Relevant bibliographies by topics / Statistické predikce

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Statistické predikce'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Statistické predikce"

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Dušek, Ladislav, Klára Benešová, Ondřej Ngo, et al. "Díl III. – Epidemiologie idiopatických střevních zánětů v české populaci – časový vývoj a statistické predikce počtu pacientů." Gastroenterologie a hepatologie 73, no. 3 (2019): 257–64. http://dx.doi.org/10.14735/amgh2019257.

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Widji Pamungkas, Wahyu, M. Syamsul Ma'arif, Tun Tedja Irawadi, and Yandra Arkeman. "STATISTICAL CONTROL DETECTION ADAPTIVE (SCDA) MODELING FOR MONITORING AND PREDICTION OF NATIONAL CRUDE PALM OIL (CPO) VOLUME." Jurnal Teknologi Industri Pertanian 27, no. 1 (2017): 1–8. http://dx.doi.org/10.24961/j.tek.ind.pert.2017.27.1.1.

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Radcliffe, C. J., and X. L. Huang. "Putting Statistics into the Statistical Energy Analysis of Automotive Vehicles." Journal of Vibration and Acoustics 119, no. 4 (1997): 629–34. http://dx.doi.org/10.1115/1.2889773.

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Sound and vibration transmission modeling methods are important to the design process for high quality automotive vehicles. Statistical Energy Analysis (SEA) is an emerging design tool for the automotive industry that was initially developed in the 1960’s to estimate root-mean-square sound and vibration levels in structures and interior spaces. Although developed to estimate statistical mean values, automotive design application of SEA needs the additional ability to predict statistical variances of the predicted mean values of sound and vibration. This analytical ability would allow analysis
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Boyages, John, Nathan Coombs, Sharon Laura, and Owen Ung. "STATISTICS CAN PREDICT PATIENT CONFUSION." ANZ Journal of Surgery 77, no. 7 (2007): 598–99. http://dx.doi.org/10.1111/j.1445-2197.2007.04165.x.

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Szeląg, Bartosz, Łukasz Bąk, Roman Suligowski, and Jarosław Górski. "Statistical models to predict discharge overflow." Water Science and Technology 78, no. 5 (2018): 1208–18. http://dx.doi.org/10.2166/wst.2018.392.

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Abstract In the paper, a comparison of prediction results concerning the annual number of discharges of stormwater from the drainage system due to stormwater overflows is depicted. The prediction has been computed by means of storm water management model (SWMM) and probabilistic models. Regarding the probabilistic modelling some simple statistical models such as logit, probit, Gompertz and linear discriminant analysis model have been applied, and as for the hydrodynamic modelling a generator of synthetic rainfall based on the Monte Carlo method has been used. The analyses conducted has shown t
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Monti, Nicolas Emanuel, and Roberto Mariano Garcia. "A Statistical Analysis to Predict Financial Distress." Journal of Service Science and Management 03, no. 03 (2010): 309–35. http://dx.doi.org/10.4236/jssm.2010.33038.

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Abdel-Rahman, H. I., and B. A. Marzouk. "Statistical method to predict the sunspots number." NRIAG Journal of Astronomy and Geophysics 7, no. 2 (2018): 175–79. http://dx.doi.org/10.1016/j.nrjag.2018.08.001.

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Wright, Ian H., Charles Kooperberg, Barbara A. Bonar, and Gerard Bashein. "Statistical Modeling to Predict Elective Surgery Time." Anesthesiology 85, no. 6 (1996): 1235–45. http://dx.doi.org/10.1097/00000542-199612000-00003.

