Time series, Advanced Statistics

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stationary time series

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Explain Genetic algorithms, Genetic algorithms: The optimization events mo...

Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in

Describe indirect least squares, Indirect least squares: An estimation tech...

Indirect least squares: An estimation technique used in the fitting of structural equation models. Commonly least squares are first used to estimate reduced form parameters. Usi

Define high-dimensional data, High-dimensional data : This term used for da...

High-dimensional data : This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21 st

Pattern recognition, Pattern recognition is a term for a technology that r...

Pattern recognition is a term for a technology that recognizes and analyses patterns automatically by machine and which has been used successfully in many areas of application inc

Expected frequencies, A term commonly encountered in the analysis of the co...

A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw

Relative risk, Relative risk is the measure of the association between the...

Relative risk is the measure of the association between the exposure to a particular factor and the risk or probability of a convinced outcome, calculated as follows     therefor

Explain kurtosis, Kurtosis: The extent to which the peak of the unimodal p...

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

Hypergeometric distribution, Hypergeometric distribution is t he probabili...

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

Data mining, The non-trivial extraction of implicit, earlier unknown and po...

The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte

Log-linear models, Log-linear models is the models for count data in which...

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

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