Starting from an unbiased estimating function and the corresponding quasi-likelihood, we consider a large class of test statistics. An explicit and readily applicable higher order asymptotic formula is derived for comparing the statistics in the class with respect to the expected lengths of the confidence intervals given by their inversion
Higher-order likelihood methods often give very accurate results. A way to evaluate accuracy is the ...
Abstract: Generalized confidence intervals provide confidence intervals for complicated parametric f...
We discuss higher-order adjustments for a quasi-profile likelihood for a scalar parameter of interes...
Starting from an unbiased estimating function and the corresponding quasi-likelihood, we consider a ...
With reference to a large class of test statistics, higher-order asymptotics on expected lengths of ...
This paper presents discussion of properties of asymptotic confidence intervals based on a normalizi...
We consider a very general class of empirical discrepancy statistics that includes the Cressie--Read...
Often we are interested in the largest root of an autoregressive process. Available methods rely on ...
We consider the problem of comparing predictive intervals for a future observation via their expecte...
General estimating functions are usually used when one desires to conduct inference about a paramete...
For a general class of empirical-type likelihoods for the population mean, higher-order asymptotics ...
We present improved methods for calculating confidence intervals and p values in situations where st...
With reference to the quasi-likelihood arising from an unbiased estimating function, we consider a l...
By the modified directed likelihood, higher order accurate confidence limits for a scalar parameter ...
The likelihood ratio statistic for testing pointwise hypotheses about the survival time distribution...
Higher-order likelihood methods often give very accurate results. A way to evaluate accuracy is the ...
Abstract: Generalized confidence intervals provide confidence intervals for complicated parametric f...
We discuss higher-order adjustments for a quasi-profile likelihood for a scalar parameter of interes...
Starting from an unbiased estimating function and the corresponding quasi-likelihood, we consider a ...
With reference to a large class of test statistics, higher-order asymptotics on expected lengths of ...
This paper presents discussion of properties of asymptotic confidence intervals based on a normalizi...
We consider a very general class of empirical discrepancy statistics that includes the Cressie--Read...
Often we are interested in the largest root of an autoregressive process. Available methods rely on ...
We consider the problem of comparing predictive intervals for a future observation via their expecte...
General estimating functions are usually used when one desires to conduct inference about a paramete...
For a general class of empirical-type likelihoods for the population mean, higher-order asymptotics ...
We present improved methods for calculating confidence intervals and p values in situations where st...
With reference to the quasi-likelihood arising from an unbiased estimating function, we consider a l...
By the modified directed likelihood, higher order accurate confidence limits for a scalar parameter ...
The likelihood ratio statistic for testing pointwise hypotheses about the survival time distribution...
Higher-order likelihood methods often give very accurate results. A way to evaluate accuracy is the ...
Abstract: Generalized confidence intervals provide confidence intervals for complicated parametric f...
We discuss higher-order adjustments for a quasi-profile likelihood for a scalar parameter of interes...
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