Results 31 to 40 of about 12,404 (50)

Extended Odd Fréchet-G Family of Distributions

open access: yesJournal of Probability and Statistics, 2018
The need to develop generalizations of existing statistical distributions to make them more flexible in modeling real data sets is vital in parametric statistical modeling and inference.
Suleman Nasiru
doaj   +1 more source

VaR: Exchange Rate Risk and Jump Risk

open access: yesJournal of Probability and Statistics, 2010
Incorporating the Poisson jumps and exchange rate risk, this paper provides an analytical VaR to manage market risk of international portfolios over the subprime mortgage crisis. There are some properties in the model.
Fen-Ying Chen
doaj   +1 more source

Forest Fire Risk Assessment: An Illustrative Example from Ontario, Canada

open access: yesJournal of Probability and Statistics, 2010
This paper presents an analysis of ignition and burn risk due to wildfire in a region of Ontario, Canada using a methodology which is applicable to the entire boreal forest region.
W. John Braun   +4 more
doaj   +1 more source

Strong Laws of Large Numbers for Arrays of Rowwise NA and LNQD Random Variables

open access: yesJournal of Probability and Statistics, 2011
Some strong laws of large numbers and strong convergence properties for arrays of rowwise negatively associated and linearly negative quadrant dependent random variables are obtained.
Jiangfeng Wang, Qunying Wu
doaj   +1 more source

On a Batch Arrival Queuing System Equipped with a Stand-by Server during Vacation Periods or the Repairs Times of the Main Server

open access: yesJournal of Probability and Statistics, 2011
We study a queuing system which is equipped with a stand-by server in addition to the main server. The stand-by server provides service to customers only during the period of absence of the main server when either the main server is on a vacation or it ...
Rehab F. Khalaf   +2 more
doaj   +1 more source

A Semiparametric Marginalized Model for Longitudinal Data with Informative Dropout

open access: yesJournal of Probability and Statistics, 2012
We propose a marginalized joint-modeling approach for marginal inference on the association between longitudinal responses and covariates when longitudinal measurements are subject to informative dropouts.
Mengling Liu, Wenbin Lu
doaj   +1 more source

Escalation with Overdose Control Using Ordinal Toxicity Grades for Cancer Phase I Clinical Trials

open access: yesJournal of Probability and Statistics, 2012
We extend a Bayesian adaptive phase I clinical trial design known as escalation with overdose control (EWOC) by introducing an intermediate grade 2 toxicity when assessing dose-limiting toxicity (DLT). Under the proportional odds model assumption of dose-
Mourad Tighiouart   +2 more
doaj   +1 more source

Finding Transcription Factor Binding Motifs for Coregulated Genes by Combining Sequence Overrepresentation with Cross-Species Conservation

open access: yesJournal of Probability and Statistics, 2012
Novel computational methods for finding transcription factor binding motifs have long been sought due to tedious work of experimentally identifying them.
Hui Jia, Jinming Li
doaj   +1 more source

Convergence Rates and Limit Theorems for the Dual Markov Branching Process

open access: yesJournal of Probability and Statistics, 2017
This paper studies aspects of the Siegmund dual of the Markov branching process. The principal results are optimal convergence rates of its transition function and limit theorems in the case that it is not positive recurrent.
Anthony G. Pakes
doaj   +1 more source

A Novel Entropy-Based Decoding Algorithm for a Generalized High-Order Discrete Hidden Markov Model

open access: yesJournal of Probability and Statistics, 2018
The optimal state sequence of a generalized High-Order Hidden Markov Model (HHMM) is tracked from a given observational sequence using the classical Viterbi algorithm. This classical algorithm is based on maximum likelihood criterion.
Jason Chin-Tiong Chan, Hong Choon Ong
doaj   +1 more source

Home - About - Disclaimer - Privacy