Using Monte Carlo analysis to investigate the relationship between overconsumption and uncertain access to one's personal utility function

Courard‐Hauri, David

doi:10.1016/j.ecolecon.2007.02.018

Cited by 13 publications

(6 citation statements)

References 35 publications

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“…Prova disso é que o MMC tem sido uma ferramenta essencial em diversas áreas da ciência, dentre elas: economia [6]; medicina [7]; medicina nuclear [8]; biologia [9]; ecologia [10,11]; física do clima [12]; climatologia [13,14]; engenharias [15,16]; modelagem de colisões veiculares [17][18][19][20].…”

Section: Método De Monte Carlounclassified

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Carvalho¹,

Armigliato²,

Almeida³

et al. 2016

Rev. Bras. Crimin.

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ResumoEste trabalho apresenta um modelo para análise probabilística de perícias de colisão de veículos automotores, apresentando um modelo computacional flexível para avaliação da confiabilidade por simulação Monte Carlo. Os procedimentos desenvolvidos buscaram a representação estatística dos parâmetros ambientais e psicomotores, tais como coeficientes de atrito e ritmo de Reação, em uma simulação, com 10.000 iterações, da confiabilidade em um modelo bidimensional aplicado a um estudo de caso de colisão frontal envolvendo dois veículos de passeio, obtendo intervalos unilaterais e bilaterais para as variáveis estudadas. AbstractThis paper presents a model for probabilistic analysis skills collision of motor vehicles, featuring a flexible computational model for the evaluation of reliability by Monte Carlo simulation. The developed procedures sought statistical representation of environmental and psychomotor parameters such as friction coefficient and reaction rate in a simulation with 10,000 iterations, reliability in a twodimensional model applied to a frontal collision case study involving two vehicles, obtaining unilateral and bilateral ranges for the variables studied.

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Section: Método De Monte Carlounclassified

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Carvalho¹,

Armigliato²,

Almeida³

et al. 2016

Rev. Bras. Crimin.

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“…This model was originally conceived to model hydrological phenomena and has been effectively used for this and also for other purposes. For a detailed discussion on the importance and structural properties of KW distribution, one may refer to [15][16][17][18][19][20]. Recently, a considerable body of literature has been devoted to the inference problems based on KW distribution [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

E-Bayesian Estimation for Kumaraswamy Distribution Using Progressive First Failure Censoring

Kotb¹,

Sharawy²,

El-Din³

2021

MMEP

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“…In fact, Kumarasawmy and Beta distributions share numerous characteristics, although some of them are much more readily available, from the mathematical point of view, for the Kumaraswamy distribution. Kumaraswamy distribution is appropriate for the modeling of bounded natural and physical phenomena, such as atmospheric temperatures or hydrological measurements [5,6], record data, such as tests, games or sports [7], economic observations [8], or for empirical data with failure rate with an increasing prior [9]. It is also appropriate in situations where one considers a distribution with infinite lower and/or upper bounds to fit data, when, in fact, the bounds are finite, which makes Kumaraswamy useful in preventive maintenance.…”

Section: Introductionmentioning

confidence: 99%

Reliability and Inference for Multi State Systems: The Generalized Kumaraswamy Case

2021

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Semi-Markov processes are typical tools for modeling multi state systems by allowing several distributions for sojourn times. In this work, we focus on a general class of distributions based on an arbitrary parent continuous distribution function G with Kumaraswamy as the baseline distribution and discuss some of its properties, including the advantageous property of being closed under minima. In addition, an estimate is provided for the so-called stress–strength reliability parameter, which measures the performance of a system in mechanical engineering. In this work, the sojourn times of the multi-state system are considered to follow a distribution with two shape parameters, which belongs to the proposed general class of distributions. Furthermore and for a multi-state system, we provide parameter estimates for the above general class, which are assumed to vary over the states of the system. The theoretical part of the work also includes the asymptotic theory for the proposed estimators with and without censoring as well as expressions for classical reliability characteristics. The performance and effectiveness of the proposed methodology is investigated via simulations, which show remarkable results with the help of statistical (for the parameter estimates) and graphical tools (for the reliability parameter estimate).

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Using Monte Carlo analysis to investigate the relationship between overconsumption and uncertain access to one's personal utility function

Cited by 13 publications

References 35 publications

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Análise probabilística de colisões veiculares pelo método de Monte Carlo

E-Bayesian Estimation for Kumaraswamy Distribution Using Progressive First Failure Censoring

Reliability and Inference for Multi State Systems: The Generalized Kumaraswamy Case

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