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Multiple imputation: The Monte Carlo technique in which missing values in the data set are replaced by m> 1 simulated versions, where m is usually small (say 3-10). Each of simulated complete datasets is analyzed by the technique appropriate to the investigation at hand, and results are later combined to generate estimates, confidence intervals etc. The imputations are created by the Bayesian approach which needs specification of the parametric model for the complete data and, if necessary, a model for mechanism by which data become missing.
Hear also required is a prior distribution for unknown model parameters. Bayes' theorem is taken in use to simulate m independent samples from the conditional distribution of the missing values provided the observed values. In most of the cases special computation techniques such as Markov chain Monte Carlo methods will be required.
This term sometimes is applied to the model for explaining the differences found between naturally happening groups which are greater than those observed on some previous occasion;
Cochrane collaboration : An international network of the individuals committed to preparing , maintaining and disseminating the systematic reviews of the effects of the health care
This graph for Cross Correlation Function for RES1, RES1 shows that there is possibly negative autocorrelation as there are alternating spikes; also the first spike is negative whi
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The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
Coincidences : Astonishing concurrence of the events, perceived as meaningfully related, with no apparent causal connection. Such type of events abounds in everyday life and is oft
relevancy of time series in business management
Chains of infection : The description of the course of infection among the group of individuals. The susceptibles infected by the direct contact with the introductory cases are sai
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