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Background Accurate estimation of operating times is a prerequisite for the efficient scheduling of the operating suite. The authors, in this study, sought to compare surgeons' time estimates for elective cases with those of commercial scheduling software, and to ascertain whether improvements could be made by regression modeling. Methods The study was conducted at the University of Washington Medical Center in three phases. Phase 1 retrospectively reviewed surgeons' time estimates and the scheduling system's estimates throughout 1 yr. In phase 2, data were collected prospectively from partici
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WRIGHT, IAN H., CHARLES KOOPERBERG, BARBARA A. BONAR, GERARD BASHEIN, and James H. Diaz. "Statistical Modeling to Predict Elective Surgery Time." Survey of Anesthesiology 41, no. 6 (1997): 335. http://dx.doi.org/10.1097/00132586-199712000-00022.

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Esclapez, Lucas, Félix Collin-Bastiani, Eleonore Riber, and Bénédicte Cuenot. "A statistical model to predict ignition probability." Combustion and Flame 225 (March 2021): 180–95. http://dx.doi.org/10.1016/j.combustflame.2020.10.051.

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Dissertations / Theses on the topic "Statistické predikce"

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Kinc, Petr. "Matematické a statistické metody pro podporu vývoje softwarových aplikací." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-378318.

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This diploma thesis focuses on the design and development of the software tool using C# programming language and his subsequent implementation into the Microsoft Dynamics NAV information system. The task of this tool is to analyze the development of selected indicators using statistical methods and to predict their future development. On the basis of these predicted data, is created an indicative budget to support decision making on the determination of key accounting parameters and coefficients for the next accounting period in the company Vodovody a kanalizace Hodonín, a.s.
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Zouharová, Daniela. "Posouzení vybraných ukazatelů mezinárodní společnosti pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2021. http://www.nusl.cz/ntk/nusl-443124.

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The thesis deals with the assessment of the economic situation of a selected company using statistical methods. The theoretical part describes the financial indicators, time series and regression analysis. The analytical part contains the calculation of selected indicators, which are subjected to statistical analysis. Based on the statistical analysis, the future development of indicators in the next two years is predicted. The last part contains suggestions that can lead to the improvement of the current situation of the company.
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Matys, Jan. "Posouzení ekonomické situace společnosti a návrhy na její zlepšení." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2019. http://www.nusl.cz/ntk/nusl-402020.

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The diploma thesis evaluates the economic situation of BPS Bicycle Industrial s. r. o. time series analysis. The theoretical part describes financial indicators, time series analyzes and regression and correlation analysis. Based on the analyzes, suggestions were made to improve the current situation of the company. BPS has proven to be financially sound. Shortcomings to improvement were identified from the analyzes. For example, share of equity and debt, use of surplus funds and turnover of receivables and payables. This ratio needs to be addressed through greater use of debt. The system of s
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Matějková, Petra. "Analýza ekonomických dat s využitím statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318359.

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This master‘s thesis evaluates the financial situation of the company using selected indicators of financial analysis using time series analysis and regression analysis. Theses is separated into two parts. The theoretical part focuses on the issue of economic indicators, financial analysis, interpretation and on time series. The practical part deals with analysis of economic indicators, which will then be subjected to statistical analysis, which tries using statistical methods to analyse the trend of individual indicators and on the basis of values from previous periods to predict future devel
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Kalousková, Petra. "Posouzení finanční výkonnosti společnosti pomocí analýzy časových řad." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-377934.

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The diploma thesis deals with an assessment of the topical financial situation of BARVY A LAKY TELURIA, s. r. o. using the time series analysis. The theoretical part focuses on the description of the financial indicators, analysis of the time series, and subsequently the regressive and correlative analysis. In the practical part, selected financial indicators are statistically analyzed. The future two-year development of indicators is predicted on the basis of the selected models; subsequently dependencies among the particular indicators are determined. In the conclusion, proposals to ameliora
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Zborovská, Marie. "Posouzení ekonomické situace mateřské společnosti pomocí statistických metod." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2021. http://www.nusl.cz/ntk/nusl-443123.

