Classical Regression Analysis Research Articles

Bayesian model averaging for the prediction of water main failure for small to large Canadian municipalities

Water utilities often rely on water main failure prediction models for developing preventive or proactive repair and replacement action programs. Due to inherent uncertainties in modeling, it is challenging to understand the water main failure processes and to predict the failure effectively. In this study, Bayesian model averaging (BMA) method is presented to identify the influential covariates and to predict the failure rates of water mains considering model uncertainties. To accredit the proposed model, it is implemented to predict the failure of pipes of the water distribution network of the City of Kelowna, BC and Greater Vernon Water, BC, Canada. Results indicate that the proposed BMA approach captures the effect of the potential explanatory variables more effectively through the posterior probabilities in contrast to that of the p-value given by the classical regression analysis. Moreover, BMA approach performs better compared to classical regression analysis when limited pipe failure data are available.

Bathymetric Mapping of Bhopal City Lower Lake Using IRS-P6: LISS-4 Imagery and Artificial Neural Network Technique

Bathymetry is the studies of underwater depth of a lake or ocean floors. Implementing bathymetric survey is expensive, time consuming and laborious process because it involved in the measurements for depth at point of the large area; it can be reduced using remote sensing techniques. The depth may be determined from the satellite images by establishing the correlation between lake depth and spectral reflectance of the image. Artificial Neural Network (ANN) techniques were used in this context has an advantage of the depth estimation possibility, without refining the depth causing scattering from environmental factors (e.g. bottom material and vegetation). In this research work, investigations have been done on the usage of the empirical models for depth determination and also on the suitability of bands. Least squares regression analysis has failed to produce desired result. ANN based Cascade Forward (CF) back propagation model was tested for single and multi band. Its result showed that using multiband (2&3) has produced comparatively better results than the classical regression analysis. The validation is performed by the various standard statistical tests such as Chi-square, t test and Mean Absolute Percentage error. Linear regression plot of measured depth and actual depth were also plotted.

Satellite remote sensing of grasslands: from observation to management

Aims Grasslands are the world’s most extensive terrestrial ecosystem, and are a major feed source for livestock. Meeting increasing demand for meat and other dairy products in a sustainable manner is a big challenge. At a field scale, Global Positioning System and ground-based sensor technologies provide promising tools for grassland and herd management with high precision. With the growth in availability of spaceborne remote sensing data, it is therefore important to revisit the relevant methods and applications that can exploit this imagery. In this article, we have reviewed the (i) current status of grassland monitoring/observation methods and applications based on satellite remote sensing data, (ii) the technological and methodological developments to retrieve different grassland biophysical parameters and management characteristics (i.e. degradation, grazing intensity) and (iii) identified the key remaining challenges and some new upcoming trends for future development. Important Findings The retrieval of grassland biophysical parameters have evolved in recent years from classical regression analysis to more complex, efficient and robust modeling approaches, driven by satellite data, and are likely to continue to be the most robust method for deriving grassland information, however these require more high quality calibration and validation data. We found that the hypertemporal satellite data are widely used for time series generation, and particularly to overcome cloud contamination issues, but the current low spatial resolution of these instruments precludes their use for field-scale application in many countries. This trend may change with the current rise in launch of satellite constellations, such as RapidEye, Sentinel-2 and even the microsatellites such as those operated by Skybox Imaging. Microwave imagery has not been widely used for grassland applications, and a better understanding of the backscatter behaviour from different phenological stages is needed for more reliable products in cloudy regions. The development of hyperspectral satellite instrumentation and analytical methods will help for more detailed discrimination of habitat types, and the development of tools for greater end-user operation.

