scholarly journals Crossing Reliability of Electric Bike Riders at Urban Intersections

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Huan Mei ◽  
Yang Xiaobao ◽  
Jia Bin
Keyword(s):  
Survival Analysis ◽  
Waiting Times ◽  
Red Light ◽  
Parametric Models ◽  
Reliability Model ◽  
Light Phase ◽  
Video Cameras ◽  
Empirical Basis ◽  
Covariate Effects ◽  
Electric Bike

This paper presents a crossing reliability model of electric bike riders at urban intersections using survival analysis approach. Riders’ crossing behavior was collected by video cameras. Waiting times in the red-light phase were modeled by reliability-based model that recognizes the covariate effects. Three parametric models by the exponential, Weibull, and log-logistic distributions were proposed to analyze when and why electric bike riders cross against the red light. The results indicate that movement information and situation factors have significant effects on riders’ crossing reliability. The findings of this paper provide an important demonstration of method and an empirical basis to assess crossing reliability of electric bike riders at the intersection.

scholarly journals A Reliability-Based Analysis of Bicyclist Red-Light Running Behavior at Urban Intersections

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Mei Huan ◽  
Xiaobao Yang
Keyword(s):  
Waiting Times ◽  
Red Light ◽  
Video Recording ◽  
Personal Characteristics ◽  
Proportional Hazard ◽  
Red Light Running ◽  
Reliability Models ◽  
Traffic Conditions ◽  
Covariate Effects ◽  
Cox Hazard Model

This paper describes the red-light running behavior of bicyclists at urban intersections based on reliability analysis approach. Bicyclists’ crossing behavior was collected by video recording. Four proportional hazard models by the Cox, exponential, Weibull, and Gompertz distributions were proposed to analyze the covariate effects on safety crossing reliability. The influential variables include personal characteristics, movement information, and situation factors. The results indicate that the Cox hazard model gives the best description of bicyclists’ red-light running behavior. Bicyclists’ safety crossing reliabilities decrease as their waiting times increase. There are about 15.5% of bicyclists with negligible waiting times, who are at high risk of red-light running and very low safety crossing reliabilities. The proposed reliability models can capture the covariates’ effects on bicyclists’ crossing behavior at signalized intersections. Both personal characteristics and traffic conditions have significant effects on bicyclists’ safety crossing reliability. A bicyclist is more likely to have low safety crossing reliability and high violation risk when more riders are crossing against the red light, and they wait closer to the motorized lane. These findings provide valuable insights in understanding bicyclists’ violation behavior; and their implications in assessing bicyclists’ safety crossing reliability were discussed.

Impact of Facility Damages on Hospital Capacities for Decision Support in Disaster Response Planning for an Earthquake

2009 ◽  
Vol 24 (4) ◽  
pp. 333-341 ◽  
Author(s):  
Jomon Aliyas Paul ◽  
Li Lin
Keyword(s):  
Disaster Response ◽  
Waiting Times ◽  
Parametric Models ◽  
Emergency Relief ◽  
Response Planning ◽  
Hospital Operations ◽  
Emergency Assistance ◽  
Life Saving ◽  
Inaccurate Estimation ◽  
The Impact

AbstractHospitals provide life-saving functions and emergency assistance to communities when disaster strikes. Any damage to hospitals from a disaster, either structural and non-structural, can impair these capabilities. In addition, an inaccurate estimation of the treatment capacities available at hospitals in a disaster-affected region can severely affect the success of emergency relief plans. In this paper, the impact of facility damage on hospital operations is estimated using a generic simulation model. From the simulation results, parametric models are developed for estimating hospitals' capacities and patient waiting times that could be used by emergency response teams in making casualty dispatching/routing decisions.

Survival analysis with change-points in covariate effects

2020 ◽  
Vol 29 (11) ◽  
pp. 3235-3248
Author(s):  
Chun Yin Lee ◽  
KF Lam
Keyword(s):  
Survival Analysis ◽  
Change Point ◽  
Cox Regression ◽  
Bootstrap Method ◽  
Bernstein Polynomials ◽  
Change Points ◽  
Ratio Test ◽  
Covariate Effect ◽  
Sequential Approach ◽  
Covariate Effects

We apply a maximal likelihood ratio test for the presence of multiple change-points in the covariate effects based on the Cox regression model. The covariate effect is assumed to change smoothly at one or more unknown change-points. The number of change-points is inferred by a sequential approach. Confidence intervals for the regression and change-point parameters are constructed by a bootstrap method based on Bernstein polynomials conditionally on the number of change-points. The methods are assessed by simulations and are applied to two datasets.

