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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.
Item-total correlation is an extensively used method for checking the homogeneity of the scale made up of number of items. It is simply the Pearson's product moment correlation c
A construction for events that happen in some planar area a, consisting of the series of 'territories' each of which comprises of that part of a closer to the particular event xi t
Ascertainment bias : A feasible form of bias, particularly in the retrospective studies, which arises from the relationship between the exposure to the risk factor and the probabil
Records on the computer manufacturing process at Pratt-Zungia Limited show that the percentage of defective computers sent to customers has been 5% over the last few years. Shipme
Demographic data: Age: continuous variable Gender: categorical variable with males coded 1, females coded 2. Relationship status: categorical variable 1 to 5. Rational
The particular projection which an investigator believes is most likely to give an accurate prediction of the future value of some process. Commonly used in the context of the anal
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
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
The Current status data arise in the survival analysis if the observations are limited to the indicators of whether or not the event of interest has happened at the time the sample
Ha: If hyperlipidemia is believed to be a side effect of second-generation antipsychotics (SGAs), then Hispanic patients with SGAs treatment will have the higher frequency of devel
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