PENGARUH BUDAYA ORGANISASI TERHADAP KINERJA KARYAWAN DIREKTORAT PRODUKSI PT DIRGANTARA INDONESIA (PERSERO)

PT Dirgantara Indonesia (Persero) is a manufacture company that provides airplane with component and service. The company has 4.225 employees. Organization culture is one of important thing that have to attentively by a company because this one possible to affect for employee performance. This research aims to determine organization culture and employee performance and the influence of organization culture on employee performance at Production Directorate PT DI. Organizational culture can be seen from the lack of implementation of the company value while the performance can be seen from the production does not reach the target and the grade of the employee's performance is still low. The method which is used in this research is quantitative research methods. Data analysis method which is used in this research are descriptive analysis, a classic assumption test, correlation analysis, regression analysis, and hypothesis testing. The sample in this research 107 respondents. The data collection is used questionnaire with Likert scale. Based on the results of data processing, organization culture currently on good category, it can be seen from innovation and risk taking, attention to detail, outcome orientation, people orientation, team orientation, aggresiveness, and stability. Then, employee performance also currently on good category, it can be seen from quantity the of work, quality of work, knowledge of job, personal qualities, cooperation, dependability, and initiative. The conclusion of this research is there’s an influence of organization culture on employee performance amounted to 28,2% which have positive by value amount 0,531 which means medium and significant value.

A New Data Analysis System to Quantify Associations between Biochemical Parameters of Chronic Kidney Disease-Mineral Bone Disease.

BackgroundIn hemodialysis patients, deviations from KDIGO recommended values of individual parameters, phosphate, calcium or parathyroid hormone (PTH), are associated with increased mortality. However, it is widely accepted that these parameters are not regulated independently of each other and that therapy aimed to correct one parameter often modifies the others. The aim of the present study is to quantify the degree of association between parameters of chronic kidney disease and mineral bone disease (CKD-MBD).MethodsData was extracted from a cohort of 1758 adult HD patients between January 2000 and June 2013 obtaining a total of 46.141 records (10 year follow-up). We used an advanced data analysis system called Random Forest (RF) which is based on self-learning procedure with similar axioms to those utilized for the development of artificial intelligence. This new approach is particularly useful when the variables analyzed are closely dependent to each other.ResultsThe analysis revealed a strong association between PTH and phosphate that was superior to that of PTH and Calcium. The classical linear regression analysis between PTH and phosphate shows a correlation coefficient is 0.27, p<0.001, the possibility to predict PTH changes from phosphate modification is marginal. Alternatively, RF assumes that changes in phosphate will cause modifications in other associated variables (calcium and others) that may also affect PTH values. Using RF the correlation coefficient between changes in serum PTH and phosphate is 0.77, p<0.001; thus, the power of prediction is markedly increased. The effect of therapy on biochemical variables was also analyzed using this RF.ConclusionOur results suggest that the analysis of the complex interactions between mineral metabolism parameters in CKD-MBD may demand a more advanced data analysis system such as RF.

Pengaruh Budaya Organisasi Terhadap Employee Engagement

Engagement at PT Kertas Padalarang (Persero) and the influence of organizational culture on employee engagement. The dimensions of organizational culture are involvement, consistency, adaptability and mission (Denison on Sobirin, 2009: 191). The dimensions of employee engagement are vigor, dedication and absorption (Schaufeli and Bakker, 2003: 5). The sample of this research as much as 151 respondents consists of supervisor, assistant supervisor, main operator, operator, and others (honorary and contract employees) which spreads in accounting, finance, R &amp; D, logistic, marketing, human resources, internal control unit, engineering and production department. The method which used in this research is quantitative research methods. Data analysis method which used are descriptive analysis, classic assumption test, regression analysis, correlation analysis and hypothesis testing. Based on the results, organizational culture is currently in the good category, compare to employee engagement that is still in the moderate category. The relation of organizational culture and employee engagement currently are on strong category. The Regression equation in this research is Y=8,655+0,651X. Therefore, the influence of organizational culture on employee engagement amounted to 45,4%.

