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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.
This is given by common network e.g. Phone Company. The public networks are those networks, which are given by common carriers. It can be a telephone company or an other organizati
calculate the mean yearly value using the average unemployment rate by month
how to resolve sequencing problem if jobs 6 given and 4 machines given. how to apply johnson rule for making to machines under this conditions. please give solution as soon as poss
Barrett and Marshall Model for conception : A biologically reasonable model for the probability of conception in a particular menstrual cycle, which supposes that the batches of sp
Case-control study : The traditional case-control study is the common research design in the epidemiology where the exposures to risk factors for cases (individuals getting the dis
i have an assignment for experimental design which is must done by SAS program can you help me also i need to hand in the assignment till thursday shall i send it for you ?
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
Balanced incomplete repeated measures design (BIRMD): An arrangement of the N randomly selected experimental units and k treatments in which each and every unit receives k1 treatm
Balanced incomplete block design : A design in which all the treatments are not used in all blocks. Such designs have the below stated properties: * each block comprises the
Goodmanand kruskal measures of association is the measures of associations which are useful in the situation where two categorical variables cannot be supposed to be derived from
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