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PRINCIPLES OF BAYESIAN INFERENCE ASSIGNMENT

RECORD 1494067789 TIME 245 WEEKS 2 DAYS

This is the category applicable when prior information is available about θ; it is well included in the prior distribution of θ. As a example we can consider that if any present model form is similar to a previous model form, and ultimate intention is to update the present model using more newly acquired data then in that case a posterior distribution of θ available from the previous model is suitable to be used as a prior distribution of θ for current model. Using this mechanism each model which is not starting from zero is not based on the newly acquired data but they are based on the collective impact of all type data whether present or past. Ibrahim and Chen, (2000) introduced the power prior as a measure so that past data does not overpower the current data. It is a all together different class of informative prior which is applicable in doing analysis where previous data and results obtained from those data are incorporated. If the present data and past data have a significant level of differences then the prior distribution will keep posterior distribution of θ in the tails. This is done to create less density in its tails. Occasionally informative type of prior is not in the right format to be used, for example if informative prior is hidden in another person or a expert, then in such cases personal belief, in such situations personal beliefs of the expert are also required to be considered. This is known as prior elicitation. We are a premier academic writing agency with industry partners in UK, Australia and Middle East and over 15 years of experience. We are looking to establish long-term relationships with industry partners and would love to discuss this opportunity further with you. Thanks & Regards visit our website. www.freeassignmenthelp.com www.cheapassignmenthelp.com



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