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Locally weighted regression is the method of regression analysis in which the polynomials of degree one (linear) or two (quadratic) are used to approximate regression function in particular 'neighbourhoods' of the space of explanatory variables. It is many times useful for smoothing scatter diagrams to allow any structure to be seen more clearly and for identifying the possible non-linear relationships between the response and the explanatory variables. A robust estimation procedure (which is usually known as loess) is taken in use to guard against deviant points distorting the smoothed points. Essentially the procedure involves an adaptation of the iteratively reweighted least squares. The example shown in the figure illustrates the situation in which the locally weighted regression differs considerably from the linear failure of y on x as fitted by least squares estimation.
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Personal probabilities : A radically special approach for allocating probabilities to events than, for instance, the commonly used long-term relative frequency approach. In this ty
(a) You are trying to develop a strategy for investing in two different stocks, Stock A and Stock B. The anticipated annual return for a $1000 investment in each stock under four
Collector's problem : A problem which derives from the schemes in which packets of a particular brand of coffe, cereal etc., are sold with coupons, cards, or other tokens. There ar
An approach of using the likelihood as the basis of estimation without the requirement to specify a parametric family for data. Empirical likelihood can be viewed as the example of
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can you help specify the model for an event study and to interpret the results/
Software which started out as the spreadsheet targeting at manipulating the tables of number for financial analysis, which has now developed into a more flexible package for workin
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