A description of direct simulation of crosswind loads caused by critical vortex excitation and the response of the structure to these loads are presented in this paper. Tower-like structures of circular cross-sections are considered. A proposed mathematical model of vortex excitation has been numerically implemented and a selfserving computer program was created for the purpose. This software, cooperating with the FEM system, allows for a simulation of a crosswind load and lateral response in real time, meaning that at each time step of the calculations the load is generated using information regarding displacements seen beforehand. A detailed description of the mathematical model is neglected in this paper, which is focused on numerical simulations. WAWS and AR methods are used in simulations.

The paper aims at comparing forecast ability of VAR/VEC models with a non-changing covariance matrix and two classes of Bayesian Vector Error Correction – Stochastic Volatility (VEC-SV) models, which combine the VEC representation of a VAR structure with stochastic volatility, represented by the Multiplicative Stochastic Factor (MSF) process, the SBEKK form or the MSF-SBEKK specification.

Based on macro-data coming from the Polish economy (time series of unemployment, inflation and interest rates) we evaluate predictive density functions employing of such measures as log predictive density score, continuous rank probability score, energy score, probability integral transform. Each of them takes account of different feature of the obtained predictive density functions.

The problem of optimally controlling a Wiener process until it leaves an interval (a; b) for the first time is considered in the case when the infinitesimal parameters of the process are random. When a = ��1, the exact optimal control is derived by solving the appropriate system of differential equations, whereas a very precise approximate solution in the form of a polynomial is obtained in the two-barrier case.

Usually, cellular networks are modeled by placing each tier (e.g macro, pico and relay nodes) deterministically on a grid. When calculating the metric performances such as coverage probability, these networks are idealized for not considering the interference. Overcoming such limitation by realistic models is much appreciated. This paper considered two- tier twohop cellular network, each tier is consisting of two-hop relay transmission, relay nodes are relaying the message to the users that are in the cell edge. In addition, the locations of the relays, base stations (BSs), and users nodes are modeled as a point process on the plane to study the two hop downlink performance. Then, we obtain a tractable model for the k-coverage probability for the heterogeneous network consisting of the two-tier network. Stochastic geometry and point process theory have deployed to investigate the proposed two-hop scheme. The obtained results demonstrate the effectiveness and analytical tractability to study the heterogeneous performance.

Small construction objects are often built by standard task teams. The problem is, how to allocate these teams to individual works? To solve the problem of allocation three methods have been developed. The first method allows to designate optimal allocation of teams to the individual works in deterministic conditions of implementation. As a criterion of the optimal allocation can be applied: “the minimization of time” or “the minimization of costs” of works execution. The second method has been developed analogously for both criteria but for stochastic conditions and for the stochastic data. The third method allows to appoint a compromise allocation of teams. In this case, the criteria “the minimization of time” and “the minimization of costs” are considered simultaneously. The method can be applied in deterministic or stochastic conditions of works implementation. The solutions of the allocation problems which have been described allow to designate the optimal allocation of task teams and to determine the schedule and cost of works execution.

The paper discusses Bayesian productivity analysis of 27 EU Member States, USA, Japan and Switzerland. Bayesian Stochastic Frontier Analysis and a two-stage structural decomposition of output growth are used to trace sources of output growth. This allows us to separate the impacts of capital accumulation, labour growth, technical progress and technical efficiency change on economic development. Since estimates of the growth components are conditioned upon model parameterisation and the underlying assumptions, a number of possible specifications are considered. The best model for decomposing output growth is chosen based on the highest marginal data density, which is calculated using adjusted harmonic mean estimator.

This article aims at constructing a new method for testing the statistical significance of seasonal fluctuations for non-stationary processes. The constructed test is based on a method of subsampling and on the spectral theory of Almost Periodically Correlated (APC) time series. In the article we consider an equation of a nonstationary process, containing a component which includes seasonal fluctuations and business cycle fluctuations, both described by an almost periodic function. We build subsampling test justifying the significance of frequencies obtained from the Fourier representation of the unconditional expectation of the process.

The empirical usefulness of the constructed test is examined for selected macroeconomic data. The article studies survey indicators of economic climate in industry, retail trade and consumption for European countries.

This paper presents some new results on exogeneity in models with latent variables. The concept of exogeneity is extended to the class of models with latent variables, in which a subset of parameters and latent variables is of interest. Exogeneity is discussed from the Bayesian point of view. We propose sufficient weak and strong exogeneity conditions in the vector error correction model (VECM) with stochastic volatility (SV) disturbances. Finally, an empirical illustration based on the VECM-SV model for the daily growth rates of two main official Polish exchange rates: USD/PLN and EUR/PLN, as well as EUR/USD from the international Forex market is presented. The exogeneity of the EUR/USD rate is examined. The strong exogeneity hypothesis of the EUR/USD rate is not rejected by the data.

