, all of which have a defined functional significance. It also presents methods to obtain the value of parameters in the model to make it approximately equivalent to an individually-measured HRTF. This conversion is achieved by the systematic deconstruction of HRIR sequences through an augmented version of the Hankel Total Least Squares (HTLS) decomposition approach. An average 95% match (fit) was observed between the original HRIRs and those re-constructed from the Damped and Delayed Sinusoids (DDSs) found by the decomposition process, for ipsilateral source locations. The dissertation also introduces and evaluates an HRIR customization procedure, based on a multilinear model implemented through a 3-mode tensor, for mapping of anatomical data from the subjects to the HRIR sequences at different sound source locations. This model uses the Higher-Order Singular Value Decomposition (HOSVD) method to represent the HRIRs and is capable of generating customized HRIRs from easily attainable anatomical measurements of a new intended user of the system. Listening tests were performed to compare the spatialization performance of customized, generic and individually-measured HRIRs when they are used for synthesized spatial audio. Statistical analysis of the results confirms that the type of HRIRs used for spatialization is a significant factor in the spatialization success, with the customized HRIRs yielding better results than generic HRIRs.

Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

Interval and Point Estimators for the Location Parameter of the Three-Parameter Lognormal Distribution

The three-parameter lognormal distribution is the extension of the two-parameter lognormal distribution to meet the need of the biological, sociological, and other fields. Numerous research papers have been published for the parameter estimation problems for the lognormal distributions. The inclusion of the location parameter brings in some technical difficulties for the parameter estimation problems, especially for the interval estimation. This paper proposes a method for constructing exact confidence intervals and exact upper confidence limits for the location parameter of the three-parameter lognormal distribution. The point estimation problem is discussed as well. The performance of the point estimator is compared with the maximum likelihood estimator, which is widely used in practice. Simulation result shows that the proposed method is less biased in estimating the location parameter. The large sample size case is discussed in the paper.

Bulk sediment parameter of three sediment cores from permafrost lowlands, Alaska Arctic Coastal Plain

Arctic lowland landscapes have been modified by thermokarst lake processes throughout the Holocene. Thermokarst lakes form as a result of ice-rich permafrost degradation and they may expand over time through thermal and mechanical shoreline erosion. We studied proximal and distal sedimentary records from a thermokarst lake located on the Arctic Coastal Plain of northern Alaska to reconstruct the impact of catchment dynamics and morphology on the lacustrine depositional environment and to quantify carbon accumulation in thermokarst lake sediments. Short cores were collected for analysis of pollen, sedimentological and geochemical proxies. Radiocarbon and Pb/Cs dating, as well as extrapolation of measured historic lake expansion rates, were applied to estimate a minimum lake age of ~ 1,400 calendar years BP. The pollen record is in agreement with the young lake age as it does not include evidence of the "alder high" that occurred in the region ~ 4.0 cal ka BP. The lake most likely initiated from a remnant pond in a drained thermokarst lake basin (DTLB) and deepened rapidly as evidenced by accumulation of laminated sediments. Increasing oxygenation of the water column as shown by higher Fe/Ti and Fe/S ratios in the sediment indicate shifts in ice regime with increasing water depth. More recently, the sediment source changed as the thermokarst lake expanded through lateral permafrost degradation, alternating from redeposited DTLB sediments, to increased amounts of sediment from eroding, older upland deposits, followed by a more balanced combination of both DTLB and upland sources. The characterizing shifts in sediment sources and depositional regimes in expanding thermokarst lakes were therefore archived in the thermokarst lake sedimentary record. This study also highlights the potential for Arctic lakes to recycle old carbon from thawing permafrost and thermokarst processes.