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The master‘s thesis examines the issue of the interconnection of market potential with financial indicators and other variables. Data from the financial statements of ABC, s. r. o. operating on the Slovak IT market are used. The dependence of market potential and other market variables was evaluated using statistical methods. Subsequently, the analysis of selected financial indicators of the company ABC, s. r. o. is statistically evaluated and the dependence with market potential is verified. Thanks to the results, the company's proposals are determined, taking into account the current situati
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Travencová, Darina. "Posouzení vybraných ukazatelů pomocí analýzy časových řad." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318310.

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The master´s thesis evaluates the economic situation of the company SCHWARTZ TECHNICKÉ PLASTY ČR s. r. o. using statistical methods. The theoretical part describes the issues necessary for the practical part, financial indicators, time series, regression and correlation analysis. In the practical part is an analysis of selected indicators of financial analysis, then statistical methods are used to predict future developments for the coming two years and to detect dependencies between the indexes. The last section contains suggestions for improving the current situation, which are based on calc
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Pokorný, Petr. "Modelování predikce bankrotu zemědělských podniků." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-319423.

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This master’s thesis is focused on problematic within the prediction of bankruptcy of companies operating in the field of agriculture in Czech republic. First part consists of introduction to companies that do business in field of agriculture and it describes bankruptcy models that are used in academicals sphere. Other part of thesis is divided into two sub-parts. First part is dedicated to an application of data into models of bankruptcy and their evaluation. Second part is focused on improvement of the best model and its main goal is to maximize the precision of the bankruptcy.
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Bartošová, Livie. "Analýza změn ve vydáních domácností v ČR." Master's thesis, Česká zemědělská univerzita v Praze, 2016. http://www.nusl.cz/ntk/nusl-256966.

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The Diploma Thesis is focused on changes in household spending in the Czech Republic.The aim was to analyze the changes in the average spending in individual household types. In the introductory part, the method of data collection by the Czech Statistical Office, which collects the data from the households in the framework of the family accounts statistics, is described. Moreover, the inflation questions are explained here, together with the description of models of consumption ways. The introduction of the Thesis also includes the explanation of options of a non-consumer spending in the fo
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Sjövill, Rasmus. "USING SEARCH QUERY DATA TO PREDICT THE GENERAL ELECTION: CAN GOOGLE TRENDS HELP PREDICT THE SWEDISH GENERAL ELECTION?" Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412889.

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The 2018 Swedish general election saw the largest collective polling error so far in the twenty-first century. As in most other advanced democracies Swedish pollsters have faced extensive challenges in the form of declining response rates. To deal with this problem a new method based on search query data is proposed. This thesis predicts the Swedish general election using Google Trends data by introducing three models based on the assumption, that during the pre-election period actual voters of one party are searching for that party on Google. The results indicate that a model that exploits in
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Books on the topic "Statistické predikce"

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Malchose, Donald Clarence. Identifying factors that predict teen driver crashes. Mountain-Plains Consortium, 2011.

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Murphy, Joseph E. Stock market probability: Using statistics to predict and optimize investment outcomes. Probus Pub. Co., 1994.

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Office, General Accounting. Early childhood programs: Parent education and income best predict participation : report to the Chairman, Subcommittee on Children, Family, Drugs and Alcoholism, Committee on Labor and Human Resources, U.S. Senate. The Office, 1994.

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Using Modeling To Predict And Prevent Victimization. Springer International Publishing AG, 2013.

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Elsner, James B., and Thomas H. Jagger. Hurricane Climatology. Oxford University Press, 2013. http://dx.doi.org/10.1093/oso/9780199827633.001.0001.

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Hurricanes are nature's most destructive storms and they are becoming more powerful as the globe warms. Hurricane Climatology explains how to analyze and model hurricane data to better understand and predict present and future hurricane activity. It uses the open-source and now widely used R software for statistical computing to create a tutorial-style manual for independent study, review, and reference. The text is written around the code that when copied will reproduce the graphs, tables, and maps. The approach is different from other books that use R. It focuses on a single topic and explai
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Lee, P. J. Statistical Methods for Estimating Petroleum Resources. Edited by Jo Anne DeGraffenreid. Oxford University Press, 2008. http://dx.doi.org/10.1093/oso/9780195331905.001.0001.

