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UJI NISBAH KEMUNGKINAN DAN STATISTIK T PADA SEBARAN GENERALIZED WEIBULL
RENDY RINALDY S., “Maximum Likelihood Ratio and T statistic On Generalized Weibull Distribution”. 48 pages The parameter is a particular characteristic of a population . Parameter estimation is an important problem in statistical inference . Parameter estimation is the estimated activity of the predictive value of a given population , because in general the value of the parameter of the distribution is not known so that inferences about the parameters requires a good probability concepts . Parameter estimation activity aims to present the results of the estimation of the population parameter values who based on sample data . Parameter estimation activities closely related to drawing conclusions based on those hypotheses . Expected error can cause errors in the withdrawal hypothesis called type I error and the type of error II.One the methods associated with the estimation of parameters is the maximum likelihood (MLE). MLE is a method of estimating the parameters of the cluster data follows a specific distribution. In this case the general MLE is a method that is applied to maximize the likelihood function from a distribution that maximizes the error to obtain a good guess parameters . And conclusion can be done by determining the value of t statistics obtained by maximizing the value of the likelihood ratio function is obtained by performing a likelihood ratio test . In this paper, will be conducted estimate parameters of the two distributions Weibull distribution and the Generalized Weibull distribution . And furthermore , will do a comparison test between the two Weibull distributions by using Likelihood Ratio Test ( maximum likelihood ratio test ) as well as the method of maximum ratio Keyword : parameters , distributions , hypothesis , the likelihood ratio
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