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Bayesian prediction for flowgraph models with covariates. An application to bladder carcinoma.

, , , and . J. Comput. Appl. Math., (2016)

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Incorporating covariates in a flowgraph model for bladder carcinoma., , , and . IWBBIO, page 1086-1096. Copicentro Editorial, (2014)A flowgraph model for bladder carcinoma., , , and . IWBBIO, page 547-553. Copicentro Editorial, (2013)Computing survival functions of the sum of two independent Markov processes: an application to bladder carcinoma treatment., , , and . Int. J. Comput. Math., 91 (2): 209-220 (2014)Modeling the recurrence-progression process in bladder carcinoma., , , and . Comput. Math. Appl., 56 (3): 619-630 (2008)Corrigendum to "Modeling dependence in the inter-failure times. An analysis in Reliability models by Markovian Arrival Processes" J. Comp. Appl. Math. 343 (2018), 762-770., , and . J. Comput. Appl. Math., (2021)Modelling the failure risk for water supply networks with interval-censored data., , , and . Reliab. Eng. Syst. Saf., (2015)An analysis of the recurrence-progression process in bladder carcinoma by means of joint frailty models., , , and . Math. Comput. Model., 54 (7-8): 1671-1675 (2011)Modeling bladder cancer using a Markov process with multiple absorbing states., , , and . Math. Comput. Model., 52 (7-8): 977-982 (2010)Bayesian prediction for flowgraph models with covariates. An application to bladder carcinoma., , , and . J. Comput. Appl. Math., (2016)Modeling dependence in the inter-failure times. An analysis in Reliability models by Markovian Arrival Processes., , and . J. Comput. Appl. Math., (2018)