Safety and comfort assessment of a train passing over an earthquake-damaged bridge based on a probability model

2021 ◽  
pp. 1-12
Author(s):  
Xiang Liu ◽  
Lizhong Jiang ◽  
Ping Xiang ◽  
Liqiang Jiang ◽  
Zhipeng Lai
Keyword(s):  
Probability Model

Probability model for control parameters in the aircraft's information and control systems

2018 ◽  
Vol 2 ◽  
pp. 9-16
Author(s):  
A. Al-Ammouri ◽  
◽  
H.A. Al-Ammori ◽  
A.E. Klochan ◽  
A.M. Al-Akhmad ◽  
...  
Keyword(s):  
Control Systems ◽  
Probability Model ◽  
Control Parameters ◽  
And Control

Economic modeling of touristic services demand in the regions

2019 ◽  
pp. 87-93
Author(s):  
Ivan Blahun ◽  
Halyna Leshchuk ◽  
Mariya Kyfor
Keyword(s):  
Systematic Approach ◽  
Income Elasticity ◽  
Probability Model ◽  
Economic Modeling ◽  
Tourism Demand ◽  
Goods And Services ◽  
Household Incomes ◽  
Tourism Services ◽  
Income Decile

Considering the important role of tourism in the socio-economic development of regions, the need for information and modeling of ways to increase demand for tourism services and tourism development is being updated. The article uses methods of analytical, logical, comparative analysis and systematic approach to study trends in demand for tourist services in Ukraine. Econometric modeling analyzes the demand for tourism services by the level of income and expenditures of the population in 2018. Trends in demand for tourism services in 2018 in terms of income and expenditure of the population with the use of the Tornquist econometric model have been analyzed. It is proposed to use the decile groups of the population for analyzing income and expenditure by the level of income, total income per capita, the level of household expenditure relative to income, the percentage of tourism expenditure by households, the expenditure on tourism and the elasticity of tourism demand. Average values of the population’s expenditures on tourism were established, which helped to determine the elasticity of effective demand for each decile group. The more than one unit of elasticity of effective tourism demand for each decile group indicated that tourism services for domestic households belong to the group of luxury goods and services. It should be noted that in the following decile income groups of households there is a decrease in elasticity. It means that when income tends to increase indefinitely, elasticity coefficients fall, and this indicates a stabilization of costs of this type. In this case, the percentage of households in each decile group that recorded the costs of organized tourism in their budgets and the value of the probability of household participation in this form of recreation was determined based on an estimated probability model. An analysis of the values of income elasticity indicators in each income decile group has shown that increasing household incomes contribute to increased demand for tourism services and an increase in the share of expenditures for these purposes in household budgets.

A Probability Model for TCP Slow Start

2011 ◽  
Vol 21 (1) ◽  
pp. 45-48
Author(s):  
Asmir Gogic ◽  
Nermin Suljanovic ◽  
Amer Hasanovic ◽  
Aljo Mujcic
Keyword(s):  
Probability Model ◽  
Slow Start

Sibling Models, Categorical Outcomes, and the Intra-Class Correlation

2021 ◽  
Author(s):  
Richard Breen ◽  
John Ermisch
Keyword(s):  
Random Effects ◽  
Probability Model ◽  
Intraclass Correlation ◽  
Linear Probability Model ◽  
Intra Class Correlation ◽  
Sibling Differences ◽  
Sibling Models ◽  
Alternative Measures ◽  
Linear Probability ◽  
Parametric Estimate

Abstract In sibling models with categorical outcomes the question arises of how best to calculate the intraclass correlation, ICC. We show that, for this purpose, the random effects linear probability model is preferable to a random effects non-linear probability model, such as a logit or probit. This is because, for a binary outcome, the ICC derived from a random effects linear probability model is a non-parametric estimate of the ICC, equivalent to a statistic called Cohen’s κ. Furthermore, because κ can be calculated when the outcome has more than two categories, we can use the random effects linear probability model to compute a single ICC in cases with more than two outcome categories. Lastly, ICCs are often compared between groups to show the degree to which sibling differences vary between groups: we show that when the outcome is categorical these comparisons are invalid. We suggest alternative measures for this purpose.

