Invited discussion paper small-sample distributional properties of nonlinear regression estimators (a geometric approach)
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Publication:3212142
DOI10.1080/02331889008802249zbMath0724.62063OpenAlexW2003204186MaRDI QIDQ3212142
Publication date: 1990
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331889008802249
surveysaddlepoint approximationmaximum likelihoodleast squares estimatorgeometric methodsasymptotic normal approximationGaussian errorsnon-Gaussian modelsecond order Edgeworth expansion
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A Dirac-function method for densities of nonlinear statistics and for marginal densities in nonlinear regression ⋮ Pivotal variables and confidence regions in flat nonlinear regression models with unknown σ ⋮ Nonlinear experimental design based on the distribution of estimators ⋮ Unnamed Item ⋮ Higher Dimensional Nonlinear Regression-A Statistical Use of the Riemannian Curvature Tensor
Cites Work
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- Functional relations, random coefficients, and nonlinear regression with application to kinetic data
- Fundamental equations for statistical submanifolds with applications to the Bartlett correction
- Small sample asymptotic expansions for multivariate M-estimates
- Saddlepoint approximations for curved exponential families
- Likelihood and observed geometries
- Theoretical comparison of bootstrap confidence intervals
- On information matrices in nonlinear experimental design
- Estimation for the nonlinear functional relationship
- Parameter transformations for improved approximate confidence regions in nonlinear least squares
- Defining the curvature of a statistical problem (with applications to second order efficiency)
- Strong approximations of the quantile process
- Saddlepoint methods and statistical inference. With comments and a rejoinder by the author
- The geometry of asymptotic inference. With comments and a rejoinder by the author
- Second order asymptotics in nonlinear regression
- Differential geometry of curved exponential families. Curvatures and information loss
- Differential-geometrical methods in statistics
- Approximating exponential models
- Almost exact distributions of estimators ii- hat nonlinear regression models
- Some Problems Connected with Statistical Inference
- On a formula for the distribution of the maximum likelihood estimator
- Saddlepoint approximations for estimating equations
- A Quadratic Design Criterion for Precise Estimation in Nonlinear Regression Models
- Differential geometry of a parametric family of invertible linear systems—Riemannian metric, dual affine connections, and divergence
- On Formulas for the Distribution of Nonlinear L.S. Estimates
- Prepivoting Test Statistics: A Bootstrap View of Asymptotic Refinements
- A note on an estimate for the convergence rate of the LSE in inadequate nonlinear regression models
- Approximate marginal densities of nonlinear functions
- Conditionality resolutions
- Estimable functions in the nonlinear model
- Testing hypotheses in nonlinear regression for nonnormal distributions
- Asymptotic Properties of Non-Linear Least Squares Estimators
- Tubes and Spheres in n-Spaces, and a Class of Statistical Problems
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