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Laplace distribution: The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random variables each having an alike exponential distribution. The examples of the distribution are shown in the Figure. The skewness mean, variance, and kurtosis of the distribution are as follows:
Component bar chart : A bar chart which shows the component parts of the aggregate represented by the whole length of the bar. The component parts are shown as the sectors of bar w
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
The tabulation of a sample of observations in terms of numbers falling below particular values. The empirical equivalent of the growing probability distribution. An example of such
Clustered data : The term applied to both the data in which the sampling units are grouped into the clusters sharing some common feature, for instance families or geographical reg
An unusual aggregation of the health events, real or perceived. The events might be grouped in the particular region or in some short period of time, or they might happen among the
The linear component ηi, de?ned just in the traditional way: η i = x' 1 A monotone differentiable link function g that describes how E(Yi) = µi is related to the linear compon
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
Probability distribution : For the discrete random variable, a mathematical formula which provides the probability of each value of variable. See, for instance, binomial distributi
Bartlett decomposition : The expression for the random matrix A which has a Wishart distribution as the product of the triangular matrix and the transpose of it. Letting each of x
Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit
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