scholarly journals Demographic Dynamics in Multitype Populations with Migrations

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 246
Author(s):  
Manuel Molina-Fernández ◽  
Manuel Mota-Medina
Keyword(s):  
Mathematical Modeling ◽  
Population Dynamics ◽  
Branching Process ◽  
Probability Model ◽  
Biological Systems ◽  
Research Work ◽  
General Setting ◽  
Process Theory ◽  
Multitype Branching Process ◽  
Demographic Dynamics

This research work deals with mathematical modeling in complex biological systems in which several types of individuals coexist in various populations. Migratory phenomena among the populations are allowed. We propose a class of mathematical models to describe the demographic dynamics of these type of complex systems. The probability model is defined through a sequence of random matrices in which rows and columns represent the various populations and the several types of individuals, respectively. We prove that this stochastic sequence can be studied under the general setting provided by the multitype branching process theory. Probabilistic properties and limiting results are then established. As application, we present an illustrative example about the population dynamics of biological systems formed by long-lived raptor colonies.

3-Dimensional direct sampling-based environmental contours using a semi-parametric joint probability model

2021 ◽  
Vol 112 ◽  
pp. 102710
Author(s):  
Xiaoyu Bai ◽  
Hui Jiang ◽  
Xiaoyu Huang ◽  
Guangsong Song ◽  
Xinyi Ma
Keyword(s):  
Probability Model ◽  
Joint Probability ◽  
3 Dimensional ◽  
Direct Sampling ◽  
Joint Probability Model

Error and Reliability in Stochastic Processes and Psychological Measurement

1972 ◽  
Vol 31 (1) ◽  
pp. 131-140 ◽  
Author(s):  
Donald W. Zimmerman
Keyword(s):  
Stochastic Processes ◽  
Random Error ◽  
Random Sampling ◽  
Probability Model ◽  
Random Variables ◽  
Formal Structure ◽  
Intermediate Structure ◽  
Psychological Measurement ◽  
Joint Distributions ◽  
True Values

The concepts of random error and reliability of measurements that are familiar in traditional theories based on the notions of “true values” and “errors” can be represented by a probability model having a simpler formal structure and fewer special assumptions about random sampling and independence of measurements. In this model formulas that relate observable events are derived from probability axioms and from primitive terms that refer to observable events, without an intermediate structure containing variances and correlations of “true” and “error” components of scores. While more economical in language and formalism, the model at the same time is more general than classical theories and applies to stochastic processes in which joint distributions of many dependent random variables are of interest. In addition, it clarifies some long-standing problems concerning “experimental independence” of measurements and the relation of sampling of individuals to sampling of measurements.

A new approach to bracket prediction in the NCAA Men’s Basketball Tournament based on a dual-proportion likelihood

2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Ajay Andrew Gupta
Keyword(s):  
National Collegiate Athletic Association ◽  
Expert Knowledge ◽  
Probability Model ◽  
Expected Value ◽  
Division I ◽  
Prediction System ◽  
New Approach ◽  
Men's Basketball ◽  
Popular Interest ◽  
The One

AbstractThe widespread proliferation of and interest in bracket pools that accompany the National Collegiate Athletic Association Division I Men’s Basketball Tournament have created a need to produce a set of predicted winners for each tournament game by people without expert knowledge of college basketball. Previous research has addressed bracket prediction to some degree, but not nearly on the level of the popular interest in the topic. This paper reviews relevant previous research, and then introduces a rating system for teams using game data from that season prior to the tournament. The ratings from this system are used within a novel, four-predictor probability model to produce sets of bracket predictions for each tournament from 2009 to 2014. This dual-proportion probability model is built around the constraint of two teams with a combined 100% probability of winning a given game. This paper also performs Monte Carlo simulation to investigate whether modifications are necessary from an expected value-based prediction system such as the one introduced in the paper, in order to have the maximum bracket score within a defined group. The findings are that selecting one high-probability “upset” team for one to three late rounds games is likely to outperform other strategies, including one with no modifications to the expected value, as long as the upset choice overlaps a large minority of competing brackets while leaving the bracket some distinguishing characteristics in late rounds.

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