Asymptotic Variance
The asymptotic variance of the giant component of configuration model random graphs
... the asymptotic variance of the size of the giant component for more general random graphs such as the NSW random graph which we discuss briefly in Section ...7. Variance calculations for random ...
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Asymptotic variance for random walk metropolis chains in high dimensions : logarithmic growth via the Poisson equation
... best of our knowledge, is the first to investigate the growth of the asymptotic variance as the dimension d Ñ 8 in this context. Moreover, it is feasible that our method could be generalised to some of the ...
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Asymptotic variance approximations for invariant estimators in uncertain asset pricing models
... Overall, our theoretical and simulation results suggest that the impact of model misspecification on the asymptotic variance of the ML and CU-GMM estimators can be very large and of practical economic ...
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The asymptotic variance of the giant component of configuration model random graphs
... the asymptotic variance of the size of the giant component for more general random graphs such as the NSW random graph which we discuss briefly in Section ...7. Variance calculations for random ...
36
Minimising MCMC variance via diffusion limits, with an application to simulated tempering
... the asymptotic variance of diffusions by writing them as appropriate limits of discrete-time birth–death chains which themselves satisfy Peskun ...the asymptotic variance of all functionals ...
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Semiparametric Efficient Adaptive Estimation of the PTTGARCH model
... Local Asymptotic Normality (LAN) ...the variance. In Section 3 we show how to compute the theoretical asymptotic variance of the maximum likelihood (ML) and quasi- maximum likelihood (QML) ...
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Asymptotic Efficiency of Maximum Likelihood Estimators Under Misspecified Models
... the asymptotic variance for ˆ equals the upper left hand element of the inverse of the Fisher information matrix based on f ...the asymptotic variance for ˆ is not equal to the lower right ...
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Tests of rank
... the asymptotic variance matrix of the limiting normal distribution of the RTC matrix estimator + Therefore , an important departure for the approach taken in this paper is that no explicit assumptions are ...
25
Bootstrapping the Expected Shortfall
... It is worth mentioning that although there has been a considerable amount of work on properties of block bootstrap methods for smooth functionals of weakly dependent data, not many theoretical results seem to be ...
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Bayesian and Non-Bayesian Estimation for Weibull Parameters Based on Generalized Type-II Progressive Hybrid Censoring Scheme
... The Fisher information matrix I , is then obtained by taking the negative expectation for the second partial derivatives from the natural logarithm likelihood function (8). Since this expectation is difficult to ...
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On the Asymptotic Normality of an Estimate of a Regression Functional
... Its asymptotic normality is proved such that the asymptotic variance depends neither on the dimension of the observation vector, nor on the smoothness properties of the regression ...The ...
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Effects of permanenet trap response in capture probability on Jolly-Seber capture-recapture model estimates.
... As seen in Table 5, the asymptotic variance estimates, var N s' exhibit positive bias under a trap-shy response and negative bias under a trap-happy response.. Survival Rate[r] ...
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Efficiency loss due to data grouping in statistical inference
... In view of the two examples cited above, it would appear that it is better to use the normal theory test in this case even though only the signs of the data are used, and so Bennett*s sign test is of doubtful value. In ...
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Asymptotic Comparison of Parameters Estimates of Two-parameter Weibull Distribution
... joint asymptotic efficiency depends on the sample size and the value of parameter ...joint asymptotic efficiency of the selected estimation and the estimates by the method of ...joint asymptotic ...
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Variance of the Isotropic Uniform Systematic Sampling
... in Theorem 4, which enables us to obtain reasonable approximation of the variance replacing Φ by 1. The resulting formula can be used for selecting the proper sampling density in optimization of the sampling ...
7
A note on Hammersley's inequality for estimating the normal integer mean
... (1.3), improve the bound (1.1), and also determine the asymptotic limit of Bhattacharyya bounds. Also, we use a suitable distance and its limiting prop- erty to show the reason why such bounds cannot be attained ...
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Advances in Portmanteau Diagnostic Tests
... general variance Portmanteau test on Autoregressive Moving Aver- age Model with Generalized Autoregressive Conditional Heteroskedasticity Error (ARMA − GARCH Model), as a special case of weak ARMA model ...the ...
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Automatic variance control and variance estimation loops
... The AVC and variance estimation loops can be implemented either in digital or analogue form. For this work the loops were implemented in software and several different signal types were tested. For convenience, a ...
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On the Spectrum of Asymptotic Expansions for an Asymptotic Normal Sequence
... ing to their asymptotic orders. Step 1 is achieved by first replacing the exponent of the integrand in (1) with its Taylor series expansion, then isolating the quadratic term of the Taylor series and performing a ...
8
Asymptotic hyperfunctions, tempered hyperfunctions, and asymptotic expansions
... For a hyperfunction f , neither its restriction to P(ω,t) nor its integral over this hy- perplane is well-defined in general, see [26, Chapter 3, Section 4]. To remedy that prob- lem, Takiguchi and Kaneko introduce a ...
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