Describes general methods of point and interval parameter estimation and the small and large sample properties of estimators: method of moments, maximum likelihood, unbiased estimation, Rao-Blackwell and Lehmann-Scheffe theorems, information inequality, asymptotic relative efficiency of estimators.

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The paper studies the asymptotic behavior of "interior point" on the second mean value theorem for integrals when the length of integral interval tends to be infinite,and the asymptotic estimation formulas under very weak conditions are given.

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For fitting ROC curves and getting the area under the ROC curve, we applied the parametric methods of binormal models and ordinal regression models, the semiparametric method of Cox proportional hazards model, the nonparametric methods of Hanley, Delong This paper also include estimation of required sample size, evaluation of confounding effects, and estimation of standard error and confidence interval by resampling method for ROC analysis.

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The confidence interval of unknown parameter represents the range of the value and the reliability about estimation of parameter.

未知參數(shù)的置信區(qū)間表示該參數(shù)的取值范圍及其可信程度先锋影音AV网站，置信區(qū)間的長度表示區(qū)間估計的精度。

So a Matlab p rogram is developed to op timize interval estimation on variance of normal distribution and p rovide arith2 metic of hypothesis testing on variance of normal distribution.

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Considering the effect of interval on the original estimation accuracy and noise factors, the optimal interval, which minimizes estimation errors, is derived. It is related with MT's velocity. In order to reach the optimal interval, joint velocity estimation and interval calculation are applied. Finally, the feasibility of proposed algorithms is discussed.

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Discussion topics include data analysis, probability concepts, point and interval estimation, statistical inference, hypothesis testing, simple regression model, inference in the simple regression model, general linear statistical model, dummy variables, collinearity, heteroscasticity, autocorrelation, error-related model, the Probit model, the Logit model and the Tobit model, simultaneous equations, and the time-series statistical model

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In order to design a scheme to quantify the observation and to get the fusion estimation from the received bits,the estimation fusion problem was changed into that of decision fusion.The interval was divided into subintervals,each subinterval was assigned a hypothesis,suitable cost coefficients of each hypothesis was selected to form the Bayes cost functional,and a mapping from estimation fusion to decision fusion was constructed.

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