Modern concepts and theorems of mathematical statistics |
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... bution) for all 9 e Q, then Tn 14 1. Basic Definitions, Concepts, Results, and Theorems Moment Generating Functions Determination of a Distribution from Its Moments Probability Integral Transform Unbiased and Asymptotically Unbiased ...
... bution) for all 9 e Q, then Tn 14 1. Basic Definitions, Concepts, Results, and Theorems Moment Generating Functions Determination of a Distribution from Its Moments Probability Integral Transform Unbiased and Asymptotically Unbiased ...
Page 15
Edward B. Manoukian. §1.12. M-Estimators 15 bution) for all 9 e Q, then Tn is called an asymptotically unbiased estimator of a function g(0) if lim^00( g(0) - ^„(0))/<rn(0) = 0. |>„(0) and <rn2(9) are referred to as the asymptotic mean ...
Edward B. Manoukian. §1.12. M-Estimators 15 bution) for all 9 e Q, then Tn is called an asymptotically unbiased estimator of a function g(0) if lim^00( g(0) - ^„(0))/<rn(0) = 0. |>„(0) and <rn2(9) are referred to as the asymptotic mean ...
Other editions - View all
Modern Concepts and Theorems of Mathematical Statistics Edward B. Manoukian No preview available - 2011 |
Modern Concepts and Theorems of Mathematical Statistics Edward B Manoukian No preview available - 1985 |
Common terms and phrases
a-test approximation beta distribution binomial bution called characteristic function Consider the test continuous distribution F(x converges in probability decision function degrees of freedom denote the number density or probability distri distributed random variables distribution with mean distribution with parameters estimator of 9 exponential family F-distribution finite given H0 is rejected hence hypothesis H0 identically distributed random independent identically distributed independent of 9 independent random variables inequality large values least-squares estimate Let Xu likelihood ratio limiting N(0 Manoukian 1986 matrix median noncentral chi-square distribution noncentrality parameter Nonparametric null hypothesis One-Sample order statistics parameter 9 Pitman asymptotic efficiency Poisson population probability density function probability mass function rank rejecting H0 respectively Roussas SC(x sequence Serfling standard normal distribution Student distribution sufficient statistic symmetric test of hypothesis Theorem Two-Sample unbiased estimator v2 degrees variance a2 Xn be independent Yj=i