Bayesian Survival Analysis of Genetic Variants in PTPRN2 Gene for Age at Onset of Cancer

Background: The protein tyrosine phosphatase, receptor type, N polypeptide 2 (PTPRN2) gene may play a role in cancer; however, no study has focused on the associations of genetic variants within the PTPRN2 gene with age at onset (AAO) of cancer. Methods: This study examined 220 single nucleotide polymorphisms (SNPs) within the PTPRN2 gene in the Marshfield sample with 716 cancer cases (any diagnosed cancer, excluding minor skin cancer) and 2,848 non-cancer controls. Multiple logistic regression model and linear regression model in PLINK software were used to examine the association of each SNP with the risk of cancer and AAO, respectively. For survival analysis of AAO, both classic Cox regression and Bayesian survival analysis using the Cox proportional hazards model in SAS v. 9.4 were applied to detect the association of each SNP with AAO. The hazards ratios (HRs) with 95% confidence intervals (CIs) were estimated. Results: Single marker analysis identified 10 SNPs associated with the risk of cancer and 9 SNPs associated with AAO (p < 0.05). SNP rs7783909 revealed the strongest association with cancer (p = 6.52x10-3); while the best signal for AAO was rs4909140 (p = 6.18x10-4), which was also associated with risk of cancer (p = 0.0157). Classic Cox regression model showed that 11 SNPs were associated with AAO (top SNP rs4909140 with HR = 1.38, 95%CI = 1.11-1.71, p = 3.3x10-3). Bayesian Cox regression model showed similar results to those using the classic Cox regression (top SNP rs4909140 with HR = 1.39, 95%CI = 1.1-1.69). Conclusions: This study provides evidence of several genetic variants within the PTPRN2 gene influencing the risk of cancer and AAO, and will serve as a resource for replication in other populations.

Outliers in Survival Analysis

Yasam cozumlemesi, tanimlanan herhangi bir olayin ortaya cikmasina kadar gecen surenin incelenmesinde kullanilan istatistiksel yontemler butunudur. Yasam cozumlemesinde aykiri degerler klasik regresyonda kullanilan yontemlerden farkli yontemler kullanilarak hesaplanmaktadir. Yasam cozumlemesinde aykiri deger belirleme yontemleri artiklara ve artiklarin analizine dayanmaktadir. Yasam cozumlemesinde kullanilan baslica artik turleri Cox-Snell, Martingale, Schoenfeld, Sapma, Log-odds ve Normal sapma artiklaridir. Etkili gozlemleri belirlemek icin kullanilan yontemler ise DFBETA, LMAX ve Olabilirlik Degisim degerleridir. Incelenen artik turleri mide kanseri ile ilgili verilere uygulanmis ve aykiri degerler belirlenmistir. Belirlenen aykiri degerler cikarilarak model yeniden kurulmus ve aykiri degerler cikarildiginda sonuclarin daha iyi oldugu gorulmustur.

Explore Xueshuan Xinmaining tablet effecting on treatment outcome of coronary heart disease based on propensity score

Xueshuan Xinmaining tablet is a Chinese patent medicine for treating chest pain caused by blood stasis. It is widely used in clinical prevention and treatment of coronary heart disease. In order to understand the treatment effect of Xueshuan Xinmaining tablet in patients with coronary heart disease, we extracted electronic medical record data from 18 large hospitals nationwide. We matched the coronary artery disease patients with or without Xueshuan Xinmaining tablet treatment on gender, age, condition at admission and whether combined with cardiac insufficiency on a one to one ratio. After matching, both groups, patients using Xueshuan Xinmaining tablet (group A) and patients not using Xueshuan Xinmaining tablet (group B), ended up with 1,122 people. In order to evaluate the effectiveness of treatment, the endpoint of effective group was defined as "cure" and "better" while the endpoint of invalid group was defined as "invalid" and "death". Chi-square test showed a statistical significant difference (P < 0.05) between the two groups of patients with coronary heart disease, with a higher efficiency in Xueshuan Xinmaining group. Classic logistic regression analysis showed no statistical significant difference between the two groups on treatment outcome efficiency. Generalized boosted models (GBM) and propensity score (PS) weighted Logistic regression were then applied to balance 45 variables between the two groups. The results showed a regression coefficient greater than 0 and a statistical significant difference (P < 0.05) between the two groups. Based on the existing results of the analysis, we considered that coronary heart disease patients using Xueshuan Xinmaining tablet had a higher efficiency in clinical efficiency than the patients not using Xueshuan Xinmaining tablet. Since this study did not certainly eliminate all the possible confounders and patients from the hospitals included in this study were not yet well represent the overall situation of the source population, the study conclusion only provided drug use reference for clinical doctors for coronary heart disease. Large randomized controlled trials needs to be done for more reliable results to guide clinical rational and effective medication.

