Bootstrap Monte Carlo Simulation Research Articles

Sub-damped Lyman α systems in the XQ-100 survey – I. Identification and contribution to the cosmological H i budget

Abstract Sub-damped Lyman α systems (subDLAs; H i column densities of 19.0 ≤ logN(H i) < 20.3) are rarely included in the cosmic H i census performed at redshifts zabs ≳ 1.5, yet are expected to contribute significantly to the overall H i mass budget of the Universe. In this paper, we present a blindly selected sample of 155 subDLAs found along 100 quasar sightlines (with a redshift path-length ΔX = 475) in the XQ-100 legacy survey to investigate the contribution of subDLAs to the H i mass density of the Universe. The impact of X-Shooter’s spectral resolution on Ly α absorber identification is evaluated, and found to be sufficient for reliably finding absorbers down to a column density of logN(H i) ≥ 18.9. We compared the implications of searching for subDLAs solely using H i absorption versus the use of metal lines to confirm the identification, and found that metal-selection techniques would have missed 75 subDLAs. Using a bootstrap Monte Carlo simulation, we computed the column density distribution function (f(N, X)) and the cosmological H i mass density ($\Omega _{\rm H\,{\small I}}$) of subDLAs and compared with our previous work based on the XQ-100 damped Lyman α systems. We do not find any significant redshift evolution in f(N, X) or $\Omega _{\rm H\,{\small I}}$ for subDLAs. However, subDLAs contribute 10–20 per cent of the total $\Omega _{\rm H\,{\small I}}$ measured at redshifts 2 < z < 5, and thus have a small but significant contribution to the H i budget of the Universe.

Bootstrap Monte Carlo Simulation of Reliability and Confidence Level with Periodical Maintenance

The bootstrap Monte Carlo simulation (BMCS) is presented as a new method for determining the reliability and confidence level of a general technical system with periodical maintenance. The method can be implemented on the basis of pure samples of failure times or of the mean value distributions in combination with the corresponding sample size of reliability. The BMCS does not require special distribution types and facilitates both the prediction and demonstration of reliability.

Interaction between finance, tourism and advertising: evidence from Turkey

The purpose – It is important to emphasize that a research on relationship between tourism, finance and advertisement is very rare. The aim of this study is investigation of causal relationship between these variables. Design – In this paper, the relationship between tourism revenues and variables like tourism index of Istanbul Stock Market (BIST) & tourism advertising durations which have not been used previously in the literature was investigated for Turkey. Methodology – To attain more useful and accurate findings, bootstrap granger causality test of Hacker Hatemi-J (2010) was used which can determine critical values by bootstrap simulation method in order to reduce the possibility of potential non-normal dispersion of errors. Approach – In purpose of contribution to literature, monthly data in the period spanning from Aug 2004 till Dec 2012 and bootstrap causality method were used, thus new findings were tried to be found Findings – While traditional Toda-Yamamoto (1996) causality test has been determined no causality between these three variables, there was observed one-way causality from tourism index to tourism advertisements by the aid of more advanced Hacker Hatemi-J (2010) causality test. As a result of study, one-way causality from tourism indices, which is an important indicator representing all positive and negative performances of businesses in tourism sector, to advertising durations was detected. The originality of this research – In this study, unlike others, variables like tourism index which represents businesses in tourism sector and tourism advertising durations were used. The relationship between tourism index, tourism advertisings and tourism revenue was examined with Hacker Hatemi-J (2010) bootstrap causality test which obtains critical values by bootstrap monte-carlo simulation. By this new test, more reliable and advanced results have been obtained. As a result, tourism index which can be considered as a fundamental performance scale of tourism sector has a vital effect on tourism advertisement.

Evaluation of the detection of glass contamination in horticultural peat and compost using microwave reflection by Monte Carlo simulation

Contamination of bagged peat by glass fragments needs to be detected before point-of-sale to protect users from cut injuries. In order to evaluate the potential for designing a microwave detection system, a bootstrap Monte Carlo simulation of transverse-electric plane microwave reflection from glass-contaminated random flat strata of wet peat and compost was carried out. Measured complex permittivity data for peat, compost, and soda-lime glass were used in conjunction with calculated water vapour pressure for the simulation. The simulation was for polyethylene bag material on both faces of randomly generated peat (or compost) strata on a supporting stainless-steel platform. This was to simulate bagged peat or compost. Generally, a dual-frequency analysis resulted in more consistent discrimination between pure and contaminated peat and compost samples than single-frequency phase-shift or amplitude ratio. Best performance was obtained with dual-frequency corrected phase difference for peat (difference=0.15 rad, p p

Bootstrap Monte Carlo simulation study of sugar industry in Bangladesh

Bootstrap is a powerful technique that can often be used when people do not know enough about the underlying process, or the nature of measurement errors, to do a credible Monte Carlo simulation. Sugar industry is an agro-based industry in Bangladesh. Sales of sugar are one of the important factors for the productivity of the sugar mills. The sales and quality demanded of sugar are determined by its price, the price relative products, consumer income, the size of the population, and tests and preferences. The sales are affected by the usual factors explaining demand. In present paper focus on a more restricted question: what are the mean sales of sugar by the industry, different sugar mills, per year? The distribution of annual sales of sugar per Taka fixed assets is normal for three sugar mills (SSM, JSM and TSM). The distribution of annual sales per employment is also normal for six sugar mills (SSM, RGSM, C&CO., JSM, RSM, NBSM and industry average (16 SM). Similarly, the distribution of annual sales of sugar in relation to production of sugar is also normal for only three sugar mills (RGSM, JSM and NBSM). The fact from Monte Carlo simulation results that the least squares estimate varies from sample to sample reflects the fact that the least square estimator for Models-1, 2 and 3 are a random variable, it has a probability or sampling distribution, which is normal. For a large class of problems, however, the bootstrap does yield easy, very quick, Monte Carlo estimates of the errors in an estimated parameter set.