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This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea of the algorithm is to replace M-step of each EM iteration with the sequence of S >1conditional or constrained maximization or the CM-steps, each of which maximizes the expected complete-data log-likelihood found in the previous E-step subject to constraints on parameter of interest, θ, where the collection of all the constraints is such that the maximization is over the full parameter space of θ. Because the CM maximizations are over the smaller dimensional spaces, many times they are simpler, faster and more reliable than corresponding full maximization known in the M-step of the EM algorithm.
The probability distribution, f (x), of largest extreme can be given as The location parameter, α is the mode and β is the scale parameter. The mean, variance skewn
Hi , Im currently taking the course Financial Econometrics of Master of Finance at RMIT. I find it really difficult to understand the course''s material and now im having the majo
The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult
Hypergeometric distribution is t he probability distribution related with the sampling without replacement from the population of finite size. If the population comprises of r ele
Auto correlation : The correlation of the internal observations in the time series, generally expressed as a function of the time lag between the observations. It is also used for
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
This is the branch of mathematics which deals with the theory of contests between two or more players under the specified sets of rules. The subject supposes a statistical aspect w
data modelling
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
Network sampling is a sampling design in which the simple random sample or strati?ed sample of the sampling units is made and all observational units which are linked to any of th
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