The main aim of this paper is to analyse the effect of Common Agricultural Policy (CAP) subsidies on technical efficiency of Polish dairy farms. We have distinguished several types of subsidies and provided an analysis to find out which types are most likely to engender systematic differences in technical efficiency. A balanced panel of microeconomic data on Polish dairy farms over an eight-year period (between 2004 and 2011), taken from the Farm Accountancy Data Network (FADN), is used. The translog production function is estimated by employing the Bayesian approach. The empirical results show that the elasticity of production with respect to livestock is the highest, whereas with respect to feed is the lowest. The mean technical efficiency in the covered period is 83%. The research reveals the negative effect of subsidies on technical efficiency.

This paper provides analyses of the accuracy and convergence time of the PPP method using GPS systems and different IGS products. The official IGS products: Final, Rapid and Ultra Rapid as well as MGEX products calculated by the CODE analysis centres were used. In addition, calculations with weighting function of the observations were carried out, depending on the elevation angle. The best results were obtained for CODE products, with a 5-minute interval precision ephemeris and precise corrections to satellite clocks with a 30-second interval. For these calculations the accuracy of position determination was at the level of 3 cm with a convergence time of 44 min. Final and Rapid products, which were orbit with a 15-minute interval and clock with a 5 minute interval, gave very similar results. The same level of accuracy was obtained for calculations with CODE products, for which both precise ephemeris and precise corrections to satellite clocks with the interval of 5 minutes. For these calculations, the accuracy was 4 cm with the convergence time of 70 min. The worst accuracy was obtained for calculations with Ultra-rapid products, with an interval of 15 minutes. For these calculations, the accuracy was 10 cm with a convergence time of 120 min. The use of the weighting function improved the accuracy of position determination in each case, except for calculations with Ultra-rapid products. The use of this function slightly increased the convergence time, in addition to the CODE calculation, which was reduced to 9 min.

In the paper finite-dimensional time-variable dynamical control systems described by linear stochastic ordinary differential state equations with single time-variable point delay in the control are considered. Using notations, theorems and methods taken directly from deterministic controllability problems necessary and sufficient conditions for different kinds of stochastic relative controllability in a given time interval are formulated and proved. It will be proved that under suitable assumptions relative controllability of a deterministic linear associated dynamical system is equivalent to stochastic relative exact controllability and stochastic relative approximate controllability of the original linear stochastic dynamical system. Some remarks and comments on the existing results for stochastic controllability of linear dynamical systems are also presented.

Seasonality is a function of a time series in which the data experiences regular and predictable

changes that repeat each calendar year. Two-stage stochastic programming model

for real industrial systems at the case of a seasonal demand is presented. Sampling average

approximation (SAA) method was applied to solve a stochastic model which gave a productive

structure for distinguishing and statistically testing a different production plan. Lingo

tool is developed to obtain the optimal solution for the proposed model which is validated

by Math works Matlab. The actual data of the industrial system; from the General Manufacturing

Company, was applied to examine the proposed model. Seasonal future demand

is then estimated using the multiplicative seasonal method, the effect of seasonality was

presented and discussed. One might say that the proposed model is viewed as a moderately

accurate tool for industrial systems in case of seasonal demand. The current research may

be considered a significant tool in case of seasonal demand. To illustrate the applicability of

the proposed model a numerical example is solved using the proposed technique. ANOVA

analysis is applied using MINITAB 17 statistical software to validate the obtained results.

The draw theory is the foundation for decreasing ore loss and dilution indices while extracting deposits from mines. Therefore, research on draw theory is of great significance to optimally guide the draw control and improve the economy efficiency of mines. The laboratory scaled physical draw experiments under inclined wall condition conducted showed that a new way was proposed to investigate the flow zone of granular materials. The flow zone was simply divided into two parts with respect to the demarcation point of the flow axis. Based on the stochastic medium draw theory, theoretical movement formulas were derived to define the gravity flow of fragmented rocks in these two parts. The ore body with 55° dip and 10 m width was taken as an example, the particle flow parameters were fitted, and the corresponding theoretical shape of the draw body was sketched based on the derived equation of draw-body shape. The comparison of experimental and theoretical shapes of the draw body confirmed that they coincided with each other; hence, the reliability of the derived equation of particle motion was validated.

A Bayesian stochastic volatility model with a leverage effect, normal errors and jump component with the double exponential distribution of a jump value is proposed. The ready to use Gibbs sampler is presented, which enables one to conduct statistical inference. In the empirical study, the SVLEDEJ model is applied to model logarithmic growth rates of one month forward gas prices. The results reveal an important role of both jump and stochastic volatility components.