Comparison of fuzzy logic based models for the multi-response surface problems with replicated response measures

A replicated multi-response experiment is a process that includes more than one responses with replications. One of the main objectives in these experiments is to estimate the unknown relationship between responses and input variables simultaneously. In general, classical regression analysis is used for modeling of the responses. However, in most practical problems, the assumptions for regression analysis cannot be satisfied. In this case, alternative modeling methods such as fuzzy logic based modeling approaches can be used. In this study, fuzzy least squares regression (FLSR) and fuzzy clustering based modeling methods, which are switching fuzzy C-regression (SFCR) and Takagi–Sugeno (TS) fuzzy model, are preferred. The novelty of the study is presenting the applicability of SFCR to the multi-response experiment data set with replicated response measures. Three real data set examples are given for application purposes. In order to compare the prediction performance of modeling approaches, root mean square error (RMSE) criteria is used. It is seen from the results that the SFCR gives the better prediction performance among the other fuzzy modeling approaches for the replicated multi-response experimental data sets.

Pengaruh Motivasi dan Kepemimpinan terhadap Kinerja

&lt;span&gt;&lt;em&gt;This study aims to examine and analyze the influence of motivation and &lt;/em&gt;&lt;span&gt;&lt;em&gt;leadership on the performance of the Sales Promotion Merchandising (SPM) Suntory &lt;/em&gt;&lt;span&gt;&lt;em&gt;Beverage Garuda Indonesia Sidoarjo. In this study, using a motivational variable (X&lt;/em&gt;&lt;span&gt;&lt;em&gt;1&lt;/em&gt;&lt;span&gt;&lt;em&gt;), &lt;/em&gt;&lt;span&gt;&lt;em&gt;leadership (X&lt;/em&gt;&lt;span&gt;&lt;em&gt;2&lt;/em&gt;&lt;span&gt;&lt;em&gt;) and performance (Y). Data collected through questionnaires and &lt;/em&gt;&lt;span&gt;&lt;em&gt;conducted on 30 Sales Promotion Merchandising (SPM) PT. Suntory Garuda Beverage &lt;/em&gt;&lt;span&gt;&lt;em&gt;Sidoarjo. Analysis of the data in this study using SPSS version 14, engineering test data &lt;/em&gt;&lt;span&gt;&lt;em&gt;used in this study include test validity by factor analysis, reliability testing with ALPHA &lt;/em&gt;&lt;span&gt;&lt;em&gt;Cronvbach, classic assumption test and multiple linear regression analysis, to test and &lt;/em&gt;&lt;span&gt;&lt;em&gt;prove the research hypothesis. In this study all theories, independent and dependent &lt;/em&gt;&lt;span&gt;&lt;em&gt;variables are accepted and valid. In this study proves that the motivation partially have &lt;/em&gt;&lt;span&gt;&lt;em&gt;a positive influence on employee performance, with significance 0.004. Similarly, for &lt;/em&gt;&lt;span&gt;&lt;em&gt;the leadership also have a positive influence on employee performance, with &lt;/em&gt;&lt;span&gt;&lt;em&gt;significance 0.002&lt;/em&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;

