Wyniki wyszukiwania - Biblioteka Nauki

Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

Ograniczanie wyników

Znaleziono wyników: 5

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: minimax estimation

Sortuj według:

Ogranicz wyniki do:

Minimax estimation of the mean matrix of the matrix-variate normal distribution

100%

Zinodiny S. , Rezaei S. , Nadarajah S.

Probability and Mathematical Statistics

2016

tom Vol. 36, Fasc. 2

187--200

In this paper, the problem of estimating the mean matrix Θ of a matrix-variate normal distribution with the covariance matrix V⊗ Im is considered under the loss functions, ω tr((δ − X)′ Q(δ − X)) + (1 − ω) tr((δ − Θ)′ Q(δ − Θ)) and k[1−e−tr((δ − Θ)′ Γ−1(δ − Θ))]. We construct a class of empirical Bayes estimators which are better than the maximum likelihood estimator under the first loss function for m > p + 1 and hence show that the maximum likelihood estimator is inadmissible. For the case Q = V = Ip, we find a general class of minimax estimators. Also we give a class of estimators that improve on the maximum likelihood estimator under the second loss function for m > p + 1 and hence show that the maximum likelihood estimator is inadmissible.

Minimax estimation in linear models

100%

Drygas H. , University of Kassel

tom 132

Information inequalities for the minimax risk of sequential estimators (with applications)

88%

Gajek L. , Mizera-Florczak B.

Applicationes Mathematicae

1998-1999

tom 25

nr 1

85-100

Information inequalities for the minimax risk of sequential estimators are derived in the case where the loss is measured by the squared error of estimation plus a linear functional of the number of observations. The results are applied to construct minimax sequential estimators of: the failure rate in an exponential model with censored data, the expected proportion of uncensored observations in the proportional hazards model, the odds ratio in a binomial distribution and the expectation of exponential type random variables.

Minimax Prediction for the Multinomial and Multivariate Hypergeometric Distributions

75%

Jokiel-Rokita A.

Applicationes Mathematicae

1998-1999

tom 25

nr 3

271-283

A problem of minimax prediction for the multinomial and multivariate hypergeometric distribution is considered. A class of minimax predictors is determined for estimating linear combinations of the unknown parameter and the random variable having the multinomial or the multivariate hypergeometric distribution.

Numerical methods for linear minimax estimation

63%

Gaffke N. , Heiligers B.

Discussiones Mathematicae Probability and Statistics

2000

tom 20

nr 1

51-62

We discuss two numerical approaches to linear minimax estimation in linear models under ellipsoidal parameter restrictions. The first attacks the problem directly, by minimizing the maximum risk among the estimators. The second method is based on the duality between minimax and Bayes estimation, and aims at finding a least favorable prior distribution.