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This book describes procedures for determining the total hydrocarbon (petroleum) resource or resource potential in a region. Statistical concepts and methods employed in petroleum resource assessment are the subject of the manuscript, extensively illustrated by numerous real case studies. Prof. Lee's computer-aided Petroleum Information Management and Resource Evaluation System (PETRIMES) methodology has been adopted by governments around the world and by major multinational oil companies to perform resource assessment and to predict future oil and gas production. Though this methodology is so
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Jarvis, B. Kierra. Using statistical modelling to predict the plutonium contamination hold-up in a glove-box. 1996.

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So Much Data So Little Math: How to Predict Data Trends -- 5 Easy Profitable Methods. University Press of America, 2000.

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Using the past to predict the future: Historical data, loss development and trend. Insurance Services Office, Inc., 1989.

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Development of an anthropometric regression equation to predict body density in African American women. 1994.

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Book chapters on the topic "Statistické predikce"

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Nogueras, Rafael, and Carlos Cotta. "Using Statistical Techniques to Predict GA Performance." In Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45720-8_85.

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Giudici, Paolo, and Emanuele Dequarti. "Statistical Models to Predict Academic Churn Risk." In Classification and Multivariate Analysis for Complex Data Structures. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13312-1_4.

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Hansson, Kristina, Birgitta Sahlén, Rasmus Bååth, and Sverker Sikström. "Linguistic: Application of LSA to Predict Linguistic Maturity and Language Disorder in Children." In Statistical Semantics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37250-7_14.

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Arora, Yash Kumar, and Santosh Kumar. "Statistical Approach to Predict Road Accidents in India." In Advances in Intelligent Systems and Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9515-5_18.

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Stuart, Elizabeth A., and Alan M. Zaslavsky. "Using Administrative Records to Predict Census Day Residency." In Case Studies in Bayesian Statistics. Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4612-2078-7_18.

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Navya, H. N., and B. P. Vijaya Kumar. "Application of Multivariate Statistical Techniques to Predict Process Quality." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5272-9_15.

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Chopde, Smita, and Jasperine James. "A Statistical Method to Predict the Protein Secondary Structure." In Nanoelectronics, Circuits and Communication Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7486-3_29.

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Croucher, John S. "Using Statistics to Predict Scores in English Premier League Soccer." In Economics, Management and Optimization in Sports. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24734-0_4.

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Invernizzi, Lorenzo, and Vittorio Magatti. "Could Machine Learning Predict the Conversion in Motor Business?" In Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89824-7_77.

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Lisitsyna, Lubov S., and Svyatoslav A. Oreshin. "Sampling and Analyzing Statistical Data to Predict the Performance of MOOC." In Smart Education and e-Learning 2019. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8260-4_7.

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Conference papers on the topic "Statistické predikce"

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Nunes, Claudia, Antonio Pacheco, and Tania Silva. "Statistical Models to Predict Electricity Prices." In 2008 5th International Conference on the European Electricity Market (EEM 2008). IEEE, 2008. http://dx.doi.org/10.1109/eem.2008.4579004.

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Xu, Haolun. "DATA MINING TECHNIQUES TO PREDICT DEFAULT IN LENDING CLUB." In International Conference on Economics, Finance and Statistics. Volkson Press, 2018. http://dx.doi.org/10.26480/icefs.01.2018.66.68.

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Hortelano, Marcos, Richard B. Reilly, and Raquel Cervigon. "Multiscale time irreversibility to predict orthostatic intolerance in older people." In 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016. http://dx.doi.org/10.1109/ssp.2016.7551829.

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Radcliffe, Clark J., and Xian Li Huang. "Putting Statistics Into the Statistical Energy Analysis of Automotive Vehicles." In ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0248.

