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Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent associations between the pairs of variables and higher order interactions among more than two variables.
The estimated expected frequencies under the particular models can be found from the iterative proportional fitting. Such type of models is, essentially, the equivalent for the frequency data, of the models for the continuous data used in the analysis of variance, except that interest usually now centres on parameters representing interactions rather than those for the main effects.
Martingale: In the gambling context the term at first referred to a system for recouping losses by doubling the stake after each loss has occured. The modern mathematical concept
The type of longitudinal study in which the subjects receive different treatments on the various occasions. Random allocation is required to determine the order in which the treatm
a psychic claims to be able to "feel colors" there are three pieces of colored paper(red, blue,green) he will place his hand on radomly selected pieces while blindfolded. you perfo
Kurtosis: The extent to which the peak of the unimodal probability distribution or the frequency distribution departs from its shape of the normal distribution, by either being mo
The graph for Partial Autocorrelation Function for RES1 shows that there is no autocorrelation even though there are alternating spikes because they fall inside the 5% significance
The method or technique for producing the sequence of parameter estimates that, under the mild regularity conditions, converges to maximum likelihood estimator. Of particular signi
Projection pursuit is a procedure for attaning a low-dimensional (usually two-dimensional) representation of the multivariate data, which will be particularly useful in revealing
Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal br
Probit analysis is the technique most commonly employed in the bioassay, specifically toxicological experiments where the group of animals is subjected to known levels of a toxin
Uncertainty analysis is the process for assessing the variability in the outcome variable that is due to the uncertainty in estimating the values of input parameters. A sensitivit
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