Optimal Extrapolation of Derivatives.
Orthogonal polynomials in nonlinear analysis of regression.
Parameter estimation in cosine regression
Parameter estimation of S-distributions with alternating regression.
We propose a novel 3-way alternating regression (3-AR) method as an effective strategy for the estimation of parameter values in S-distributions from frequency data. The 3-AR algorithm is very fast and performs well for error-free distributions and artificial noisy data obtained as random samples generated from S-distributions, as well as for traditional statistical distributions and for actual observation data. In rare cases where the algorithm does not immediately converge, its enormous speed...
Polynomials associated with exponential regression
Fitting exponentials to data by the least squares method is discussed. It is shown how the polynomials associated with this problem can be factored. The closure of the set of this type of functions defined on a finite domain is characterized and an existence theorem derived.
Predictions in nonlinear regression models.
Probability distribution of the multivariate nonlinear least squares estimates
Projection pursuit quadratic regression - the normal case
The model of quadratic regression is studied by means of the projection pursuit method. This method leads to a decomposition of the matrix of quadratic regression, which can be used for an estimation of this matrix from the data observed.
Properly recorded estimate and confidence regions obtained by an approximate covariance operator in a special nonlinear model
The properly recorded standard deviation of the estimator and the properly recorded estimate are introduced. Bounds for the locally best linear unbiased estimator and estimate and also confidence regions for a linearly unbiasedly estimable linear functional of unknown parameters of the mean value are obtained in a special structure of nonlinear regression model. A sufficient condition for obtaining the properly recorded estimate in this model is also given.
Properties of the generalized nonlinear least squares method applied for fitting distribution to data
We introduce and analyze a class of estimators for distribution parameters based on the relationship between the distribution function and the empirical distribution function. This class includes the nonlinear least squares estimator and the weighted nonlinear least squares estimator which has been used in parameter estimation for lifetime data (see e.g. [6, 8]) as well as the generalized nonlinear least squares estimator proposed in [3]. Sufficient conditions for consistency and asymptotic normality...
Quadratic regression models
Random thresholds for linear model selection
A method is introduced to select the significant or non null mean terms among a collection of independent random variables. As an application we consider the problem of recovering the significant coefficients in non ordered model selection. The method is based on a convenient random centering of the partial sums of the ordered observations. Based on L-statistics methods we show consistency of the proposed estimator. An extension to unknown parametric distributions is considered. Simulated examples...
Reflexiones sobre la estrategia de medida de los cambios en probabilidad en modelos de elección binarios.
Este trabajo se centra en la evaluación de la medida que, en el marco de los modelos de elección binarios o dicotómicos, se utiliza para reflejar el cambio en la probabilidad ante la variación de una de las variables explicativas. La opción de cuantificación más común ha consistido en utilizar el vector de valores medios de las variables explicativas, lo que podemos entender como poner el énfasis en el comportamiento de un "individuo medio". Frente a esta práctica habitual, efectuamos una propuesta...
Robust estimations in classical regression models versus robust estimations in fuzzy regression models
In this paper are presented two robust estimators of unknown fuzzy parameters in the fuzzy regression model and investigated the relationship between these robust estimators in the classical regression model and in the fuzzy regression model.
Robust quasi-linear system identification
Second-order approximation of the entropy in nonlinear least-squares estimation
Sensitivity analysis of -estimators of non-linear regression models
An asymptotic formula for the difference of the -estimates of the regression coefficients of the non-linear model for all observations and for observations is presented under conditions covering the twice absolutely continuous -functions. Then the implications for the -estimation of the regression model are discussed.
Separable least squares, variable projection, and the Gauss-Newton algorithm.
Sequential estimation method for the minimum of a quadratic regression function
Some limit properties of an approximate least squares estimator in a nonlinear regression model with correlated nonzero mean errors.