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Abstract Sound and vibration transmission modeling methods are important to the design process for high quality automotive vehicles. Statistical Energy Analysis (SEA) is an emerging design tool for the automotive industry that was initially developed in the 1960’s to estimate root-mean-square sound and vibration levels in structures and interior spaces. Although developed to estimate statistical mean values, automotive design application of SEA needs the additional ability to predict statistical variances of the predicted mean values of sound and vibration. This analytical ability would allow
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Tarvo, Alexander. "Using Statistical Models to Predict Software Regressions." In 2008 IEEE International Symposium on Software Reliability Engineering (ISSRE). IEEE, 2008. http://dx.doi.org/10.1109/issre.2008.21.

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Mlynarski, Wiktor, and Josh McDermott. "Natural Sound Statistics Predict Auditory Grouping Principles." In 2018 Conference on Cognitive Computational Neuroscience. Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1135-0.

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Al-Ajmi, Mohammed D., Dhafer Al-Shehri, Nasser M. Al-Hajri, Abdullrahman T. Mishkes, Muhammad A. Al-Hajri, and Nayef S. Al-Shammari. "Risk Based Statistical Approach to Predict Casing Leaks." In SPE Middle East Oil & Gas Show and Conference. Society of Petroleum Engineers, 2017. http://dx.doi.org/10.2118/183948-ms.

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Liebmann, Carl M., and Martin Diorio. "Using statistical analysis methods to predict switching stability." In 2014 IEEE AUTOTEST. IEEE, 2014. http://dx.doi.org/10.1109/autest.2014.6935166.

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Williams, Trefor P., Sudha Lakshminarayanan, and Harold Sackrowitz. "Analyzing Bidding Statistics to Predict Completed Project Cost." In International Conference on Computing in Civil Engineering 2005. American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40794(179)157.

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Kustianingsih, Rini, M. Fariz Fadillah Mardianto, Belindha Ayu Ardhani, et al. "Fourier series estimator in semiparametric regression to predict criminal rate in Indonesia." In INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0042123.

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Reports on the topic "Statistické predikce"

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MORVILLO, Mónica, and Angela DIBLASI. Comparision of statistical methothologies to predict non detected observations. Cogeo@oeaw-giscience, 2011. http://dx.doi.org/10.5242/iamg.2011.0777.

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Bogner, Hillary, Fran Barg, and Dawei Xie. Using Statistical Models to Predict Worsening Health Among Older People With Disabilities. Patient-Centered Outcomes Research Institute® (PCORI), 2020. http://dx.doi.org/10.25302/05.2020.ad.12114567.

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Desai, Manisha, Maria Montez-Rath, Kris Kapphahn, et al. Comparing Statistical Models That Predict if Patients Will Take a New Medicine as Directed. Patient-Centered Outcomes Research Institute® (PCORI), 2020. http://dx.doi.org/10.25302/05.2020.me.13035989.

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gagne, Joshua, Moa Lee, Ajinkya Pawar, and Yaa-Hui Dong. Comparing Statistical Models That Predict if Patients Will Take a New Medicine as Directed. Patient-Centered Outcomes Research Institute® (PCORI), 2020. http://dx.doi.org/10.25302/05.2020.me.130906274.

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Kent, David, Jenica Upshaw, Catherine Viscoli, Christine Lundquist, Jessica Paulus, and Walter Kernan. Using Statistical Methods to Predict Treatment Response Based on Patients' Likelihood of Having Benefits or Side Effects from the Treatment. Patient-Centered Outcomes Research Institute (PCORI), 2020. http://dx.doi.org/10.25302/05.2020.rr.17050001.

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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting
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Guo, Boyun, Andrew Duguid, and Ronar Nygaard. Statistical Analysis of CO2 Exposed Wells to Predict Long Term Leakage through the Development of an Integrated Neural-Genetic Algorithm. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1373948.

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Evaluation of statistical models to predict chemical quality of shallow ground water in the Pine Barrens of Suffolk County, Long Island, New York. US Geological Survey, 1993. http://dx.doi.org/10.3133/wri924100.

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