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Likelihood is the probability of a set of observations provided the value of some parameter or the set of parameters. For instance, the likelihood of the random sample of n observations with probability distribution, f(x,θ) which can be given by This function is the basis of the maximum likelihood estimation. In number of applications the likelihood includes number of parameters, only a few of which are of interest to investigator. The remaining nuisance parameters are essential in order that the model makes the sense physically, but their values are largely irrelevant of the investigation and the conclusions to be made. Since there are troubles in dealing with likelihoods which depend on a large number of incidental parameters (for instance, maximizing the likelihood will be more tough) some form of modified likelihood is sought which comprises as few of the uninteresting parameters as possible. The number of possibilities is available. For instance, the marginal likelihood, removes the nuisance parameters by integrating them out of the likelihood. The profile likelihood with respect to parameters of interest, is the original likelihood, partly maximized with respect to the nuisance parameters.
Procedures for estimating the probability distributions without supposing any particular functional form. Constructing the histogram is perhaps the easiest example of such type of
Difference b/w historigram and histogram
K-means cluster analysis is the method of cluster analysis in which from an initial partition of observations into K clusters, each observation in turn is analysed and reassigned,
A law supposedly applicable to voting behaviour which has a history of several decades. It may be stated thus: Consider a two-party system and suppose that the representatives of t
Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing
Hosmer-Lemeshow test is a goodness-of-fit test taken in use in logistic regression, particularly when there are regular covariates. Units are spitted into deciles based on predict
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 optimizin
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
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
Regression discontinuity design is the quasi-experimental design in which participants in, for instance, an intervention study, are assigned to the treatment and control groups on
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