An experimental study on the temperature dependency for horizontal shear performance of 300 × 300 square lead–rubber bridge bearing

It is widely accepted that the mechanical behaviour of lead–rubber bearing for bridge will change distinctly with temperature variation. This paper outlines an experimental study for 300 × 300 square type lead–rubber bridge bearing. The experimental results of temperature dependency for horizontal shear performance of lead–rubber bearing are presented. It can be seen that the horizontal shear stiffness of the bearing will be reduced as the temperature rises. The horizontal damping ratio of the bearing will be reduced as the temperature increases, but such a trend will not be obvious when the temperature is higher than 23°C. By using the classical regression analysis, estimation of the formula for temperature dependency for horizontal shear stiffness and horizontal damping ratio of 300 × 300 mm square lead–rubber bearings are given.

HARmonic–LINear (HarLin) model for solar irradiation estimation

The solar energy has potential future effectiveness in a variety of areas and it helps to decrease the dominance of fossil fuels, which cause atmospheric pollution, global warming and climate change impacts. In the literature, there are different methodologies for its modeling, but this study suggests the harmonic analysis application to solar irradiation and sunshine duration data for more refined relevant prediction of solar irradiation. The basis of the methodology is combined application of the HARmonic and the classical LINear regression analyses, and therefore, it is referred to as the HarLin model. It isolates first the periodicity from the daily averages of records and then the linear regression analysis is applied elegantly to first order stationary data. The results are tested and compared with the Adaptive-Neuro Fuzzy Inference System (ANFIS) model based on the Sugeno fuzzy logic inference system and Angström–Prescott model in the form of a linear regression analysis. In the application, three solar irradiation sites are considered from different solar energy potential locations in Turkey, namely, at Adana, Gaziantep and Silifke cities. The predictions by the HarLin model appear more successful than ANFIS and the classical Angström–Prescott approaches.

Applicability of Bromilow´s Time-cost Model for Residential Projects in Slovakia

Abstract The concept of construction time has been mentioned by most researchers as one of the key factors of a successful project. Time-cost model for rapid estimation of construction time appeared in the world some fifty years ago and the most mentioned is model developed by Bromilow. The purpose of submitted research is to validate Bromilow´s time-cost (BTC) model and identify constants in BTC model in context with residential construction projects in Slovak construction conditions. The data for the study were obtained from 28 residential projects completed within the period 2010-2013 in regions of Slovakia. The data were analyzed using classical correlation and regression analysis

Rank regression: an alternative regression approach for data with outliers.

SummaryLinear regression models are widely used in mental health and related health services research. However, the classic linear regression analysis assumes that the data are normally distributed, an assumption that is not met by the data obtained in many studies. One method of dealing with this problem is to use semi-parametric models, which do not require that the data be normally distributed. But semi-parametric models are quite sensitive to outlying observations, so the generated estimates are unreliable when study data includes outliers. In this situation, some researchers trim the extreme values prior to conducting the analysis, but the ad-hoc rules used for data trimming are based on subjective criteria so different methods of adjustment can yield different results. Rank regression provides a more objective approach to dealing with non-normal data that includes outliers. This paper uses simulated and real data to illustrate this useful regression approach for dealing with outliers and compares it to the results generated using classical regression models and semi-parametric regression models.

Abstract 5072: Meta-analysis of genome-wide association studies identifies novel susceptibility loci for follicular lymphoma