scholarly journals Survival Analysis on Pedigrees: A Marked Point Process Model

2010 ◽  
Vol 40 (1) ◽  
pp. 35-64
Author(s):  
Angus S. Macdonald
Keyword(s):  
Survival Analysis ◽  
Process Model ◽  
Point Processes ◽  
Marked Point ◽  
Age At Onset ◽  
Parametric Models ◽  
Marked Point Processes ◽  
Inherited Disorders ◽  
Partial Model ◽  
Special Cases

AbstractRegulation of insurers' use of genetic information means actuaries are interested in age-at-onset of genetic disorders. Arjas & Haara (1984) suggested marked point processes (MPPs) as useful models for life history data with complex covariates. Age-at-onset distributions (or equivalently, hazard rates) in respect of inherited disorders are often estimated from pedigrees, which are life histories with unusually complex covariates, as well as strong dependencies induced by shared genes. Since Elston (1973) parametric models have often been used, conditioning the likelihood on known genotypes. However, a genotype identii ed by a presymptomatic genetic test is a form of internal covariate (Kalbfleisch & Prentice, 2002). We propose a very general MPP model of a pedigree, including presymptomatic genetic testing, (‘the full model’) and show under what circumstances the partial model leading to Elston's likelihood is valid. In practice, pedigrees are often ascertained retrospectively. Many such events can be modelled by augmenting the natural filtration of the MPP. We show that, except in simple special cases, the partial model is no longer valid, and the resulting likelihoods appear to be intractable. In particular, ascertainment interacts even with independent censoring so that likelihoods no longer factorize. For one simple special case — studies of sibships — we generalise a classical result to age-at-onset data. We conclude that the study of genetic conditions with variable age at onset gains insights from the underlying principles of survival analysis in their modern form, but that great care is needed in translating epidemiological studies into actuarial models.

On some waiting time problems

2000 ◽  
Vol 37 (03) ◽  
pp. 756-764 ◽  
Author(s):  
Valeri T. Stefanov
Keyword(s):  
Survival Analysis ◽  
Finite Number ◽  
Markov Processes ◽  
Waiting Time ◽  
Generating Functions ◽  
Continuous Time ◽  
Waiting Times ◽  
Phase Type ◽  
Phase Type Distributions ◽  
Semi Markov Processes

A unifying technology is introduced for finding explicit closed form expressions for joint moment generating functions of various random quantities associated with some waiting time problems. Sooner and later waiting times are covered for general discrete- and continuous-time models. The models are either Markov chains or semi-Markov processes with a finite number of states. Waiting times associated with generalized phase-type distributions, that are of interest in survival analysis and other areas, are also covered.

scholarly journals A Non-Parametric Approach for Survival Analysis of Component-Based Software

2020 ◽  
Vol 5 (2) ◽  
pp. 309-318
Author(s):  
Sandeep Chopra ◽  
Lata Nautiyal ◽  
Preeti Malik ◽  
Mangey Ram ◽  
Mahesh K. Sharma
Keyword(s):  
Survival Analysis ◽  
Failure Rate ◽  
Growth Models ◽  
Reliability Estimation ◽  
Parametric Models ◽  
Model Parameters ◽  
Parametric Approach ◽  
Estimation Model ◽  
Failure Data ◽  
Non Parametric

Reliability of a software or system is the probability of system to perform its functions adequately for the stated time period under specific environment conditions. In case of component-based software development reliability estimation is a crucial factor. Existing reliability estimation model falls into two broad categories parametric and non-parametric models. Parametric models approximate the model parameters based on the assumptions of fundamental distributions. Non-parametric models enable parameter estimation of the software reliability growth models without any assumptions. We have proposed a novel non-parametric approach for survival analysis of components. Failure data is collected based on which we have calculated failure rate and reliability of the software. Failure rate increases with the time whereas reliability decreases with the time.

On some waiting time problems

2000 ◽  
Vol 37 (3) ◽  
pp. 756-764 ◽  
Author(s):  
Valeri T. Stefanov
Keyword(s):  
Survival Analysis ◽  
Finite Number ◽  
Markov Processes ◽  
Waiting Time ◽  
Generating Functions ◽  
Continuous Time ◽  
Waiting Times ◽  
Phase Type ◽  
Phase Type Distributions ◽  
Semi Markov Processes

A unifying technology is introduced for finding explicit closed form expressions for joint moment generating functions of various random quantities associated with some waiting time problems. Sooner and later waiting times are covered for general discrete- and continuous-time models. The models are either Markov chains or semi-Markov processes with a finite number of states. Waiting times associated with generalized phase-type distributions, that are of interest in survival analysis and other areas, are also covered.

Integrating Semiparametric and Parametric Models in Survival Analysis of Bridge Element Deterioration

2013 ◽  
Vol 19 (2) ◽  
pp. 176-185 ◽  
Author(s):  
Ying Nan Yang ◽  
Mohan M. Kumaraswamy ◽  
Hoat Joen Pam ◽  
Hong Ming Xie
Keyword(s):  
Survival Analysis ◽  
Parametric Models
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