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Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizing some numerical index of the clustering. Since it is not possible to consider every partition of n individuals into g groups (because of the enormous number of the partitions), the algorithm starts with some given initial partition and considers individuals in turn for moving into the other clusters, creating the move if it causes an improvement in the value of the clustering index. The procedure is continued until no move of the single individual causes an improvement.
Harris and Stevens forecasting is the method of making short term forecasts in the time series which is subject to abrupt changes in pattern and the transient effects. Instances o
The interplay of the genes and environment on, for instance, the risk of disease. The term represents the step away from the argument as to whether the nature or nurture is the pre
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
Radical statistics group : The national network of the social scientists in United Kingdom committed to the critique of statistics as taken in use in the policy making procedure. T
A vague concept which occurs all through statistics. Essentially the term means the number of independent units of the information in an easy relevant to the estimation of the para
The scatter plot of SRES1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plot show that th
Help on my test preparation . .
Observation-driven model is a term generally applied to models for the longitudinal data or time series which introduce within the unit correlation by specifying the conditional
what is operational gaining
Multivariate data is the data for which each observation consists of the values for more than one random variable. For instance, measurements on the blood pressure, temperature an
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