Abstract Background. Follicular lymphoma (FL) is an indolent B-cell malignancy with a variable clinical course that may transform to more aggressive forms of lymphoma. Previous modestly powered GWAS have reported multiple FL susceptibility loci in the HLA class I and II regions at 6p21.32-33, but novel non-HLA susceptibility loci and the genetic architecture of FL associations in the HLA region remain to be elucidated. Methods. We conducted the largest GWAS of FL to date consisting of 2,142 cases and 6,221 controls of European ancestry from 22 studies scanned on the Illumina OmniExpress. After imputation of common SNPs using IMPUTE2 and 1,000 Genomes Project v3 data, we conducted a meta-analysis of these data with two previous FL GWAS (n=586 cases, 1,537 controls) and replicated top hits in an additional 629 cases and 4,283 controls. Expression quantitative trait loci (eQTL) analyses were performed to evaluate the effects of associated variants on gene expression. Classical HLA allele imputations and stepwise regression analyses are underway to further characterize the HLA associations. Results. In the joint meta-analysis, the strongest association with FL risk was observed in the HLA region, where a large number of SNPs showed genome-wide significance (P&amp;lt;5x10-8 to P= 1.84x10-84), particularly in HLA class II at 6p21.32 where several HLA eQTLs were identified (P &amp;lt; 0.05). Outside HLA, we identified four novel loci associated with FL at 11q23.3 (CXCR5, rs4938573; P=3.14x10-15), 11q24.3 (ETS1, rs4937362; P=3.33x10-9), 3q13.33 (CD86, rs2681416; P=9.79x10-11) and 3q28 (LPP, rs6444305, P=2.55x10-8). These novel susceptibility loci were located in four biologically relevant genes involved in immune regulation: CXCR5 and its ligand, CXCL13, are involved in guiding B-cells into the B-cell zones of secondary lymphoid organs as well as T-cell migration. ETS1 is expressed in lymphoid cells and regulates immune cell function including differentiation, survival, and proliferation. CD86 and CD80 are classic members of the B7 costimulatory pathway that is important in maintaining immune function, suppression of autoimmunity and antitumor surveillance. LPP encodes a LIM domain-containing protein of the zyxin family and participates in cell adhesion, cell migration, proliferation and transcription dynamics. Conclusions. This large GWAS provides further support for the important role of common genetic variation in non-HLA genes and further evidence of the key role that HLA immune-regulatory genes play in the pathogenesis of FL. Citation Format: Christine F. Skibola, Sonja I. Berndt, James R. Cerhan, Zhaoming Wang, Joseph Vijai, Lucia Conde, Paul de Bakker, Sophia S. Wang, Claire M. Vajdic, Brenda M. Birmann, Susan L. Slager, James McKay, Paige M. Bracci, Alexandra Nieters, Qing Lan, Angela R. Brooks-Wilson, Martha S. Linet, Demetrius Albanes, John J. Spinelli, Roel C.H. Vermeulen, Mark P. Purdue, Meredith Yaeger, Lauren R. Teras, Silvia de Sanjose, Alain Monnereau, Simon Crouch, Jia Nee Foo, Henrik Hjalgrim, Gianluca Severi, Brian K. Link, Kimberly A. Bertrand, Yawei Zhang, Karin E. Smedby, Stephen J. Chanock, Nathaniel Rothman, NHL GWAS Consortium. Meta-analysis of genome-wide association studies identifies novel susceptibility loci for follicular lymphoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5072. doi:10.1158/1538-7445.AM2014-5072

Analysis effects of Shuxuening injection on patient’s liver function based on electronic medical data

To assess whether the Shuxuening injection influences liver function, this paper analyzes the hospital information system (HIS) data from 20 national hospitals. The patients were divided two groups: patients (5 353 cases) using Shuxuening injection acted as the exposed group, then the patients (4 863 cases) not using Shuxuening injection acted as the unexposed group. Take the abnormal changes of alanine aminotransferase and aspartate aminotransferase indexes as the result. Control confounding factors by stratification analysis, classic logistic regression analysis, before logistic regression based on propensity score weighting method and logistic regression based on generalized boosted models (GBM) of propensity score weighted combination of covariate adjustment. Then, the study analyzes the effects of Shuxuening injection on liver function by observing the changes of the indexes. Analysis of the impact of parenterally administered Shuxuening on ALT shows that, before logistic regression based on propensity score, then the regression is -0.232 (P value is 0.017). However, after logistic regression based on propensity score method the regression became -0.150 (P value is 0.370). Whereas, analysis of the impact of parenterally administered Shuxuening on AST shows that, before logistic regression based on propensity score, then the regression is -0.034 (P value is 0.767). However, after logistic regression based on propensity score method the regression became -0.091(P value is 0.538). Thus, propensity score method can control a large number of confounding factors, making the results more close to the clinic. Hence, based on existing electronic medical data, this study didn't find that parenterally administered Shuexuening influences ALT and AST.

