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英語(yǔ)人>網(wǎng)絡(luò)例句>interval estimation 相關(guān)的網(wǎng)絡(luò)例句
interval estimation相關(guān)的網(wǎng)絡(luò)例句

查詢?cè)~典 interval estimation

與 interval estimation 相關(guān)的網(wǎng)絡(luò)例句 [注:此內(nèi)容來(lái)源于網(wǎng)絡(luò)外国免费黄色网站,僅供參考]

The interval estimation information given by estimators is classfied. The bargaining interval and bargaining value is also determined for each class information. Then, the information of the bargaining interval and bargaining value is integrated by utilizing the induced ordered weighted averaging operator. The problem to choice the weighted vector of the IOWA operator is also discussed.

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Therefore, a new hypergeometric distribution method is proposed for testability estimation and demonstration. Based on hypergeometric distribution, the maximum likelihood estimate method is applied in point estimation, and the Bayes formula is applied for interval estimation, hence a testability demonstration rule is provided.

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Finishing calculation of mean value, standard deviation, skewness, kurtosis of Beta distribution.(2) Fitting parameters of many kinds of typical distribution and using residual deviation to evaluate fitting precision.(3) Using Beta distribution as an agreed indication distribution applied to many kinds of practical photoelectric measurement distributions.(4) Deriving theory formula of Bayes point estimation about Beta distribution parameters and mean value and standard deviation on the condition of mean square error loss function and supposed the prior distribution is uniform distribution.(5) Generating MCMC sample from post distribution by the method of Gibbs sample algorithm. Calculating bayes point estimation from sample on the condition of mean square error loss function. Calculating confidence interval by an approximate method to complete interval estimation.

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Events,Operation and Relation of Sets, Classical Probability, Geometrical Probability , Statistical Stability of a Frequency, Axioms of Probability, Conditional Probability, Total Probability Theorem, Bayes' Rule,Independent Events,Independent Repeated Trials, One Dimensional Random Variables, Discrete Random Variables, Distribution Function of a Random Variables , Continuous Random Variables, Normal Distribution, Distribution of a Function of a Random Variable, Multidimensional Random Variables, Joint Distribution Function, Marginal Distribution Function,Discrete Two—Dimensional Random Variables,Continuous Two—Dimensional Random Variables, Independent Random Variables, Distribution of Functions of Random Variables,Expectation,Variance, Covariance, Coefficient of Correlation, Bivariate Normal Distribution, Law of Large Numbers, The Central Limit Theorems, Sample and Population ,Chi—Squared, T and F Distributions , Sampling Distributions , Point Estimation , Interval Estimation , Testing Hypotheses , A Test of Significance for Parameters in a Single Sample From a Normally Distributed Population , A Test of Significance for Parameters in Two Sample From Normally Distributed Populations .

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First of all, we introduce some interval methods and propose a new approach to find confidence interval for the slope in homoscedastic measurement error models. The performance of the interval estimation is compared in terms of both coverage probability and its diameter via simulation studies. Second, we suggest two approaches to estimate confidence intervals for the slope and joint confidence regions for both intercept and slope in heteroscedastic measurement error models. Application of these methods are illustrated with real data sets.

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The point estimation and the interval estimation are more ideal. It is worthwhile for other people .

得到的預(yù)測(cè)的點(diǎn)估計(jì)和區(qū)間估計(jì)都較為理想美女的隐私秘视频网站丝袜,具有一定的參考價(jià)值。

In this paper a kind of point estimation and interval estimation using order statistics on percentiles of unknown continuous type totality is studied in this paper.

本文給出了未知連續(xù)型總體百分位點(diǎn)的一種次序統(tǒng)計(jì)量的區(qū)間估計(jì)方法精品国产99国产精品嫩草影院。

The main contents of the course is as follows: events and their probability, random variables and their distributions, moments, point estimation and interval estimation, hypothesis testing, etc.

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We consider multisensor statistical interval estimation fusion for the purpose of estimation of a parameter θ.

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Confidence Interval Estimation, Linear extrapolation, Exponential Estimation were used to compute the demand numbers.

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