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Full-Text Articles in Statistics and Probability
To Logit Or Not To Logit Data In The Unit Interval: A Simulation Study, Kayode Idris Hamzat
To Logit Or Not To Logit Data In The Unit Interval: A Simulation Study, Kayode Idris Hamzat
Major Papers
In this paper, we recommend a mechanism for determining whether to logit or not to logit data in the unit interval which is based on quantile estimation of data between 0 and 1. By using a simulated dataset generated from a Beta regression model, the estimated quantile for this model perform better than those based on the linear quantile regression with logit transformation.
Further, we investigate the performance of the quantile regression estimators based on the LQR and we conclude that it is better than those based on the Beta regression when the distribution is contaminated with 10% uniform numbers …
Task Interrupted By A Poisson Process, Jarrett Christopher Nantais
Task Interrupted By A Poisson Process, Jarrett Christopher Nantais
Major Papers
We consider a task which has a completion time T (if not interrupted), which is a random variable with probability density function (pdf) f(t), t>0. Before it is complete, the task may be interrupted by a Poisson process with rate lambda. If that happens, then the task must begin again, with the same completion time random variable T, but with a potentially different realization. These interruptions can reoccur, until eventually the task is finished, with a total time of W. In this paper, we will find the Laplace Transform of W in several special cases.
Extension Of First Passage Probability, Yiping Zhang
Extension Of First Passage Probability, Yiping Zhang
Major Papers
In this paper, we consider the extension of first passage probability. First, we present the first, second, third, and generally k-th passage probability of a Markov Chain moving from one state to another state through step-by-step calculation and two other matrix-version methods. Similarly, we compute the first passage probability of a Markov Chain moving from one state to multiple states. In all discussions, we take into account the situations that one state moves to a different state and returns to itself. Also, we find the mean number of steps needed from one state to another state in a Markov Chain …