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The probability distribution which is a linear function of the number of component probability distributions. This type of distributions is used to model the populations thought to contain the relatively distinct groups of observations. An early instance of the application of this type of distribution was that of Pearson in the year1894 who applied the following mixture of the two normal distributions to the measurements made on a particular type of crab:
Poisson regression In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regre
Models which make use of the smoothing techniques such as locally weighted regression to identify and represent the possible non-linear relationships between the explanatory and th
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if |t | > t = 1.96
A term usually used for unobserved individual heterogeneity. Such variation is of main concern in the medical statistics particularly in the analysis of the survival times where ha
The nonparametric Bayesian inference approach to using the finite mixture distributions for modelling data suspected of the containing distinct groups of observations; this approac
Prognostic scoring system is a technique of combining the prognostic information contained in the number of threat factors, in a manner which best predicts each patient's risk of
The time series for RESI1, HI1 and COOK1 have appeared again with different outlier values even though the 17 outliers found early were removed.
The technique of sampling used in the ecology for determining how much plants or animals are in a given fixed region. A set of randomly placed lines or points is recognized and the
Latin square is an experimental design targeted at removing from the experimental error the variation from two extraneous sources so that a more sensitive test of the treatment ef
properties of chebyshevs lemma
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