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Method of moments is the procedure for estimating the parameters in a model by equating sample moments to the population values. A famous early instance of the use of the procedure is in Karl Pearson's description of estimating five parameters in the finite mixture distribution with two univariate normal components. Little taken in use in modern statistics since the estimates are known to be less efficient than those given by the alternative procedures such as the maximum likelihood estimation.
Models for the analysis of the survival times, or the time to event, data in which it is expected that a fraction of the subjects will not experience the event of interest. In a cl
This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea o
The Null Hypothesis - H0: There is no first order autocorrelation The Alternative Hypothesis - H1: There is first order autocorrelation Durbin-Watson statistic = 1.98307
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
Modern hotels and certain establishments make use of an electronic door lock system. To open a door an electronic card is inserted into a slot. A green light indicates that the doo
How do I report the results in the table?
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
A procedure whereby the collection of multiple sample units are combined in their entirety or in part, to form the new sample. One or more succeeding measurements are taken on the
sales per day for a product are as follows: x= 10, 11, 12, 13 (p)= 0.2, 0.4, 0.3, 0.1 obtain mean and variance of daily sale. if the profit is described by the following equation p
Cluster analysis : A set of methods or techniques for constructing a sensible and informative classi?cation of an initially unclassi?ed set of data, using variable values observed
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