Add to ORKGAbstract: This paper studies a general problem of making inferences for functions of two sets of parameters where, when the first set is given, there exists a statistic with a known distribution. We study the distribution of this statistic when the first set of parameters is unknown and is replaced by an estimator. We show that under mild conditions the variance of the statistic is inflated when the unconstrained maximum likelihood estimator (MLE) is used, but deflated when the constrained MLE is used. The results are shown to be useful in hypothesis testing and confidence-interval construction in providing simpler and improved inference methods than do the standard large sample likelihood inference theories. We provide three applications o...
In this paper we study inference for a conditional model with a jump in the conditional density, whe...
Abstract. In this paper we consider latent variable models and intro-duce a new U-likelihood concept...
In statistical theory and practice, a certain distribution is usually assumed and then optimal solut...
Abstract: This paper studies a general problem of making inferences for functions of two sets of par...
We construct limiting and small sample distributions of maximum likelihoodestimators (mle) from the ...
This paper studies the general problem of making inferences for a set of parameters θ in the presenc...
The four-parameter beta distribution is non regular at both lower and upper endpoints in maximum lik...
In practice, nuisance parameters in statistical models are often replaced by estimates based on an e...
We study inference in structural models with a jump in the conditional density, where location and s...
This article deals with the confidence interval estimation of [theta]1, when the parameters [theta]1...
We consider two types of problems in maximum likelihood estimation of parameters of linear functions...
In this paper we consider latent variable models and introduce a new U-likelihood concept for estima...
Truncated observations for some applications and parameters with a certain kind of constraints may p...
We show that three convenient statistical properties that are known to hold forthe linear model with...
This paper concerns normal approximations to the distribution of the maximum likelihood estimator in...
In this paper we study inference for a conditional model with a jump in the conditional density, whe...
Abstract. In this paper we consider latent variable models and intro-duce a new U-likelihood concept...
In statistical theory and practice, a certain distribution is usually assumed and then optimal solut...
Abstract: This paper studies a general problem of making inferences for functions of two sets of par...
We construct limiting and small sample distributions of maximum likelihoodestimators (mle) from the ...
This paper studies the general problem of making inferences for a set of parameters θ in the presenc...
The four-parameter beta distribution is non regular at both lower and upper endpoints in maximum lik...
In practice, nuisance parameters in statistical models are often replaced by estimates based on an e...
We study inference in structural models with a jump in the conditional density, where location and s...
This article deals with the confidence interval estimation of [theta]1, when the parameters [theta]1...
We consider two types of problems in maximum likelihood estimation of parameters of linear functions...
In this paper we consider latent variable models and introduce a new U-likelihood concept for estima...
Truncated observations for some applications and parameters with a certain kind of constraints may p...
We show that three convenient statistical properties that are known to hold forthe linear model with...
This paper concerns normal approximations to the distribution of the maximum likelihood estimator in...
In this paper we study inference for a conditional model with a jump in the conditional density, whe...
Abstract. In this paper we consider latent variable models and intro-duce a new U-likelihood concept...
In statistical theory and practice, a certain distribution is usually assumed and then optimal solut...