Potential Functions and Conservative Estimating Functions
نویسندگان
چکیده
منابع مشابه
Estimating Functions
Estimating functions provide inference methods based on a model for speciied functions of the response variable, such as the mean and variance. The inference methods can use the limiting distribution of the estimating function, or the derived limiting distribution of the estimating function roots, or the derived limiting distribution of the quasi-likelihood function. In fully speciied parametri...
متن کاملEstimating Functions for Discretely
hagen] are generalized to facilitate parameter estimation in discretely observed stochastic diierential equations, where the observations are corrupted by additive white noise. This generalization provides an optimal solution to the parameter estimation problem in terms of estimating functions as an alternative to methods based on the Kalman lter or higher order lters. Using Monte Carlo simulat...
متن کاملAggregate Functions, Conservative Extension, and Linear Orders
1 Summary Practical database query languages are usually equipped with some aggregate functions. For example, \\nd mean of column" can be expressed in SQL. However, the manner in which aggregate functions were introduced in these query languages leaves something to be desired. Breazu-Tannen, Buneman, and Wong 3] introduced a nested relational language NRC(=) based on monads 16, 24] and structur...
متن کاملAggregate Functions, Conservative Extensions, and Linear Orders
1 Summary Practical database query languages are usually equipped with some aggregate functions. For example, \\nd mean of column" can be expressed in SQL. However, the manner in which aggregate functions were introduced in these query languages leaves something to be desired. Breazu-Tannen, Buneman, and Wong 3] introduced a nested relational language NRC(=) based on monads 16, 24] and structur...
متن کاملEstimating Spectral Density Functions Robustly
• We consider in the following the problem of robust spectral density estimation. Unfortunately, conventional spectral density estimators are not robust in the presence of additive outliers (cf. [18]). In order to get a robust estimate of the spectral density function, it turned out that cleaning the time series in a robust way first and calculating the spectral density function afterwards lead...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1994
ISSN: 0090-5364
DOI: 10.1214/aos/1176325372