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The nonparametric Bayesian inference approach to using the finite mixture distributions for modelling data suspected of the containing distinct groups of observations; this approach does not need the number of mixture components to be known in before. The basic idea is that the Dirichlet procedure induces a prior distribution over the partitions of the data which can then be combined with the prior distribution over parameters and chance. The distribution over partitions can be generated incrementally using Chinese restaurant procedure.
Interval-censored observations are the observations which often occur in the context of studies of time elapsed to the particular event when subjects are not monitored regularl
An investor with a stock portfolio sued his broker, claiming that a lack of diversification in his portfolio had led to poor performance. The data, shown below, are the rates of re
The contingency tables in which the row and column both the categories follow a natural order. An instance for this might be, drug toxicity ranging from mild to severe, against the
The marketing manager of Handy Foods Ltd. is concerned with the sales appeal of one of the company's present label for one of its products. Market research indicates that supermark
Classification matrix: A term many times used in discriminant analysis for the matrix summarizing the results and outputs obtained from the derived classi?cation rule, and obtaine
Homoscedasticity - Reasons for Screening Data Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of
Chebyshev's inequality: A statement about the proportion of the observations which fall within some number of the standard deviations of the mean for any of the probability distri
an oil company is considering whether or not to bid for an offshore drilling contract. The bid would cost $60 with a 65% chance of gaining the contract. Outcome success Probability
Probability judgements : Human beings often require assessing the probability which some event will occur and accuracy of these probability judgements often determines success of o
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
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