The Effect of Timeliness and Credit Ratings on the Information Content of Earnings Announcements

This paper investigates the impact of timeliness and credit ratings on the information content of the earnings announcements of Greek listed firms from 2001 to 2008. Using the classical event study methodology and regression analysis, we find that firms tend to release good news on time and are inclined to delay the release of bad news. We also provide evidence that the level of corporate risk differentiates the information content of earnings according to the credit rating category. Specifically, firms displaying high creditworthiness enjoy positive excess returns on earnings announcement dates. In contrast, firms with low creditworthiness undergo significant share price erosions on earnings announcement days. We also observe a substitution effect between timeliness and credit ratings in relation to the information content of earnings announcements. Specifically, we find that as the credit category of earnings-announcing firms improves, the informational role of timeliness is mitigated.

POSOUZENÍ VLIVU ZMĚN SAZEB DANÍ NA CENY CIGARET V ČESKÉ REPUBLICE

The consumption taxes called excise duties are imposed on tobacco products in the Czech Republic and also in the other European Union countries. Cigarette taxation is atypical compared to taxation of other products encumbered with excise duty. Number of cigarettes and also consumer’s price together make the tax base. Harmonization effort of cigarette taxes in the European Union countries and also pure fiscal need of Czech Republic, are causes of frequent changes of cigarette taxes rates in recent years. These changes does not conduce only to changes of tax collection, but also bring many other effects, that have to be identified and analysed to set global results of steps to be made in the scope of tax policy in the Czech Republic. Average price of all 435 cigarettes marks on the market in the period from July 2001 to July 2009 is the base characteristic necessary to examine impacts of cigarette taxes changes. Classical regression analysis is used to analyse legislative changes impact on average cigarettes price. Single legislative changes are realized through the use of synthetic (dummy) variables performing as explanatory variables. There is also tested significance of particular parameters of the model and analysed structural breakages in this text. It is necessary not only to impeach lawful impact of these steps during imposing or changing of taxation, but also effective impact, which is often very different from lawful impact. From implementation of obligatory of marking the cigarettes in 2001 we are able to identify some relevant characteristics and impacts of changes of tax burden imposed on cigarettes in the Czech Republic. Statistically significant changes of average non-weighted price of cigarettes are identified in here, as well as structural breakages of average non-weighted price of cigarettes and values of tax incidence. Also temporal and other connection with given facts is discussed.

Peak discharge prediction due to embankment dam break by using sensitivity analysis based ANN

Accurate prediction of peak discharges due to embankment dam failure is essential to identifying and reducing potential for loss of life and damage in the downstream floodplain. Because, when a dam fails the damage is certain, but the extent of this damage cannot be evaluated in advance. The loss of life and property damage can vary depending on flood area and population. In order to cope with embankment dam breaching and to take necessary steps beforehand many researchers worked on parametric breach models based on Regression Analysis (RA) to estimate the peak outflow from a breached embankment dam since 1970s. RA is a widely-used approach that could provide acceptable results. Since, this approach bears restrictive assumptions, direct application of RA ignoring these assumptions might cause pitfalls and biased calculations. In this study, it is shown that previous works generated by RA gives biased calculations and a new alternative approach, based on Artificial Neural Networks (ANN), is suggested in replacement of classical RA, which gives more accurate results according to both numerical error criteria and scientific background.